These AI systems can create content, assist with choices, and find trends. They can act as digital helpers, doing tasks that usually need human input. They also spark creativity by making images, text, videos, and audio.

These systems use natural language understanding (NLU) and natural language processing (NLP) to learn and create outputs. However, their understanding is still limited.

This is where prompt engineering comes in. It makes results better by fine-tuning the questions given to AI. The models can be hard to predict, sometimes giving different or unhelpful answers to the same question.

This article will explore how AI boosts output and how prompt engineering makes answers more precise.

What is prompt engineering? 

Prompt engineering is the process of designing and refining prompts to improve the responses of generative AI and large language models (LLMs). It aims to enhance response outputs by optimizing and improving prompt inputs.

Prompt engineering involves designing and refining input instructions to guide artificial intelligence systems in accurately understanding and interpreting user queries. 

This field optimizes how AI systems, particularly language models, process and respond to inputs through techniques that enhance contextual comprehension and logical reasoning. 

Effective prompts ensure that AI systems generate relevant and precise outputs, improving their overall performance and reliability.

These methods help the AI give answers that make sense, are reliable, and stay on topic.

Why is prompt engineering important? 

Many businesses use prompt engineering to work faster and better.

A study by Grand View Research shows the prompt engineering market was worth $222.1 million in 2023. It’s expected to grow by 32.8% from 2024 to 2030. 

As more companies use AI, it’s crucial to make sure AI gives clear, correct answers through smart questioning. We don’t know all the long-term effects of AI yet. This makes it even more vital to check if these tools are reliable.

AI can sometimes create false info, make things up, or state wrong facts. This can happen due to poor training, biased data, or flaws in what it learns.

Prompt engineering helps fix these issues. Better inputs and guiding AI to follow logical steps lead to more precise and focused outputs.

Companies must avoid AI risks that could slow progress. If not managed, these risks can lead to AI spreading lies, creating unfair content, or making bad choices.

Firms must be careful when making and using AI. If not, they risk their good name and might break regulations. Prompt engineering is one way to dodge these problems and keep AI growth ethical and accurate.

This method makes AI outputs more targeted and cuts down on mix-ups.

How does prompt engineering work? 

Prompt engineering uses natural language skills to help AI grasp and follow instructions.

These models use various methods to solve problems, do tasks, and generate different types of content. These methods include machine learning (ML), deep learning (DL), and natural language processing (NLP). 

Despite these combined powers, LLMs often struggle with context and nuance, leading to a range of possible outputs. 

To tackle this challenge, prompt engineers create libraries of templates containing instructional, conversational, and creative scripts. They test and refine various prompt formats, optimizing the model’s understanding of complex instructions.

Let’s take a closer look at how prompt engineering works: 

1. Write a good prompt

Create clear, easy-to-understand prompts for AI tools. Avoid complex words unless they’re needed. Make the AI take on a specific role to get better answers and set clear limits to guide the AI’s response. 

For example, ask it to describe something in three sentences. Don’t use questions that push for a certain answer. This helps get fair responses from the AI and Keep your prompts simple. You must learn how to fine-tune AI models like GPT-3 to improve at prompting. 

These can teach you useful skills for working with different AI tools. Remember, a good prompt is key to getting the results you want from AI.

2. Try and test

Making better prompts takes practice. Start by writing your first prompt based on your need, then use the AI to get an answer. 

Check if the answer matches what you wanted. If not, change the prompt and try again. Keep doing this until you’re happy with the result. While you do this, try your prompt with different inputs, which helps make sure it works well in many situations. 

Testing is a key part of making good prompts. It helps you understand how the AI thinks and how to guide it better. Don’t be afraid to try new ideas and see what works best.

3. Adjust and improve

You can do more than just change the prompt. You can also adjust the AI model itself. This means changing the model’s settings to work better for specific tasks. 

It’s a more complex method, but it can improve the AI’s performance for special uses. This process is called fine-tuning or calibrating the model. It allows you to tailor the AI to your needs. 

To get better at writing prompts, try to understand how (LLMs) work. This can help you write prompts that get the answers you want. You can experiment with different ways to write prompts to see what works best.

Prompt engineering use cases

Understanding the different use cases of prompt engineering helps effectively apply AI across various tasks and industries.

Let’s take a closer look: 

Legal and compliance 

Prompt engineering in law and AI compliance improves document review, contract analysis, and rule checks. Better prompts help AI find key legal terms and spot compliance risks. AI can also handle routine tasks.

Lawyers can then focus on complex choices while AI manages repetitive work. Testing different prompts ensures compliance across regions. Adapting prompts to local laws makes the tool more reliable for legal tasks.

Chatbots 

Prompt engineering makes chatbots and digital assistants more natural and aware of context.

Custom prompts help chatbots better grasp and answer tricky user questions, making customers happier. This tech works in many fields—from shops handling buyer queries to healthcare aiding patient talks.

By fine-tuning prompts, chatbots become smarter and able to give correct info, solve issues faster, and offer personal service. This makes them key in customer care across many areas.

Healthcare 

In healthcare, prompt engineering boosts AI use for patient diagnosis, treatment advice, and office tasks.

Well-made prompts ensure AI systems read complex medical data correctly, aiding in faster diagnosis and custom treatments. They also smooth patient talks, like booking visits or managing follow-ups, making work more efficient.

In remote care, prompt engineering helps refine virtual visits, ensuring patient questions are understood and answered well, leading to better health results.

Business intelligence and analytics 

Prompt engineering is essential in business insights by making data queries more precise. Custom prompts let AI systems pull useful insights from big data sets, aiding decision-making.

This helps in real-time analysis, where firms rely on precise, prompt-driven AI models to predict trends, track performance, and find chances.

Better prompts ensure AI tools give relevant, timely, and fitting insights. This approach drives strategic business plans and helps stay ahead of rivals.

Education and training 

In education, prompt engineering refines AI tools for personal learning and effective training.

Custom prompts let AI adapt to each learner’s style, giving tailored content and feedback that boosts student interest and understanding.

For job training, prompt engineering helps create adaptive modules that respond to worker performance in real-time.

This leads to faster skill growth and better knowledge retention, making learning and training more dynamic and responsive to each person’s needs.

Software development 

Prompt engineering is vital in software creation. It helps automate coding tasks and improve design processes. Well-crafted prompts help AI systems write code snippets, fix software, and suggest improvements.

This cuts down on time spent on routine tasks. As a result, development gets faster, and code quality gets better. Prompt engineering also aids software testing by guiding AI to find potential bugs or weak spots.

It ensures the final product is strong and secure. Prompt engineering helps teams streamline work and boost software performance.

Software engineering 

Prompt engineering in software engineering refines AI tools for system design, analysis, and optimization tasks.

Precise prompts help AI systems grasp complex engineering needs and create optimal designs or solutions. This helps in big projects where efficiency and precision are key.

Automating routine tasks with prompt engineering lets engineers focus on new ideas and strategic growth. This improves overall project outcomes and reduces errors in the engineering process.

Cybersecurity and computer science 

Prompt engineering in cybersecurity boosts threat detection, response, and system weakness analysis.

Better prompts enable AI systems to spot and stop potential security threats more accurately, ensuring strong protection against cyber-attacks.

In computer science, prompt engineering improves algorithm performance and optimizes computer processes.

It enables AI models to adapt to new threats and tech advances, making them more effective in protecting digital assets and advancing computer research.

This leads to safer, more efficient, innovative solutions in both fields.

Fine-tuning AI through prompt engineering 

Prompt engineering is key in developing AI systems that give precise and reliable results.

Crafting targeted prompts helps AI grasp context, process data well, and produce outputs that match specific business goals. This precision is crucial for ensuring AI’s practical use across various sectors.

Creating explainable AI should be a priority as it becomes more common in businesses. Transparency in AI decision-making is essential, especially as these models become key to business operations. Prompt engineering must set clear system rules, ensuring AI follows logical reasoning and clear processes.

Companies need to refine and customize AI solutions to meet their specific needs. Generic, one-size-fits-all tools can hinder innovation and lead to inefficiency. A tailored approach ensures AI drives meaningful business outcomes.

Adopting a step-by-step approach in prompt engineering, with ongoing testing, allows businesses to refine AI systems.

FAQs

1. Is prompt engineering a real job?

Yes, prompt engineering is a real job. It focuses on crafting and refining prompts to improve AI model responses. This role is critical in maximizing the effectiveness of AI systems, particularly with advanced models like GPT.

2. What is prompt engineering salary?

The estimated annual total compensation for a Prompt Engineer AI is ₹9,79,006. The average base salary is ₹7,00,500 per year. These figures represent the median, calculated from Glassdoor’s proprietary Total Pay Estimate model.

3. Is prompt engineering difficult?

Prompt engineering can be challenging, as it requires a deep understanding of AI models and the ability to craft precise instructions to achieve desired results. It involves continuous experimentation, problem-solving, and creativity to fine-tune prompts.

The post What is prompt engineering & how does it work? appeared first on Digital Adoption.

From digital databases that store our financial information to sophisticated systems that calculate complex transactions, the success of modern financial services is inherently linked to technology.

The rise of AI will only continue to impact banking and fintech. Major strides in data and computer sciences have seen AI graduate from the pages of science fiction. Today, AI’s applications are catapulting operational capabilities. Not just in finance but industry-wide.

The benefits of AI, from precise decision-making to pattern detection, position it as a catalyst for innovation.

In this article, we’ll explore AI in finance. We’ll define it and explore examples of how it’s used in the sector today. We’ll also uncover the top AI applications and tools the finance sector leverages.

What is AI in finance?

AI in finance involves augmenting financial services capabilities through artificial intelligence technology. Some forms of AI in finance involve training computers to learn and perform complex tasks without pre-programming. 

Grandview Research reveals the global market for artificial intelligence in financial technology was worth 9.45 billion US dollars in 2021. They expect this market to grow steadily at 16.5% annually until 2030.

In finance, these systems primarily employ data-dependent AI, such as machine learning (ML) and deep learning (DL). ML in fintech teaches computers to automate activities and strengthen decision-making processes based on data they have learned. 

Others often leverage rule-based AI for more acute processes, such as anomaly detection. These more stringent forms of AI are designed to identify and address specific issues with high precision.

What are some AI applications in finance?

Artificial intelligence (AI) is revolutionizing the finance industry by introducing advanced applications that enhance decision-making and operational efficiency.

AI is reshaping how financial institutions manage risk and deliver personalized customer experiences.

Let’s take a closer look. 

Speech recognition

Speech recognition enables users to interact hands-free with banking systems, enhancing security and convenience. Customers can authenticate transactions and access account details through voice commands. 

In trading, speech recognition facilitates real-time updates and swift order executions. It also improves trader efficiency and responsiveness to market changes. It can accurately convert spoken words into actionable data, streamlining customer service and functional workflows within financial institutions. This enables intuitive user interfaces across digital platforms. 

This is a pivotal advancement in user experience and operational resilience in the financial sector.

Sentiment analysis

Sentiment analysis uses natural language processing to interpret and quantify market sentiment from textual data sources. 

This technology analyzes massive data sets from social media, news articles, and financial reports. It accurately assesses public perception and investor sentiment. Financial institutions use this analysis to make informed decisions about market trends, customer sentiment, and investment opportunities based on the tone and context of communications.

This real-time analysis helps adjust trading strategies and optimize risk management practices. It also ensures proactive responses to evolving market dynamics and enhances decision-making processes.

Anomaly detection

Anomaly detection is pivotal for identifying irregular patterns within extensive datasets. This technology detects unusual behaviors in transactions and market activities, enhancing fraud prevention and risk management strategies. 

Advanced machine learning algorithms enable financial institutions to monitor and respond to anomalies in real-time. This helps fortify security and ensure operational resilience.

Anomaly detection also optimizes operational efficiency by pinpointing discrepancies in trading activities and market behaviors. It enables timely interventions to mitigate risks and enhance overall performance. 

Recommendations

AI algorithms generate recommendations that provide valuable insights into financial decision-making. They analyze historical data, market trends, and customer behaviors to offer personalized investment advice and portfolio recommendations.

Machine learning models empower financial advisors to optimize asset allocation strategies, which can be tailored to individual risk profiles and financial goals. AI-driven recommendations enhance customer engagement by delivering timely insights and actionable suggestions, which breeds trust and satisfaction. 

Integrating these technologies empowers financial institutions to offer more informed, responsive, personalized services. This improves client outcomes and drives competitive advantage in the evolving financial landscape.

Translation

AI-powered translation capabilities are transforming finance by breaking language barriers and facilitating seamless communication across global markets. 

This technology ensures accurate and efficient financial documents, reports, and communications translation. It also enables international collaboration and regulatory compliance for financial institutions. It leverages neural networks and NLP to confidently engage with stakeholders worldwide, allowing them to translate complex financial information accurately while preserving context.

AI-driven translation tools streamline operations, enhance transparency, and support decision-making by providing timely access to multilingual data and insights. This capability is crucial in expanding market reach, boosting global partnerships, and driving innovation within the financial industry.

Document processing

Intelligent document processing automates and optimizes the handling of extensive paperwork and digital documents. 

This technology swiftly extracts and analyzes data from forms, contracts, and financial statements. Machine learning algorithms streamline document workflows, reducing manual errors and processing times for greater efficiency. It also enhances compliance with regulatory standards by facilitating consistent and thorough document analysis.

It enables rapid information retrieval, supports informed decision-making, and boosts overall operational efficiency. This empowers professionals to focus on strategic initiatives while upholding data integrity and security standards.

Image recognition

Image recognition technology in finance is changing how institutions analyze and use visual data.

It automates the analysis of images like checks, IDs, and financial documents. This improves processes such as document verification and fraud detection. Advanced algorithms help financial entities interpret and extract information from images, minimizing errors.

Image recognition also enhances customer experience by enabling faster and more secure document handling, ensuring compliance with regulatory standards. This technology fosters innovation in financial services by integrating visual data into decision-making processes, enhancing risk management and operational insights.

Conversations

Conversations in finance are being transformed through advanced digital communication tools that facilitate seamless interaction between institutions and clients. 

These tools enable real-time dialogue across multiple platforms, enhancing customer engagement and satisfaction. Financial organizations leverage these capabilities to provide personalized assistance, address inquiries promptly, and offer tailored solutions. 

Efficient communication channels, like interactive websites and mobile apps, allow institutions to optimize service delivery and ensure customers receive a responsive experience. Conversations also play a crucial role in internal operations, enabling collaboration and knowledge sharing. 

Data science and analytics

Data science and analytics are essential tools in finance. They help institutions analyze large datasets to make informed decisions and improve operations. 

These fields use statistics and models to find trends in financial data. Financial companies use them to manage risk better, invest smarter, and work more efficiently.

Data insights also help understand customers, personalize services, and predict market trends. These skills are like a superpower, helping them follow rules, innovate, stay competitive, and gain valuable insights.

Predictive modeling

Predictive modeling is essential in modern finance. It utilizes statistical methodologies to forecast future trends and behaviors based on historical data analysis. 

This method enables financial institutions to anticipate market movements, understand customer preferences, and optimize investment strategies. Predictive modeling identifies patterns and correlations within datasets. This helps mitigate risks, allocate resources effectively, and improve operational efficiency.

It also supports personalized customer interactions and targeted marketing efforts, enhancing service delivery and customer satisfaction. Ultimately, predictive modeling empowers finance professionals to navigate uncertainties and capitalize on opportunities in a dynamic economic environment.

Cybersecurity

Cybersecurity is critical in the finance sector. It ensures the protection of sensitive information and transactions from cyber threats. 

Financial institutions need strong cybersecurity. It protects client data and builds trust. They use effective strategies and technology. This keeps data safe, blocks unauthorized access, and reduces cyberattack risks.

Strong cybersecurity helps them follow regulations, stay financially stable, and make operations more resilient. They achieve this with advanced encryption, multi-layered authentication, and continuous monitoring to find and respond quickly to threats.

Prioritizing cybersecurity also safeguards client assets and reinforces digital trust in financial services.

Generative AI

Generative AI is reshaping finance using computational algorithms to create novel data and simulations that simulate real-world scenarios. 

Generative AI is transforming finance with powerful computer programs. These programs create realistic fake data for testing and training. This fake data helps build better models to predict the future and manage risks.

Generative AI also analyzes customer behavior and preferences by recommending personalized financial products and services.

It also supports decision-making processes by providing insights derived from complex data analysis. Generative AI empowers finance professionals to improve operational efficiency and deliver enhanced customer experiences in an increasingly data-driven world.

What are some examples of AI in finance?

Understanding examples of AI in finance is crucial as it illustrates how technology enhances efficiency, innovation, and regulatory compliance in the industry. AI’s impact reshapes operations and decision-making paradigms from automating complex processes to predicting market trends.

Personalize services and products

AI enables financial institutions to personalize services and products for their customers. AI algorithms can identify individual preferences and behaviors by analyzing vast data sets. 

Banks can offer tailored financial advice, customized investment portfolios, and personalized banking services. For instance, AI-driven chatbots provide real-time assistance, while machine learning models predict customer needs and suggest relevant financial products. Personalized services enhance customer satisfaction and loyalty, driving better engagement and retention. 

AI’s ability to deliver bespoke financial solutions transforms the customer experience, making it more intuitive and responsive to individual needs.

Create opportunities

AI creates numerous opportunities in the finance sector by optimizing processes and uncovering new revenue streams. 

Powerful data analysis and machine learning are giving financial companies a big edge. They can now spot upcoming market trends, better assess investment risks, and even create new financial products. AI can also trade super fast using complex computer programs, making better decisions than humans in a fraction of a second.

Additionally, AI-driven fraud detection systems help secure transactions and build customer trust. By leveraging AI, financial firms can streamline operations, reduce costs, and capitalize on new business opportunities, ultimately driving growth and maintaining a competitive edge in the industry.

Manage risk and fraud

AI plays a crucial role in managing risk and fraud in the finance sector. Advanced machine learning algorithms analyze vast datasets to identify unusual patterns and behaviors indicative of fraudulent activities. 

Financial institutions are deploying real-time monitoring systems powered by AI. These systems detect and flag suspicious transactions, significantly reducing fraud. AI-driven risk management tools assess creditworthiness more accurately than traditional methods.

They can predict potential defaults with greater precision. These adaptive AI systems enhance their predictive capabilities by continuously learning from new data. This provides financial institutions with robust tools to mitigate risks and safeguard assets.

A proactive approach significantly strengthens the security and reliability of financial operations.

Enable transparency and compliance

AI is becoming a game-changer for financial institutions, promoting both transparency and compliance.

Advanced algorithms can quickly analyze massive datasets, automating regulatory checks and ensuring companies follow the rules. These AI tools also act as watchdogs, identifying irregularities and guaranteeing accurate reporting. Real-time transaction monitoring further strengthens compliance efforts.

By integrating AI solutions, financial companies streamline operations and build trust with regulators and clients. They can ultimately create a more stable and transparent economic environment. This approach mitigates risks and promotes a healthy financial system for long-term growth.

Automate operations and reduce costs

AI’s powerful automation is transforming efficiency and costs in finance. Advanced algorithms and machine learning streamline tasks like data entry, reconciliation, and customer service. This speeds things up and ensures accuracy, boosting overall efficiency.

AI goes a step further with predictive analytics. Analyzing past data and forecasting trends helps allocate resources wisely and avoid unnecessary spending. These AI technologies deliver significant cost savings and make resource allocation more flexible. This keeps financial firms competitive in today’s dynamic economy.

AI’s future impact on finance

The future of AI in finance promises a dramatic transformation. Cutting-edge technologies will revolutionize traditional practices, driving innovation across the industry.

Integrating artificial intelligence into financial services will deliver significant benefits as it evolves. We can expect enhanced efficiency, improved decision-making, and a profound reshaping of how customers interact with financial services.

AI’s role in personalized finance is set to redefine customer experiences. AI can analyze customer behaviors and preferences through sophisticated algorithms and natural language processing to offer tailored financial advice and product recommendations. This improves customer satisfaction and deepens client engagement and loyalty.

AI-driven automation is also expected to streamline operational processes within financial institutions. Tasks such as document processing, compliance monitoring, and fraud detection can be performed more efficiently and accurately through AI technologies, freeing human resources for more strategic and value-added activities.Looking ahead, the adoption of AI in finance is backed by promising data and real-world examples showcasing its benefits. For instance, the Government Office for Science has demonstrated that AI-powered trading algorithms can outperform human traders in speed and accuracy, improving investment outcomes.

The post AI in finance: Applications + examples appeared first on Digital Adoption.

That’s because organizations that use them save time in IT cost optimization efforts. They also enhance the digital employee experience by solving common issues efficiently.

A digital assistant (or virtual assistant) is a technology that can complete simple tasks. It can also answer questions or guide confused users. It bridges the gap in human support by solving common or basic problems. It saves time, reduces costs, and enhances user experiences, often as part of an AI-driven digital transformation.

This article explains what a digital assistant is. We clarify what digital assistants can do, the types currently available, how you can use them, and popular examples. After reading it, you will know whether you need one and what type suits your needs.

Examples of popular digital assistants

Several examples of digital assistants exist, but the five tools below are all examples of enterprise technology. They will all suit various enterprise applications. 

Enterprise digital assistants include:

IBM Watsonx Assistant

IBM Watsonx Assistant interacts with users using advanced AI, natural language understanding (NLU), and machine learning. Organizations can deploy it across multiple channels to provide customer support and automate tasks.

Enterprise features of IBM Watson Assistant include: 

• Multi-channel support: Seamless integration with web, mobile, and messaging platforms.
• Customizability: Allows businesses to tailor the assistant to their specific needs.
• Analytics: Provides detailed performance tracking and insights.

IBM Watson Assistant is highly scalable and customizable, fitting diverse enterprise needs. However, to maximize effectiveness, significant initial setup and training are required.

Microsoft Power Virtual Agents

Microsoft Power Virtual Agents on Azure enables businesses to build chatbots using a no-code/low-code interface. It integrates with Microsoft 365 and Dynamics 365, allowing for streamlined automation and support.

Enterprise features of Microsoft Power Virtual Agents include:

• No-code Interface: Easy bot creation without needing deep technical skills.
• Integration with Microsoft Products: Seamless integration with Microsoft 365, Dynamics 365, and other Power Platform services.
• AI-driven Insights: Provides analytics and AI-driven insights to improve performance.

Microsoft Power Virtual Agents is user-friendly and integrates well with existing Microsoft ecosystems. However, it is limited to Microsoft environments, which may restrict flexibility for some enterprises.

Salesforce Einstein Bots

Salesforce Einstein Bots leverage AI and natural language processing to handle customer inquiries and automate tasks within the Salesforce ecosystem.

Enterprise features of Salesforce Einstein Bots include:

• CRM Integration: Direct integration with Salesforce CRM for seamless customer data access.
• Pre-built Templates: Offers templates for common use cases to speed up deployment.
• Real-time data access: Provides real-time updates and data handling within the Salesforce platform.

Salesforce Einstein Bots enhance customer service efficiency within the Salesforce environment. This assistant is best for businesses already using Salesforce, limiting broader applicability.

Oracle Digital Assistant

Oracle Digital Assistant uses AI and machine learning to provide contextual responses and automate workflows. It integrates with Oracle Cloud and other enterprise systems.

Enterprise features of Oracle Digital Assistant include:

• Pre-built skills: Skills include Oracle applications like ERP, HCM, and CX.
• Multi-channel deployment: Supports deployment across web, mobile, and messaging platforms.
• Multilingual support: Offers support for multiple languages to cater to global enterprises.

Oracle Digital Assistant offers deep integration with Oracle’s suite of enterprise applications.

However, like Salesforce Einstein Bots, Oracle Digital Assistant’s benefits are less significant for non-Oracle-focused organizations.

SAP Conversational AI

SAP Conversational AI employs natural language processing and machine learning to build and manage chatbots. It integrates with SAP’s enterprise solutions to enhance productivity and support.

Enterprise features of Oracle Digital Assistant include:

• Integration with SAP solutions: Seamlessly connects with SAP ERP, C/4HANA, and other enterprise systems.
• Low-code bot building: Allows creation of chatbots with minimal coding required.
• Performance analytics: Offers detailed analytics and performance metrics.

SAP Conversational AI optimizes workflows and support within the SAP ecosystem. Its design suits SAP environments. The design limits its use outside the SAP ecosystem.

Examine this list of examples of digital assistants. Ensure you invest in the right tool for your needs. 

Types of digital assistants

There are three main types of digital assistants. Before investing, consider each one and how it might align with your needs. 

Virtual assistants

Virtual personal assistants, like Microsoft’s Cortana or Samsung’s Bixby, offer assistance personalized to the user’s needs. They manage schedules, set reminders, send messages, and can often integrate with many other applications for a seamless workflow. 

They use AI to learn user preferences and habits, enhancing productivity and offering a tailored, efficient user experience across various devices and platforms.

Chatbots

Chatbots, such as those integrated into customer service websites or messaging apps like Facebook Messenger, provide text-based interactions. They handle customer inquiries, offer product information, and can assist with troubleshooting. 

Chatbots use natural language processing. They use this technique to understand and respond to user inputs. This process streamlines customer support and engagement. OpenAI’s ChatGPT, MS Cortana, and Google Gemini are all examples of chatbots.

AI-powered assistants

AI-powered assistants use machine learning (ML) and natural language processing (NLP. They use these techniques to understand and respond to users’ requests. They are intelligent because they can learn from user interactions. They also adapt to user preferences and improve accuracy over time. 

These assistants enhance productivity and provide personalized support. They can also streamline tasks, making daily activities more efficient and user-friendly. ChatGPT uses AI to power its digital assistant capabilities. 

Consider these three digital assistant types and choose the best one for your needs to ensure ROI.

What do digital assistants offer?

Before you invest in a digital assistant, you’ll need to know what they can do. Then you’ll know if they will work for you and increase efficiency. 

The list of tasks a digital assistant can do includes:

Centralize information

A digital assistant centralizes information. It aggregates data from diverse sources such as databases, documents, and APIs. 

It offers a unified interface where users can access crucial information swiftly and efficiently. This approach reduces the time spent searching multiple platforms and ensures consistency in data retrieval across the organization.

Support task prioritization

Digital assistants aid in task prioritization. They evaluate the urgency and importance of tasks. 

Digital assistants analyze deadlines, dependencies, and user preferences to help users focus on high-priority activities. They can also be useful productivity software. 

It optimizes time management and employee productivity. This process ensures that critical tasks receive appropriate attention, enhancing overall efficiency and team goal achievement.

Automate employee tasks

Automating repetitive tasks is a hallmark of digital assistants.

They free employees from mundane activities. These activities include data entry, scheduling meetings, or updating records. 

By handling routine tasks, assistants allow employees to concentrate on more complex and value-added responsibilities. This process boosts productivity. It also increases job satisfaction while reducing operational costs.

Increase data accessibility

Real-time data access is crucial for digital assistants, ensuring they provide accurate and timely information to users. 

By integrating with data sources and APIs, assistants swiftly retrieve up-to-date information, enhancing decision-making processes and operational efficiency. This capability ensures users have reliable access to the latest data insights, improving overall organizational agility and responsiveness.

Streamline approval processes and workflows

Digital assistants streamline approval workflows by automating routing, notifying stakeholders, and tracking progress. 

They facilitate faster decision-making and reduce bottlenecks in processes like expense approvals, purchase orders, or document reviews. By preemptively addressing potential delays or issues, assistants enhance operational efficiency and ensure smoother workflow management across departments.

Employee onboarding and HR assistance

Digital assistants streamline digital employee onboarding by guiding new hires through paperwork, policy reviews, and benefits enrollment. 

They assist with common HR queries, provide information on company policies, and facilitate smoother integration into the organization. ChatGPT prompts for HR contain a helpful list of ways HR teams can use ChatGPT as a digital assistant. When they automate administrative tasks, assistants enhance HR efficiency and improve employee satisfaction during the critical onboarding phase.

Sales and CRM integration

Digital assistants support sales teams by managing leads, tracking pipelines, retrieving customer information, and automating follow-up actions. 

They integrate seamlessly with CRM systems. This allows them to enhance sales processes, improve customer relationship management, and ensure timely engagement with prospects. 

This approach boosts sales team productivity and effectively nurtures customer relationships throughout the sales lifecycle.

Project management support

Digital assistants can benefit project management. These tools facilitate project planning, assign tasks, track progress, and send milestone reminders. 

They enhance team collaboration. They achieve this by centralizing project-related communications and documentation/ Doing so ensures aligned project goals and timelines. 

This feature helps teams stay organized, meet deadlines, and achieve project milestones within budget constraints.

Data analysis and reporting

Digital assistants contribute to data analysis and reporting. They generate reports, analyze data trends, and provide actionable insights. They also assist in decision-making by presenting data-driven recommendations based on real-time analytics. This approach allows them to support strategic initiatives and business intelligence efforts. 

The data analysis and reporting feature enables organizations to leverage data effectively. They can engage in data-driven decision-making to unlock competitive advantage in the marketplace.

Digital assistant use cases 

Enterprises can leverage digital assistants for various purposes. They can enhance efficiency, streamline operations, and improve customer service. 

When AI and machine learning drive digital assistants, they can handle mundane tasks, freeing human employees for more complex activities. 

Customer service

Digital assistants can provide 24/7 customer support, handle routine inquiries, resolve common issues, and escalate complex problems to human agents. Organizations using them in this way reduce wait times and improve customer satisfaction. 

You can also ensure consistent, reliable service, enhancing the overall customer experience and brand loyalty. This approach will lead to satisfied customers who continue to purchase products and use your services. 

Employee assistance

Internally, digital assistants help employees by managing schedules, setting reminders, and providing quick access to information. They can complete simple tasks like answering questions, assisting with HR queries, and streamlining workflow. This approach increases productivity and allows staff to focus on strategic, high-value tasks that require human expertise.

Data management

Digital assistants assist in data entry, retrieval, and analysis. They pull reports faster than human staff could hope to achieve, analyze trends, and provide actionable insights. This implementation aids in informed decision-making, ensures data accuracy, reduces manual effort, and enables businesses to harness the full potential of their data resources.

Automating routine tasks

Digital assistants can automate booking meetings, sending follow-up emails, and processing orders. This approach reduces the risk of human error, ensures staff can tick off tasks promptly, and frees employees to concentrate on more critical and innovative aspects of their roles that drive innovation and growth.

Systems integration

Digital assistants integrate with various enterprise systems, such as CRM and ERP, providing seamless access to information across different platforms. This integration improves workflow efficiency, enables real-time data sharing, enhances collaboration, and supports a cohesive and integrated approach to efficient business operations.

Inventory management

Digital assistants monitor stock levels, place reorder requests, and track inventory movements. When you take this approach, you receive the reward of optimal stock levels, reduce the risk of overstocking or stockouts, and streamline your inventory management, reducing waste and saving resources for the organization.

Scheduling

Digital assistants manage appointments, meetings, and reminders for employees. They help maintain organized schedules, reduce the likelihood of conflicts, and increase overall productivity by ensuring that employees can focus on their tasks without worrying about calendar management.

Training and onboarding

Digital assistants provide new employees with the information, resources, and training materials they need to quickly settle in and gain knowledge. 

Leveraging digital assistants in this way accelerates the onboarding process, ensures consistent training, and helps new hires become more productive, enhancing their integration into the organization and overall employee satisfaction.

Financial tasks

Digital assistants handle tasks such as processing invoices, managing expense reports, and executing routine financial transactions. This approach improves accuracy, speeds up financial processes, reduces manual workload, and ensures compliance with financial regulations, ultimately enhancing overall economic efficiency.

As you can see from the ways you can use digital assistants above, they help enterprises save time, reduce costs, and enhance employee and customer experiences.

Consider your needs before investing in a digital assistant

Before investing in a digital assistant, assess your specific needs. 

First, identify tasks you need to automate. Next, consider integration requirements with existing systems. Also include preferred communication channels (voice, text) and desired features. 

Compare your list of needs to what specific digital assistants can do.

For example, Salesforce Einstein Bots is great for companies that use Salesforce. But it has limited potential for companies that don’t. Compare the digital assistant budget to your budget. Invest in a digital assistant when you are sure it meets your needs.

A well-suited digital assistant can enhance efficiency and productivity, while a poor match might lead to frustration and wasted resources. Invest in the right digital assistant to maximize efficiency and increase revenue.

The post What is a digital assistant? Examples + types appeared first on Digital Adoption.

Your business plans need specific and technical expertise to record them correctly so they are easy to follow and can drive digital transformation.

The number of technical writer roles will likely grow by 7% from 2022 to 2032. This statistic shows that the need for technical writing will increase over the next ten years and that organizations now accept they need these experts for many business purposes.

This article covers 17 comprehensive and detailed examples. 

When you finish reading, you’ll know what technical writing you need for every purpose. 

This knowledge will make your products easy to use, and based on structured, well-documented plans and outstanding user support, you will position your organization strongly against competitors.

17 Examples of technical writing

These 17 common examples of technical writing cover everything an enterprise might need. Take a look and find something relevant to your organization that fulfills a need, and invest today.

1. User guides

Image: manula

User guides are instructional manuals designed to help users understand and operate products or systems during customer onboarding. 

These documents provide step-by-step instructions, troubleshooting tips, and detailed explanations of features and functions.

User guides are crucial for enterprises. They improve user experience by helping customers use products efficiently, reducing support needs, boosting satisfaction, and cutting costs. One enterprise example is a user guide for new employees on company software and policies.

Enterprises can integrate user guides into support and training, offer digital versions, and enhance them with multimedia for better engagement.

2. Release notes 

Image: markvsql

Release notes document changes, fixes, and enhancements in software updates. 

Enterprises use them to inform users about updates, new features, bug fixes, and product improvements. 

Using release notes has many benefits. They help manage user expectations, reduce confusion, and provide a record of modifications. 

Release notes support internal teams by documenting progress and facilitating communication across departments. They enhance user satisfaction and trust while streamlining internal processes and development cycles.

3. Company documents

Image: nimbusweb

Company documents like employee handbooks and orientation manuals demand precise technical writing skills and deep organizational understanding. 

Enterprises utilize company notes to document key decisions, strategies, and communications, ensuring consistent information flow and team alignment. One example is an employee handbook outlining company policies, benefits, and code of conduct.

These notes track progress, record meeting outcomes, and serve as references. The benefits are enhanced transparency, onboarding, compliance, and accountability.

4. Technical reports

Image: datadrivenu

Technical reports offer comprehensive insights into specific technical subjects. They present detailed findings, analyses, and recommendations. 

Enterprises often use technical reports to document research, development, and analyses. These reports share detailed information, aid decision-making, guide project development, and facilitate collaboration. One example is a technical report on the feasibility study for a new product prototype.

They also record innovations and problem-solving efforts, supporting future reference and continuous improvement, enhancing knowledge management, transparency, and operational efficiency.

5. Standard Operating Procedures (SOPs)

Image: helpjuice

Standard operating procedures (SOPs) are holistic processes. They help employees work together and accomplish various organizational tasks. 

SOPs are process documentation that ensures smoother internal operations and workflows. An example is the SOP for inventory management in warehouse operations. Other examples include SOPs for payroll processing and manufacturing guidelines.

SOPs make business processes more efficient and economical.

6. Technical specifications

Image: smartsheet

Technical specifications define the precise requirements and capabilities of products or systems. 

Enterprises leverage technical specifications to outline detailed requirements and standards for products or systems. A common example is the technical specifications for designing and constructing a new office building.

These specifications ensure consistent quality, guide development processes, facilitate team communication, and support compliance with industry standards. These benefits enhance efficiency and product reliability.

7. Knowledge-base articles

Image: invgate

Knowledge base articles provide solutions to common issues and best practices. Enterprises empower users and support teams to troubleshoot independently. 

Enterprises utilize knowledge-based articles to provide detailed information and solutions for common issues. A frequent and useful example is a knowledge-based article on troubleshooting common software installation issues for employees.

These articles support customer self-service, reduce support requests, and enhance user satisfaction. They also streamline employee training and ensure consistent, accessible information across the organization.

8. User manuals 

Image: document360 

User guides are instructional manuals designed for inexperienced end-users. They assist users with products ranging from consumer electronics and appliances to B2B SaaS tools and solutions. 

These guides are user-friendly and contain several illustrations. The illustrations and text emphasize common issues and features. One example you might have encountered before is a user manual for operating and maintaining industrial machinery on the production floor.

Technical writers must collaborate with engineers, programmers, and product designers to ensure comprehensive product coverage.

9. Software documentation

Image: Altexsoft

Computer software needs accompanying documentation. Installation guides, for example, help users navigate the implementation and installation process.

A well-crafted installation guide should include detailed workflows, video tutorials, FAQs, and a troubleshooting section. 

Programmers often automate the process, while the technical writer creates alert boxes and the ReadMe file. An example of this type of technical writing is enterprise software documentation detailing installation, configuration, and usage procedures for customer relationship management (CRM) software.

Software documentation tools make creating, publishing, and maintaining these installation guides easy.

10. Training materials

Image: Venngage

Training materials deliver structured content. This content educates employees on processes, software applications, or essential skills and can speed up the process of digital adoption of new technologies.

Another function of training materials is to standardize training practices across departments. Doing so ensures a skilled and knowledgeable workforce. A useful example is training materials for new employees covering customer service skills and company policies.

These materials are crucial in enterprise environments. They facilitate the effective onboarding of new hires and promote continuous professional development. 

11. Troubleshooting guides

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Troubleshooting guides outline systematic steps for efficiently diagnosing and resolving technical issues as part of customer continuity.

Enterprises leverage troubleshooting guides to help users independently diagnose and resolve issues with products or systems. These guides provide step-by-step instructions and solutions to common problems, improving customer support efficiency.

One common example is a troubleshooting guide for diagnosing network connectivity issues in office environments.

These guides minimize service disruptions and optimize support processes. 

12. Whitepapers and case studies

Image: Datanalytics

Case studies and whitepapers are industry-specific documents. These documents showcase real-world examples. 

Case studies appear in a passive voice and focus on specific instances. They provide vital takeaways and frequently use data to emphasize benefits. An example is a case study highlighting the implementation of a cloud-based ERP system in a multinational corporation.

Conversely, whitepapers tackle particular challenges and utilize the active voice. Technical writers who create these documents should have comprehensive industry knowledge to write effectively. One example is a whitepaper on the future of sustainable packaging in the consumer goods industry.

Case studies and whitepapers demonstrate an organization’s expertise and value and are helpful for lead generation.

13. Business plans

Image: visme

Business plans communicate a company’s strategic goals, operational strategies, and financial forecasts. In enterprise settings, they serve as foundational documents. 

A useful example is a business plan outlining expansion into new markets for a technology startup company.

These plans guide decision-making, attract investors, and align teams to achieve long-term objectives. They also promote sustainable business growth and competitive advantage.

14. API documentation

Image: stoplight

API documentation enables developers to see and change a software product’s code. It facilitates API implementation. 

It provides comprehensive instructions and tutorials. These instructions and tutorials simplify integration with other APIs, including web, software, and SCPIs. This documentation often includes code samples, usage scenarios, and detailed explanations.

A great example of API documentation details endpoints, authentication methods, and data formats for integrating payment processing services into e-commerce platforms.

API documentation benefits enterprises by guiding developers in integrating services, ensuring compatibility, accelerating development, and enhancing product interoperability and functionality.

15. Annual reports

Image: zapier

Annual reports summarize a company’s financial performance. They also record achievements and strategic objectives over a fiscal year. 

Large organizations use annual reports to communicate financial performance, strategic achievements, and plans to stakeholders and investors. 

An ideal example is an annual report summarizing a global telecommunications company’s financial performance, strategic initiatives, and market outlook.

These reports are pivotal for enhancing stakeholder transparency and maintaining investor confidence. They demonstrate accountability through precise, detailed assessments of organizational accomplishments and future directions. 

16. Service-level agreements (SLAs)

Image: fluentsupport

An SLA is a legally binding agreement between a provider and a customer. It details the services offered and defines the guarantees, warranties, and other mutually negotiated terms. 

An example of a service level agreement is defining response times and resolution benchmarks for IT support services.

This contract ensures both parties understand expectations, responsibilities, and performance standards. It promotes transparency and accountability and a reliable and productive business relationship.

17. Request for proposal (RFP)

Image: responsive 

An RFP (Request for Proposal) is a business document. It announces a project and invites bids from multiple qualified contractors. 

The RFP writing style is persuasive, and its quality can determine the deal’s success. A well-crafted RFP should clearly outline the project goals and explain challenges, the scope of the work, and evaluation criteria.

An example of a request for proposal could involve soliciting bids from qualified vendors for a new software development project.

Review the above technical writing examples and consider which is best for your organization to promote user-centricity and capability. 

Use technical writing to drive user capability

Technical writing drives enterprise user capability. It provides clear, precise documentation. This documentation helps employees and customers understand and use complex systems and tools. 

For example, a user guide increases customer capability for a new product. It ensures they optimize its use and have a positive experience. This guide makes them more likely to buy more products from the same company as they understand the value of the products. 

Technical writing enhances productivity, reduces errors, and streamlines workflows when employees can use new software quickly using training guides.

This user-centricity leads to improved efficiency and better decision-making. It also provides a competitive edge in the market.

The post 17 Great technical writing examples appeared first on Digital Adoption.

It relies on core technologies such as machine learning (ML), deep learning (DL), NLP, and NLU. These technologies create intelligent systems and algorithms that can learn from experience. 

Recent advances in AI have sparked widespread interest across business and broader society. The limits of AI  show no bounds, with skyrocketing investments continuing industry-wide. According to Statista, the AI market is projected to grow from $200 billion in 2023 to over $1.8 trillion by 2030.

This article explores real-world examples of AI in action. We’ll focus on various ways AI is being used, from small-scale activities to widespread adoption. Then, we’ll look at ten of the most important AI examples in the real world. 

10 Real-world examples of artificial intelligence

Artificial intelligence has been around for a while. It’s already garnered mainstream media attention and is evolving at breakneck speed. But are we taking advantage of its full potential? 

Understanding AI’s real-world applications and how it’s transforming industries is essential to maximizing the technology’s potential. 

To understand AI’s capabilities in the modern world, we’ve broken down the top ten real-world examples of AI by industry. 

Let’s explore the top ten examples of AI by industry:

AI in eCommerce

eCommerce is a prime example of AI’s transformative power. From personalized product recommendations to intelligent search, AI streamlines the shopping experience. 

It analyzes customer data to predict buying patterns, helping businesses tailor offers and boost sales. AI-powered chatbots provide 24/7 customer support, improving satisfaction. 

Even inventory management is optimized with AI, predicting demand and preventing stockouts. AI’s continuous learning and adaptability mean it’s constantly improving. It makes eCommerce smarter, faster, and more customer-centric. 

Real-world example

Stitch Fix, an online clothing retailer, heavily relies on AI. Their algorithms analyze a customer’s style quiz, feedback, and purchase history to recommend personalized clothing selections. This data-driven approach elevates the shopping experience and increases customer satisfaction.

AI in education

AI is making inroads into the education sector by offering adaptability and individualization. AI-powered platforms can analyze student data to pinpoint strengths and weaknesses. 

This ensures learning resources and practice questions are aligned with their needs. It also helps students learn independently, leading to better engagement and outcomes.

Real-world example

Knewton Alta is an adaptive learning platform used in higher education. It uses AI to customize course materials and assessments based on each student’s performance. This ensures a more personalized and effective learning journey.

AI in lifestyle

AI integrates into our daily lives, offering unparalleled convenience, personalization, and insights. From smart home devices to personalized content recommendations, AI subtly enhances our lifestyle experiences. 

AI-powered voice assistants like Alexa allow us to control various home devices with simple voice commands. These assistants can learn our habits to automate tasks and personalize experiences. 

Streaming platforms like Netflix and Spotify leverage AI to analyze our preferences. They suggest movies, shows, and music that align with our tastes. 

Real-world example

Smart thermostats like Nest use AI to learn your temperature preferences over time. This allows them to create energy-efficient schedules, lowering your bills and reducing your carbon footprint.

AI in navigation

AI is revolutionizing navigation, making travel safer, more efficient, and more accessible. GPS systems use AI to analyze real-time traffic data, predict congestion, and suggest the fastest routes. 

Self-driving cars rely on AI-powered systems for object detection, path planning, and decision-making. AI is also improving navigation for those with disabilities. It does this by integrating voice commands and personalized routing options.

Real-world example

Google Maps is a prime example of AI in navigation. It uses machine learning to analyze massive amounts of traffic data. This provides users with accurate travel times, alternative routes, and even warnings about potential slowdowns.

AI in robotics

AI is pushing the boundaries of what robots can do. It transforms them from machines that perform repetitive tasks to intelligent collaborators. AI enables robots to perceive their environment through advanced sensors and computer vision. This allows them to adapt to changes and make decisions in real time. 

Machine learning helps robots improve their performance over time and optimize movements. AI also drives advancements in natural language processing, enabling more seamless interactions.

Real-world example

Amazon’s warehouses use thousands of AI-powered robots called “Kiva bots.” These robots use computer vision and machine learning algorithms to navigate the warehouse, retrieve storage pods, and deliver them to human workers for picking and packing. This system has significantly increased efficiency and accuracy in Amazon’s order fulfillment process.

AI in healthcare

AI is poised to revolutionize the healthcare industry, improving diagnosis, treatment, and patient outcomes. 

AI-powered systems can analyze vast amounts of medical data, including images like X-rays and MRIs, to detect patterns the human eye might miss. This aids in the early diagnosis of diseases like cancer. AI can also develop personalized treatment plans based on a patient’s medical history, genetics, and other factors. 

AI-powered virtual assistants and chatbots can even provide patients with initial triage and support, freeing up medical professionals for more complex cases.

Real-world example

IBM Watson for Oncology is an AI-powered system that assists oncologists in making more informed treatment decisions. It analyzes patient data, medical literature, and clinical guidelines to provide evidence-based recommendations tailored to each case.

AI in gaming

AI is vital in modern game development, leading to more immersive and dynamic gaming experiences. 

AI drives the behavior of non-player characters (NPCs), making them more lifelike and unpredictable. They can learn and adapt to player actions, creating a sense of challenge and realism. 

AI algorithms can also generate game worlds, levels, and content, ensuring no two playthroughs are identical. They analyze player data to personalize difficulty settings and tailor gameplay experiences.

Real-world example

The game “The Last of Us Part II” features incredibly realistic and adaptive enemy AI. Opponents actively strategize, communicate with each other, flank the player, and react dynamically to environmental changes. This results in incredibly tense and challenging encounters that feel far less scripted than in many similar games.

AI in social media

AI is deeply embedded in the social media landscape, shaping how we interact with content and each other. It plays a significant role in what you see on your feeds. Algorithms analyze your interests, behaviors, and connections to personalize content recommendations. 

AI also helps moderate online communities and flag harmful content that violates platform guidelines. AI-powered chatbots can now provide customer service, answer FAQs, and engage directly with users.

Real-world example

TikTok’s Creative Assistant showcases how AI augments social media creation. It analyzes trends, popular formats, and successful content on the platform. This lets the Creative Assistant help users with idea generation, script writing, and tailoring their content for the TikTok audience. This AI-powered tool simplifies the creative process and allows users to produce videos with a better chance of going viral.

AI in finance

AI is revolutionizing the financial industry, enhancing decision-making, improving efficiency, and combating fraud. AI algorithms can analyze vast datasets of financial information to uncover patterns and insights that humans might miss. 

AI-powered systems are used to develop credit scoring models that assess risk more accurately. This opens lending opportunities for underserved individuals. AI also drives the creation of high-frequency trading algorithms that execute trades at lightning speed based on real-time market conditions.

Real-world example

Companies like ZestFinance use AI to create alternative credit scoring models. These models analyze non-traditional data points, expanding financial access to those with thin credit histories or past financial difficulties.

AI in automobiles

AI is fast changing how we interact with and experience our cars. Self-driving vehicles heavily rely on AI systems to perceive the environment. They do this through cameras, sensors, and lidar. 

These systems use computer vision and machine learning to identify objects, navigate roads, and make real-time driving decisions. AI also enhances assistance features like adaptive cruise control and automatic emergency braking. This makes our roads safer. In-car AI assistants offer voice commands for navigation, music control, and climate settings. This provides a more seamless and intuitive driving experience.

Real-world example

Tesla’s Autopilot is one of the most advanced AI-powered driver systems. It uses a combination of cameras, radar, and ultrasonic sensors, along with powerful neural networks. It can enable features like automatic lane changes, traffic-aware cruise control, and even self-parking capabilities.

AI: The bigger picture 

AI’s reach extends far and wide. It’s no longer confined to tech giants–it’s knocking on the door of every sector.  

Healthcare professionals are harnessing AI for disease detection. Insurers are using AI to streamline claims processing, predict risk, and even personalize coverage for each individual. In the world of finance, it’s powering lightning-fast trading and robust fraud detection. This is just a taste of how AI is already in play.

Understanding these real-world examples is the secret weapon for navigating the AI revolution. Seeing AI in various industries sparks essential questions: How could this transform my business? Where might I be vulnerable? Is my team prepared for digital transformation?

Studying AI’s successes and failures in other fields gives you the insight needed to plot your unique AI journey. This isn’t guesswork; it’s a calculated strategy to prepare your business to survive the AI wave and ride it confidently to the top.

The post 10 AI examples transforming industries appeared first on Digital Adoption.

Businesses today need to offer unique experiences across various channels. This helps engage audiences on their preferred platforms. They also must outpace their competitors.

Traditional methods no longer suffice for engaging customers, employees, and partners. These groups now expect immediacy and convenience. 

Cloud adoption improves the customer and employee experience. It allows organizations to adapt to rapid changes. This keeps them competitive and agile.

In this article, we will focus on what cloud adoption is and how it works. Next, we will examine who it is for and the various types. 

Then, we will look at how you can implement cloud adoption. Following this, we will go into when to use it and which sectors currently use it. Lastly, we will consider its benefits and challenges.

What Is Cloud Adoption?

Cloud adoption involves integrating cloud computing into business practices. Cloud computing stores, manages, and processes critical data using remote servers.

This transition can mean moving from traditional on-site infrastructure to cloud-based services. It can also involve using cloud solutions alongside existing in-house systems.

Adopting the cloud signifies the start of a digitally mature enterprise. It’s more than changing technology. It highlights a fundamental shift in how businesses operate.

This means that it affects organizational procedures and the workforce. In the first instance, it aims to enhance the scalability of data management systems. This change will also reduce costs and cut risks.

How Does Cloud Adoption Work?

The process of cloud adoption takes place in the following steps:

Assessment: CIOs and IT leaders must assess the pros and cons of cloud adoption in their industry. They should explore well-known vendors within their field. Additionally, they must gather information about the experiences of early adopters. The focus needs to be on challenges and successes.

This stage will also involve evaluating current infrastructure and application interdependencies. This exercise can pinpoint potential risks and obstacles associated with migration.

Planning: Companies must engage in comprehensive research before crafting their cloud strategy. This step involves examining recognized cloud platforms and services. You also need to decide on the type of cloud adoption. This could be public, private, hybrid, or multi-cloud.

Proof of Concept: This crucial stage involves creating a cloud adoption strategy. You can call this strategy a proof of concept (POC). You must introduce the POC to your team members and ensure their ongoing support.

Data Migration: Explore and choose from the available storage options. You also need to focus on security within your budget constraints. Once you’ve confirmed the integrity of your data, proceed with migrating it to the cloud.

Application Migration: Select the migration approach that best fits your organizational needs. Options may include lift-and-shift migration, re-platforming, repackaging, and retaining. This step is a vital component of your cloud adoption plan.

Adoption: Use these tools to automate the scaling of features and functions. Cloud services offer significant scalability and elasticity benefits.

Optimization: After the initial adoption phase, continuous improvement is essential. This process helps companies to maximize the return on their cloud investment.

Who Is Cloud Adoption For? 

Cloud adoption is for any organization that wants to use cloud computing as a disruptor. It can also be a means to enhance its capabilities. It can also help organizations launch innovative products and services. 

Transitioning to the cloud moves beyond focusing on cost reduction. Instead, it focuses on accelerating innovation to secure a competitive advantage.

Cloud adoption and migrating data are the starting points. This initial step facilitates the development of a cohesive data platform.

A modern data platform is crucial for exploring advancements in AI and ML, such as generative AI. Here, the cloud functions as the facilitator. Data acts as the catalyst. AI becomes the defining distinction.

Companies that need to adapt to the ever-changing world will also benefit. Cloud technology can drive digital transformation by providing tools for rapid digitization. It allows businesses to create impactful automation strategies.

This large-scale automation helps employees with complex tasks. It also improves efficiency and saves time. This then increases returns on investment. With cloud adoption, organizations avoid the cost and hassle of physical IT infrastructure. They can use services like virtual servers, storage, and databases on demand.

Types Of Cloud Adoption

Before moving to the cloud, you need to be aware of the various types of cloud adoption models:

Public Cloud

The public cloud offers cloud services over a network for public use. Customers can’t control the infrastructure’s location.

Users share the cost model. It can be either free or based on a pay-per-use policy. This cloud type is ideal for organizations managing host and user applications.

Multi-Cloud

The multi-cloud approach uses services from various cloud providers. It allows organizations to select services that best meet their needs. This avoids reliance on a single vendor. Multicloud offers diversity in features and capabilities.

But, it introduces complexity in management and increases costs. There can be compatibility and interoperability challenges due to providers using different technologies.

Hybrid Cloud

Hybrid clouds merge public and private cloud features into a heterogeneous cloud. They overcome the scalability limits of private clouds by using public cloud resources. Benefits include cost efficiency, quick data transfer, and improved security.

Yet, hybrid environments can be complex to create and manage. They pose challenges in security management and need specific expertise.

Private Cloud

A private cloud serves one organization, providing control over security and data. This cloud type suits organizations with high security and management needs.

Community Cloud

Community clouds target specific industries or communities. They integrate services from different clouds to meet shared goals. These clouds are cost-effective through shared infrastructure.

Despite their adaptability and scalability, managing shared responsibilities can be difficult. They offer a security level that is between public and private clouds. Community clouds support sectors like media, healthcare, energy, and scientific research.

How To Implement Cloud Adoption

Embracing cloud adoption is not a decision to rush into. Understanding the technology is essential. You also need to know your current setup and future opportunities.

Below are steps to help your organization reap the benefits of embarking on a cloud journey:

Understand the Need for Cloud

Before moving to cloud implementation, consider its impact on your organization. Identify your motivations and goals. These factors will guide your planning and strategy. Understand the differences between on-premise and cloud servers. Know the cloud provider’s revenue model to optimize costs.

Conduct An IT Infrastructure Assessment

Assess your current digital infrastructure. This step helps develop a successful strategy for cloud adoption. Identifying potential obstacles and opportunities is crucial for efficient deployment.

Align Departmental Perspectives

Different departments have unique concerns and risks. Aligning these with business objectives is vital. Your cloud strategy should result from collaborative efforts. It should provide a unified vision of the cloud’s role.

Choose a Cloud Service Model

Analyze your infrastructure and business figures to select a suitable cloud service model. Consider the provider’s strategy to ensure alignment with your long-term goals. Choose IaaS, PaaS, or SaaS based on your company’s needs.

Ensuring Effective Communication

Maintain effective communication across the organization. Discuss the benefits and costs of cloud adoption. Broaden cloud evangelism as more stakeholders see its benefits.

Develop Cloud Expertise

Hire or train cloud experts to ensure successful cloud adoption. Integrate them into development teams and emphasize cloud development through regular training and coaching solutions.

Establish Governance and Continuous Optimization

• Put in place a governance model for using cloud services. 
• Track performance and costs. 
• Use automation to maintain agility as cloud usage expands.

When To Use Cloud Adoption

Various motivations can push businesses toward transformation via cloud adoption. Critical business events might trigger this shift. 

These can include responding to regulatory compliance changes. It can also involve undergoing mergers, acquisitions, or divestitures. There might also be a need to manage the environmental impact of the business.

Businesses might also adopt the cloud to scale and meet geographic demands. They may also seek to optimize internal operations or boost business agility. For instance, cloud adoption could occur to protect against cyberattacks.

Finally, the desire to improve customer experiences can lead to cloud adoption. For instance, your organization might want to improve email communications through software. Developing new technical capabilities is another strong motivator.

Which Sectors Does Cloud Adoption Benefit?

Here are some examples of industries that cloud adoption can benefit:

Energy and Utilities

Cloud adoption is pivotal in transforming the energy and utilities sector. It supports smart grid technologies, improving grid performance and energy distribution. It also helps adapt to demand changes.

Cloud analytics and IoT devices enable predictive maintenance. This approach allows early equipment issue detection, preventive maintenance, and cost savings. It also improves operational reliability.

Agriculture

In agriculture, IoT and big data are driving innovation. They help us understand the environment and crop production better. Cloud technology provides detailed insights from soil, machinery, and livestock sensors. This optimizes agricultural practices and enhances decision-making.

Education

Education faces ongoing funding challenges. Cloud adoption offers a solution. It centralizes resources for students and streamlines assignment distribution for teachers. This improves collaboration and accessibility.

Healthcare

Cloud solutions have revolutionized healthcare. They secure patient data storage and ensure HIPAA compliance. Telemedicine, enabled by cloud technology, offers remote healthcare services. This improves access in remote areas and enhances patient care.

Retail

Retailers use cloud technology to analyze customer preference data. This enables personalized offerings and boosts sales. Cloud also simplifies vendor management by automating invoicing and payments. This makes operations more efficient.

Manufacturing

Cloud adoption provides a cost-effective alternative for manufacturing infrastructure. It supports product development, marketing, and smart manufacturing. Cloud tools aid in marketing, product planning, and supply chain integration. Cloud-based ERPs track production, stock, and sales.

Finance and Banking

In finance and banking, cloud adoption improves security and compliance. It includes measures like encryption and access controls. This protects financial data and aids regulatory compliance. 

Cloud solutions enable real-time transaction processing, improving the efficiency of financial operations. Cloud-based machine learning models detect and prevent fraud, securing the economic ecosystem.

Benefits Of Cloud Adoption

Cloud adoption offers organizations the opportunity to achieve their business objectives.

Here are some key advantages of embracing cloud technology:

Drives Decisions Based On Data

Businesses generate massive amounts of data daily. This data, known as big data, includes both structured and unstructured types. Extracting valuable insights from big data requires efficient and cost-effective processing methods.

Traditional storage systems may not keep up with the volume of data. Investing in infrastructure becomes necessary for supporting big data processing.

On-premises data warehouses often cannot support the rapid processing needed for advanced analytics. Migrating to the cloud allows organizations to better analyze data. This move enables data-driven decision-making.

Adopting cloud business intelligence is essential for staying competitive. It eliminates the need for physical infrastructure and enhances data accessibility.

Allows Business Expansion

Whether through mergers or diversification into new markets, cloud adoption streamlines these processes.

A strategic shift towards cloud computing can transform business operations. This leads to increased efficiency and facilitates new avenues for growth.

Enhances Customer Experience

In the digital age, customer satisfaction is paramount. Cloud technology offers businesses a significant advantage by enabling superior customer service.

Companies that use cloud-based customer support systems often resolve issues more quickly. This is because of the high availability and reliability of cloud services. Moreover, these systems allow for instant communication with customers. This enhances their experience and, by extension, their loyalty to the brand.

Offers Data Security and Scalability

Data loss, whether from natural disasters or technical failures, is a concern. Cloud adoption provides a secure, resilient environment for data storage and backup. This ensures business continuity even in the face of such challenges.

One of the most appealing aspects of cloud services is their scalability. As businesses grow, their IT needs change. You can adjust your cloud services requirements to fit evolving requirements. This removes the need for much upfront investment in physical infrastructure.

Supports Flexibility and Remote Work

The global shift towards remote work has highlighted the importance of flexibility. Cloud services enable employees to access critical systems and data from anywhere. This fosters a dynamic, agile organization.

Enables Cost Efficiency

Cloud adoption services operate on a pay-as-you-go pricing model. This means that businesses pay only for the resources they use.

This approach offers a more predictable, manageable cost structure. This is more cost-effective than on-premises IT infrastructure.

Furthermore, the provider can update and maintain cloud services. This reduces the burden of costly upgrades and maintenance on the business.

Improves Implementation Cycles

Organizations with on-premise software often face long lead times. It takes months to decide to install a product and then to determine its actual usage.

Cloud solutions offer a solution with quicker implementation cycles. Products go live in weeks, not months.

Moreover, cloud technology boosts team collaboration. It lets teams access, edit, and share documents and data anytime. This increases productivity and efficiency. Cloud-based apps provide real-time updates on workflows and file sharing.

Compels Better Security and Disaster Recovery

Cloud adoption enhances an organization’s ability to protect its data. It also helps a company recover from disasters. Personal devices and on-premises servers are vulnerable to security breaches and physical damage.

This is because they use robust encryption and many layers of backup to safeguard data. This minimizes downtime and the impact on business operations.

Provides Environmental Benefits

Adopting cloud technology benefits the environmental side of a business. By using the cloud, you can reduce waste and energy consumption. This contributes to a smaller carbon footprint.

Furthermore, cloud platforms ease seamless collaboration across departments and geographies. This breaks down data silos and drives efficiencies within the workplace.

Challenges of Cloud Adoption

Here are common challenges businesses might encounter during their transition to the cloud:

Security Concerns

A PwC survey reveals that 66% of IT professionals consider security a significant challenge in cloud adoption. But, cloud service providers can offer good security measures. 

They use strong encryption, conduct regular audits, and have compliance certifications. This has enhanced data protection in the cloud.

So, overcoming this challenge involves a shift in organizational culture. Think about how your organization can become comfortable with cloud technologies. Start small, migrating a few workloads to the cloud and evaluating the results.

Understand your cloud provider’s security breach contingency plans. Appreciate how they can enhance security on your end.

Enhancing cybersecurity includes ensuring robust data encryption. It also involves adding extra authentication measures. You also need to foster clear communication among various teams.

The Organizational Impact of Cloud Migration

Cloud migration affects more than just the IT team. It may also have implications for legal, finance, and HR departments. All teams need to collaborate. This ensures all employees understand the cloud adoption model and workflows.

Security training and ongoing cloud education are vital to cut operational challenges. Introducing a new cloud system necessitates personnel training and an effective troubleshooting system.

Initial resistance from employees unfamiliar with cloud technology is common. However, clear communication of the benefits of the cloud can help enterprise digital adoption. Continuous learning can also act as employee training and fill any skill gaps.

Loss of Control

Adopting cloud solutions means less control over software, systems, and computing assets.

Reliability issues arise from internet dependency, which can disrupt business operations. Downtime and cloud service outages may lead to major productivity and revenue losses.

This poses challenges in assessing security system efficiency. It also makes implementing incident responses and monitoring data more difficult.

To address this, check each cloud provider’s visibility level. Also, look at their measures to prevent data breaches. 

Next, look at what measures they have in place to cut the effect of downtime. Utilizing monitoring tools or setting up APIs can provide insights into your data. They can assist in reducing the risks associated with reduced oversight.

Next Steps For Cloud Adoption

Not moving to the cloud can make you fall behind competitors and lose your competitive edge. A strong cloud adoption strategy is crucial for growth and future-proofing your business.

Buying a cloud subscription isn’t enough. Your teams need to use the cloud in their daily tasks to see a real return on investment. Cloud adoption success depends on your teams’ willingness to adopt and use new tools.

For long-term success, you need an effective cloud adoption plan. Cloud adoption projects are complex, and developing the necessary skills can take time. Assessing your current infrastructure, business needs, and goals is important.

This assessment helps you create a strategic plan and make informed decisions. Sharing knowledge across the company builds a community that supports your strategic goals.

Achieving success with cloud technology requires continuous planning, monitoring, and optimization. Following cloud adoption best practices reduces risk and avoids common pitfalls.

The post Cloud Adoption: What Is It And Why Is It Important? appeared first on Digital Adoption.

These platforms are compared across various parameters including advanced automation, customer experience, enterprise readiness, customer support, pricing structure, and unique advantages. As the field continues to evolve, and these platforms roll out new features and enhancements, it is important to note that this page will be updated regularly to reflect the most current information.

Both Whatfix and Pendo are well received by users and industry analysts. But not all DAP solutions were created equal. So, how can you know which is right for you? The first step would be to outline your objectives and priorities beyond the need to streamline onboarding and training with walkthroughs. 

This may include accessing user behavior insights, automating tasks, applying cross-app analytics, and optimizing software licensing, among others.

Once you’ve got your list in hand, a side-by-side comparison of features, capabilities, and user feedback will go a long way towards helping you gain clarity about which solution is best suited for your organization’s digital adoption needs.

Whatfix and Pendo at a glance

Whatfix is well known for offering an affordable platform that performs well on delivering core DAP functionalities. The platform is focused on streamlining enterprise software onboarding and providing real-time task guidance for reducing the number of inquiries that the help desk receives.

The Whatfix solution is best suited for organizations that have prioritized quick wins over customization depth and self-serve independence.

Pendo is primarily a product experience platform that also offers certain capabilities for supporting digital adoption. These include guided workflows, an in-app resource center, and in-app feedback. 

The company offers two products. One addresses the customer use case, while the other supports the employee use case, both through the prism of product experience.

Whatfix comes in with solid reviews, earning positive feedback regarding the platform’s overall capabilities and customer service. The offering is noted for its core functionalities for enterprise software onboarding and real-time task guidance. 

Though it’s important to note that reviewers would like to see more customization options and to avoid the need for technical support when making certain configurations and content updates.

As for Pendo, the platform is appreciated by users in organizations with simple workflows and more modest DAP requirements. 

For those who are more focused on product experience, the guided workflows, in-app resource center, and in-app feedback are well regarded. 

Though, users also comment that design options for personalization and customizations are restricted and some implementation processes require IT assistance.

Data centricity

When comparing Whatfix and Pendo’s data and analytics capabilities, several key differences emerge.

Whatfix provides usage analytics that offer visibility into user interactions, helping identify the most and least used content. However, the analytics are sometimes viewed as unclear and lacking in providing comprehensive insights. 

The platform is considered suitable for less complex deployments but lacks the depth of insight and predictive capabilities necessary for adjusting in-app guidance content and flows. This limitation, however, doesn’t diminish the usefulness of the platform for businesses seeking basic user behavior analysis.

Beyond simple activity reports, addressing more complex needs with Whatfix requires an IT-level understanding of how data is tracked and monitored. Moreover, while the organization can get reports on user interactions, discovering applications and related interactions is coding intensive.

Pendo, on the other hand, is noted for its robust data and analytics capabilities. The platform provides detailed user analytics, including heatmaps, user path analysis, and funnel tracking. These features offer a deeper understanding of user behavior and engagement, allowing businesses to optimize their product and marketing strategies effectively. 

Pendo’s analytics are considered more comprehensive and insightful than those of Whatfix, making it a more suitable choice for businesses needing advanced, sophisticated user analytics. In the Pendo platform elements need to be tagged, session playbacks are not possible, and custom reporting has been noted to be cumbersome.

However, it’s important to note that both platforms come with their own sets of pros and cons. The choice between them ultimately depends on the specific data and analytics needs of the business.

Whatfix vs Pendo: Content building capabilities

Content creation and building capabilities form the core of any digital adoption platform, determining how effectively and easily in-app guidance content can be generated and tailored to meet user needs. 

Whatfix excels in providing a simple and streamlined content creation process. The platform offers intuitive, no-code tools for creating interactive walkthroughs and guides, thereby lowering the barrier to content creation for non-technical users. The platform also allows for customization of features like welcome messages, pop-up triggers, and flow segmenting, enhancing user engagement and experience. However, some users have expressed the desire for more flexibility in customizing conditions, triggers, and logic that control behaviors.

Pendo, in contrast, is well-regarded for its dynamic content creation capabilities. It offers a comprehensive set of tools for creating customized in-app messages, tooltips, and guides. Pendo’s content building capabilities are more advanced than Whatfix’s, featuring a broad array of customization options and a more detailed interface. This can, however, result in a steeper learning curve for new users.

And with Pendo, since the company has been traditionally focused on customer experience rather than in-app guidance, the Pendo Editor does not have the features required for addressing complex flows and processes. 

While Whatfix provides an easy to use, no-code content creation process, Pendo offers more sophisticated and flexible content creation capabilities. The choice between the two will depend largely on the complexity of the content needs of the business and the level of customization required.

Whatfix vs. Pendo: Automation and workflow support

Automation and workflow support are vital features in a digital adoption platform, ensuring streamlined processes and efficient task execution. 

Whatfix provides decent automation support, offering features such as auto-generating walkthroughs, which reduces the manual effort in content creation. It also includes automation in its analytics, for instance, generating automated reports that help businesses track user behavior without manual intervention. 

Additionally, Whatfix supports task list creation that guides users through a series of tasks, improving workflow and user productivity. However, there has been some user feedback regarding the desire for more advanced automation features, such as conditional automation based on user behavior or response. Whatfix offers a simple and streamlined approach to automation and workflow support, ideal for businesses with less complex needs. 

Pendo, alternatively, stands out in providing robust automation and workflow support. It offers features like auto-guide dispatch, which automatically displays guides to users based on pre-defined conditions, and automated customer segmentation, which categorizes users based on their behavior. This results in personalized user experiences and more targeted guidance. 

Furthermore, Pendo supports the creation of sophisticated user paths, which guide users through complex tasks and workflows, thereby enhancing productivity. However, the depth of Pendo’s automation capabilities could lead to a steeper learning curve for new users.

Whatfix vs. Pendo: Customer support

Customer support and success are key components of any tech solution, and both Whatfix and Pendo have demonstrated commitment in this area, albeit with distinct strategies.

Whatfix is often commended for its customer-focused approach, with users mentioning the responsive and knowledgeable customer support team. They’ve shown dedication in providing continuous product improvements based on customer feedback, which has earned them the reputation of a customer-centric company.

However, there have been instances of technical errors and bugs disrupting usage, causing some customers to feel a need for more robust technical support and faster problem resolution.

On the other hand, Pendo does not fall short in customer support and success either. They have a help center and offer an extensive range of resources such as guides, webinars, and tutorials. Pendo’s support team is also highly responsive and generally resolves customer issues effectively. Some users, however, have found Pendo’s onboarding process to be complex and felt a need for more hands-on assistance during the initial setup phase.

In a nutshell, while Whatfix has a customer-focused approach with quick response times, Pendo provides comprehensive resources and robust support. Both platforms have room for improvements: Whatfix in addressing technical issues and Pendo in assisting users throughout the onboarding process.

Whatfix vs. Pendo: Business value and ROI

When assessing the value and ROI of Whatfix and Pendo, both platforms showcase a notable capacity to drive user engagement, improve productivity, and enhance customer satisfaction. 

Whatfix excels in its commitment to improving user experience with its intuitive user interface, simplified content creation, and effective analytics-driven insights. Customers report a significant reduction in training and support costs, faster onboarding, and increased user engagement, all leading to enhanced productivity and performance. Moreover, the tool’s impact extends to improving sales processes, boosting conversions, and fostering customer independence and self-sufficiency, thus resulting in a positive ROI. 

Pendo, on the other hand, stands out with its robust data and analytics capabilities. It provides comprehensive user analytics including heatmaps, path analysis, and funnel tracking. This deeper understanding of user behavior and engagement allows businesses to optimize their product and marketing strategies effectively. 

Additionally, Pendo’s dynamic content creation capabilities offer a wide array of customisation options, making it more suitable for businesses needing advanced and sophisticated user analytics. While this might involve a steeper learning curve for new users, the long-term benefits in terms of user engagement and customer satisfaction could lead to remarkable ROI. 

Whatfix vs. Pendo: Enterprise readiness

Whatfix offers a digital adoption platform that provides core functionalities for enterprise software onboarding and real-time task guidance, which are best suited for product managers at enterprise and mid-market organizations.

The platform’s simplicity and user-friendliness is attractive for small to mid-size enterprises or for those seeking a simplified implementation. 

Pendo is better suited for mid-market organizations and small businesses. Some design options for personalization and customizations are restricted, implementation processes may require IT assistance, and the Pendo consolidated suite of tools is primarily aimed at reducing manual effort, rather than handling complex enterprise workflows.

Whatfix vs. Pendo pricing comparison

Whatfix

Whatfix has two main pricing packages – one for DAP and one for product analytics. The DAP package is then further broken down to web, desktop, mobile, and enterprise plans. For a web deployment, there are standard, premium, and pro options. The first two options are designed for employee or customer-facing applications, with the pro option intended for customer facing applications with over one million users.

Each web package option includes features such as in-app guidance, surveys, and content aggregation, with progressively more extensive capabilities depending on the package level. For example, surveys in the standard package are out-of-the-box, but in the premium package they may be customized.

The DAP desktop, mobile, and enterprise packages have two options – standard and premium, both for employee or customer facing applications, and each with a certain features set, based on the level selected.

The enterprise package is the only one that covers an unlimited number of web-based employee-facing applications.

The product analytics pricing package also comes with a standard or premium option. The standard package is designed for a cloud-based deployment plan that is available with any web, desktop, or enterprise plan. The premium package is designed for cloud-based deployment of web-based and desktop-based employee or customer-facing applications.

Among the features available in both are user action tagging, dashboards, funnel insights, event properties, and more, where the standard package allows for 25 tag user actions and the premium option is unlimited.

Pricing for each package is comprised of a flat fee along with user license fees, which are defined as based on the type of user who will access the application.

Whatfix product and service add-ons include out-of-the-box content templates, integrations, and analytics, white-labeling, professional services, and more.

Whatfix offers a free trial to interested organizations.

Pendo pricing structure

Pendo offers custom pricing that is based on monthly active users (MAU). The company offers three packages – free, growth, and portfolio.

The free option includes product analytics, in-app guides, net promoter score (NPS), and roadmaps.

The Growth package is designed for use with a single web or mobile app, and includes product analytics, in-app guides, Net Promoter Score (NPS), roadmaps, and cross-app reports.

And the Portfolio package includes all that the Growth package offers but is meant for organizations with multiple products and can be used across unlimited web and mobile apps.

Among the features available in each are in-app guides, sentiment via NPS and surveys, and roadmaps, with the free plan available for 500 active monthly users, and growth and portfolio as a custom offering.

Features that are not available in the free package include a product engagement score, guide experiments, cross-app journey reports, and more.

The Whatfix advantage: quick wins at an affordable price

Whatfix is well positioned for organizations seeking basic capabilities that accelerate enterprise software onboarding within a modest budgetary framework.

The platform offers simplified content creation for deploying real-time task guidance and reducing training and support efforts.

Without a breadth of self-serve features, Whatfix is better suited for teams who don’t especially need to be independent and don’t mind engaging with the company’s support team for realizing certain capabilities.

The Pendo advantage: enhancing the product experience 

For some companies ensuring a smooth product experience is prioritized over securing digital proficiency. This is where Pendo has found its niche. 

It offers an in-product resource center, a feedback solicitation tool, and the ability to categorize feedback. This way, teams can gain insights on features and usage and tweak products for an enhanced user experience, as based on real-life inputs.

Which is best for you? 

Bottom line, which is best for you? As was noted in the beginning of the review, it all depends on what you need. 

If you are looking for an easy-to-use, no-code solution with decent automation support and customer success commitment, Whatfix is a great option. It offers quick wins at affordable prices and can be beneficial for small to mid-size enterprises or organizations with less complex needs. If yours is an organization whose processes are not marked by complexity and you don’t mind workarounds to issues that are specific to your workflows, then Whatfix is for you. 

With Whatfix you’ll get straightforward onboarding processes and affordability without the depth and breadth of a wider DAP offering.

On the other hand, if you need robust automation and workflow support, along with comprehensive analytics capabilities and advanced user engagement features, Pendo is worth considering. It may have a steeper learning curve and be more suitable for mid-market organizations or businesses with more sophisticated content needs.

Not every organization has prioritized full-fledged digital adoption with extensive customization and analytics. If your KPIs are driven by how employees and customers experience a product, Pendo has what you need.

Pendo is an excellent choice for a mid-market organization or small business looking for an intuitive and user-friendly approach to enhancing the product experience.

Ultimately, it is important to carefully evaluate your business’s unique requirements and goals before making a decision. Both Whatfix and Pendo offer valuable digital adoption solutions, but the best fit for your organization will depend on your specific needs and priorities. So, take the time to research and assess your options before making a decision. After all, investing in a digital adoption platform is an important decision that can greatly impact your business’s success. 

The post The Definitive Whatfix vs. Pendo Comparison appeared first on Digital Adoption.

These platforms are compared across various parameters including advanced automation, customer experience, enterprise readiness, customer support, pricing structure, and unique advantages. As the field continues to evolve, and these platforms roll out new features and enhancements, it is important to note that this page will be updated regularly to reflect the most current information.

Both WalkMe and Pendo are well received by users and industry analysts. But not all DAP solutions were created equal. So, how can you know which is right for you? The first step would be to outline your objectives and priorities beyond the need to streamline onboarding and training with walkthroughs. 

This may include accessing user behavior insights, automating tasks, applying cross-app analytics, and optimizing software licensing, among others.

Once you’ve got your list in hand, a side-by-side comparison of features, capabilities, and user feedback will go a long way towards helping you gain clarity about which solution is best suited for your organization’s digital adoption needs.

WalkMe and Pendo at a glance

WalkMe is well recognized as the pioneer of DAP, serving as the trusted partner of choice for organizations all over the world who are looking to accelerate digital adoption and improve employee and customer experience. WalkMe is long recognized as an industry leader, having received widespread acclaim for its digital adoption platform. Recent accolades include InfoWorld Technology of the Year Award 2022, Software Asset Management Solution of the Year 2023, Forbes Cloud100 World’s Best Cloud Companies, and many more. 

The platform is well noted for enabling organizations with effective and fast digital adoption. And the company is also regarded for continually introducing innovations that extend the value of DAP, such as its conversational interface that leverages NLP for chat-based interactions.

Pendo is fundamentally a product experience platform (PXP) that includes a repackaging of features for the DAP market, introduced in 2022. In effect, Pendo offers two products, one for product managers of SaaS products, Pendo Adapt, and another that is positioned for DAP, Pendo Engage.

Pendo Engage helps users understand, guide, and gather feedback from employees. It draws from Pendo’s other products, i.e., analytics, guidance, pop-ups, etc., but is packaged separately from Pendo Adapt since it has a lot of product management-focused features that are less relevant to DAP.

Ultimately, what this means is that Pendo is relatively new to the employee experience domain.

User sentiment for WalkMe across the leading software review websites is extremely favorable, achieving a nearly perfect score overall, with very high ratings in key criteria, such as ease of use, customer service, and value for money. 

Among the most noted ‘likes’ are WalkMe’s comprehensive feature set, enabling non-technical users to build solutions quickly, extensive customization for tailoring experiences for different users and use cases, streamlined workflows, and automated tasks.

As for Pendo, the platform is appreciated by users in organizations with simple workflows and more modest DAP requirements. And for those who are focused on product experience, the guided workflows, in-app resource center, and in-app feedback are well regarded. 

Though, users also comment that design options for personalization and customizations are restricted and some implementation processes require IT assistance.

WalkMe vs. Pendo: Data and analytics capabilities

When examining the data and analytics features of WalkMe and Pendo, both platforms provide valuable insights into user behavior and interactions, but they approach these functionalities in slightly different ways.

With WalkMe, you can track all data related to digital adoption within your organization, including individual user and account usage insights. Additionally, WalkMe automates the discovery of applications across your tech stack, providing a comprehensive analysis of usage.

The application discovery feature provides valuable insights into total users, usage duration, and frequency. This enables organizations to identify potential areas for cost optimization, app consolidation, and license allocation.

WalkMe’s workflow analytics offer a profound understanding of user interactions within apps, specifically in the context of specific tasks. By identifying drop-off triggers and improving process efficiency, you can streamline workflows and enhance productivity. Furthermore, with guidance analytics, you can effortlessly track user engagement with on-screen guidance and predefined elements.

WalkMe’s analytics suite collects and analyzes data on user interaction with your digital assets. It provides metrics on error rates, completion rates, and drop-off points within walkthroughs. Moreover, WalkMe allows the tracking of custom events, enabling the collection of specific data points that are unique to your business needs. However, some users note that WalkMe’s data visualization could be more intuitive and easier to understand.

In addition to these powerful features, WalkMe provides form completion analytics, allowing you to uncover insights into user bottlenecks, time wastage, or process abandonment. User interaction playback sessions enable you to capture, analyze, and replay entire user sessions, gaining a deeper understanding of user behavior. Lastly, WalkMe offers customizable reports that provide valuable insights into user experience, ensuring you have the information you need to make informed decisions.

Pendo, on the other hand, provides detailed analytics on user interactions, behavior, and product usage. It also offers tagging capabilities, enabling easy tracking of features without requiring the assistance of an engineering team. Pendo’s Path Analysis feature helps identify the most common user journeys through your product, while its Funnel Reports measure conversion and drop-off within a series of steps. Pendo users, however, have reported some limitations in terms of robustness and customization of analytics, and occasional issues with data reliability. 

In the Pendo platform elements need to be tagged, session playbacks are not possible, and custom reporting has been noted to be cumbersome in comparison with WalkMe’s custom report builder.

In addition to analytics, Pendo offers in-app guides and targeted messaging to improve user onboarding and activation. These features have received positive reviews from users as they provide a seamless way to engage with customers and increase adoption rates. However, some customers have mentioned superficial data insights and challenges in guide creation.

WalkMe vs Pendo: Content building capabilities

WalkMe and Pendo both offer notable content-building capabilities, but there are some distinct differences between the two. WalkMe excels with its ease of use and robust personalization options. Its user-friendly platform employs an intuitive drag-and-drop interface, coupled with detailed guides and tutorials, which makes it an accessible tool for non-technical users. 

WalkMe’s superior personalization capabilities allow users to tailor their walkthroughs based on user preferences, roles, and behavior, fostering a more engaging and relevant user experience. Furthermore, WalkMe’s advanced segmentation and branching capabilities enable users to create unique paths based on user responses or behavior. 

WalkMe’s extensive language support also makes it a fitting choice for global businesses in need of content creation and management across various regions and user groups. 

Pendo, on the other hand, is equally renowned for its intuitive interface and detailed analytics on user interactions, behavior, and product usage. 

Pendo’s content building features are relatively easy to use, with a straightforward interface that doesn’t require extensive coding knowledge. Notably, Pendo’s content is highly customizable, which users find valuable for creating targeted user experiences. However, some users have reported challenges in guide creation and a steeper learning curve with Pendo’s content building tools.

Traditionally, Pendo has been focused on customer experience and analytics, rather than in-app guidance. One articulation of this can be seen in the Pendo Editor, which does not have the features required for addressing complex flows and processes. 

For example, there is no code free branching and splitting for complex business processes, and no automation, nor smart tip data validation, error-handling, or an ActionBot. 

Moreover, the capturing algorithm is noted for being less robust, which means that content doesn’t always connect to elements as expected. Pendo’s language support is also commendable, though it lacks the breadth offered by WalkMe meaning multi-language needs may not be fully met.

WalkMe vs. Pendo: Automation and workflow support

When it comes to automation and workflow support, WalkMe and Pendo offer different strengths.

WalkMe shines with its robust automation capability that is designed to accelerate business processes and streamline workflows. The platform provides powerful tools like Walk-Thrus, which are step-by-step guides that automate the process of training users on new software or features. WalkMe’s automation also extends to its SmartTips feature, which provides users with instant, contextual help without any human intervention. Furthermore, WalkMe’s Automation Anywhere feature is another stand-out offering, which allows businesses to automate any repetitive task or workflow, saving valuable time and resources.

In terms of workflow support, WalkMe’s dynamic walkthroughs can create adaptive sequences based on user actions and decisions, enabling a customized user experience. Its Task List feature allows businesses to create personalized task lists for users, guiding them through complex processes and ensuring nothing is missed. WalkMe’s Process Tracker also allows organizations to monitor user progress and identify bottlenecks, providing crucial insights to improve workflow efficiency.

Additionally, WalkMe supports complex business logic with customizable user workflow templates. Users can select the workflow aligned to their organizational needs, choose relevant tasks and customize their WalkMe in-app guidance content accordingly.

On the other hand, Pendo is well-regarded for its workflow support capabilities. Pendo’s Guides are a core feature of its platform, providing on-screen, step-by-step walkthroughs for users to efficiently navigate through complex processes or new features. These guides are easily customizable, allowing businesses to tailor the user experience based on specific roles, preferences, or behaviors.

Where Pendo falls a bit short is in its automation capabilities. While the platform does offer some automation in terms of guide delivery and user segmentation, it lacks the more advanced automation features found in WalkMe, such as task automation. However, Pendo’s analytics and data-driven approach offsets this somewhat, providing valuable insights that can be used to refine and optimize workflows.

WalkMe vs. Pendo: Enterprise readiness

When it comes to enterprise readiness, both WalkMe and Pendo offer a host of features designed to meet the rigorous demands of large-scale operations.

WalkMe’s enterprise readiness is evident in its robust security framework, which includes ISO 27001 and SOC 2 Type II certifications, Fed-RAMP Ready status, GDPR compliance, and privacy by design. WalkMe’s high scalability allows it to handle large volumes of users and complex organizational structures, making it a suitable choice for large enterprises. 

Additionally, WalkMe provides comprehensive integration capabilities, offering out-of-the-box integrations with leading business tools and custom API integrations to ensure seamless interoperability across your tech stack. 

WalkMe also has an extensive partner network further underscoring its suitability for global enterprises. It collaborates with an array of technology partners, solution providers, and consulting partners to bolster its offering. These partnerships enhance WalkMe’s integration capabilities, extend its reach, and provide clients with additional resources and expertise. Regardless of your geographical location or specific business needs, this robust network ensures you can access and leverage WalkMe’s innovative technology effectively.

Pendo, on the other hand, also demonstrates strong commitment to enterprise readiness. Their platform is designed to scale with your business, supporting large user bases and complex product suites. Pendo’s security measures are robust, with compliance certifications including ISO 27001, SOC 2 Type II, GDPR, and the EU-US Privacy Shield. Like WalkMe, Pendo offers broad integration capabilities, supporting common business tools and offering API access for custom integrations. However, Pendo’s support offerings are reportedly less comprehensive than WalkMe’s, with some users noting slower response times and a lack of dedicated success managers.

In conclusion, both WalkMe and Pendo are well-equipped to handle the complex needs of large enterprises, with WalkMe possibly having a slight edge in terms of support and scalability.

WalkMe vs. Pendo: Customer support and success

Customer support is a crucial element in maintaining user satisfaction and encouraging continuous engagement with the platform. Both WalkMe and Pendo offer customer support, but their respective offerings differ slightly.

WalkMe has a comprehensive customer success program, offering dedicated success managers. This personalized approach ensures that all customer issues are addressed promptly and efficiently. Additionally, WalkMe offers 24/7 support and a comprehensive knowledge base including extensive online documentation, webinars, and technical guides. WalkMe’s robust online community also provides an excellent platform for users to share insights, challenges, and solutions, fostering a sense of collaboration and community.

Pendo, on the other hand, provides a strong support framework, but reports suggest it is less extensive than WalkMe’s. Pendo offers email and chat support as well as an online knowledge base. However, some users have reported slower response times and a lack of dedicated success managers. Despite these criticisms, many users appreciate Pendo’s support for its helpfulness and responsiveness.

WalkMe vs. Pendo: Business value and ROI

When evaluating the business value and return on investment (ROI) of WalkMe and Pendo, there are several factors to consider:

WalkMe, with its robust set of features, provides significant business value. Its advanced automation capabilities can lead to substantial time savings for businesses, effectively increasing productivity levels and reducing operational costs. The platform’s detailed analytics can also provide valuable insights into user behavior, enabling businesses to optimize their software usage and improve overall user experience. These improvements can lead to higher customer satisfaction levels, increased customer retention, and ultimately, increased revenue.

In terms of ROI, WalkMe’s users often report a swift return on their investment. The efficiency gains from using the platform can lead to significant cost savings. Furthermore, businesses can expect increased revenue from improved customer satisfaction and engagement, further enhancing the ROI.

Pendo, on the other hand, also offers significant business value. Its detailed analytics on user interactions, behavior, and product usage can provide businesses with actionable insights to improve their product offerings and user experience. Furthermore, Pendo’s in-app guides and targeted messaging can enhance user onboarding and activation, leading to higher user engagement and retention.

In terms of ROI, Pendo’s users have also reported positive returns on their investment. The cost of the platform can often be justified by the improvements in product usage and customer retention. The data-driven insights provided by Pendo can also enable businesses to make informed decisions, leading to improved operational efficiency and potentially increased revenue.

Businesses seeking more advanced automation capabilities and personalized user experiences may find more value in WalkMe, while those prioritizing detailed user analytics and product usage insights may lean towards Pendo.

WalkMe vs. Pendo pricing comparison

WalkMe pricing structure

WalkMe offers two pricing packages, WalkMe for Employees and WalkMe for Customers. Both are designed to be flexible for accommodating any organization at any stage of the DAP maturity lifecycle as well as for easily picking the package of capabilities and pricing that’s right for them.

The WalkMe for Employees package includes a subscription model for the WalkMe Core offering with optional advanced add-on modules. This approach enables alignment between required features and corresponding pricing, where organizations that need only core features are not required to pay for additional DAP capabilities and functionality.

The WalkMe Core package includes analytics and reporting, interactive in-app guidance, unlimited user workflows, pre-built or bespoke, omnichannel experiences, and admin security controls including access management, privacy settings, and data hosting and residency. 

Advanced add-on modules feature expanded DAP capabilities that extend the value of the Core package. Available modules include enterprise analytics, customization and collaboration, connected workplace, and enterprise security.

WalkMe for Customers is a package for customer facing applications. It includes advanced analytics and reporting, interactive in-app guides, tooltips, notifications, a self-serve content creation engine, smart audience targeting, enterprise-grade security, personalized onboarding and product tours, customer sentiment via NPS and surveys, and multi-language support, along with branding and white labeling.

WalkMe also offers a slimmed down, more affordable option called WalkMe Essentials. This is a package that comes at a fixed price with a fixed scope that is ready to roll out in four weeks. It includes up to two pre-built sales and HR workflows which are deployed for one of the following apps – Salesforce, Microsoft Dynamics, Workday, or SAP SuccessFactors, with professional services support. 

Pendo pricing structure

Pendo offers custom pricing that is based on monthly active users (MAU). The company offers three packages – free, growth, and portfolio.

The free option includes product analytics, in-app guides, net promoter score (NPS), and roadmaps.

The Growth package is designed for use with a single web or mobile app, and includes product analytics, in-app guides, Net Promoter Score (NPS), roadmaps, and cross-app reports.

And the Portfolio package includes all that the Growth package offers but is meant for organizations with multiple products and can be used across unlimited web and mobile apps.

Among the features available in each are in-app guides, sentiment via NPS and surveys, and roadmaps, with the free plan available for 500 active monthly users, and growth and portfolio as a custom offering.

The WalkMe advantage: extending the value of DAP 

WalkMe is the undisputed pioneer of DAP. With a transparent overlay it provides in-app guided tours and walkthroughs that assist users both internal and external users of enterprise software, home-grown applications, and digital tools, on any channel including desktop, mobile, and web.

It offers a feature set that is comprehensive, yet easy to manage for non-technical users. WalkMe also offers extensive customization options for addressing numerous user types and use cases.

One of the most widely appreciated benefits of WalkMe is how it extends the value and promise of DAP with unique features such as cross-app automation, cross-application analytics and insights, and an ActionBot that is powered by conversational automation.

The Pendo advantage: enhancing the product experience 

For some companies ensuring a smooth product experience is the focus, rather than securing digital proficiency. This is where Pendo has found its niche. With an in-product resource center, a feedback solicitation tool, and the ability to categorize feedback, teams can garner insights on features and their usage and tweak as based on real-life user experiences.

Which is best for you? 

Bottom line, which is best for you? As was noted in the beginning of the review, it all depends on what you need.

WalkMe is right for you if you have different types of users who need to be onboarded to numerous new apps and digital tools, or their new features, quickly and easily, and on an ongoing basis. WalkMe is also for you if you’re looking to gain clear, data-driven, and actionable insights into how you can maximize usage and optimize your software investments.

If on the other hand, you’re a mid-market organization or small business and are looking for a straightforward approach to enhancing the product experience, then Pendo is for you.

Not every organization has prioritized full-fledged digital adoption with extensive customization and analytics. If your KPIs are driven by how employees and customers experience a product, Pendo has what you need.

It’s also important to note that WalkMe has an extensive partner and peer ecosystem with an active global community of users and partners that provides insights, support, and resources.

Pendo’s smaller community and less established partnerships point to a less robust ecosystem compared to WalkMe.

WalkMe also outperforms in privacy and security. Comprehensive technical, contractual, and operational safeguards are applied, such as best-of-breed authentication, encryption, access control systems and configurations to protect against unauthorized access. 

Also, unique to WalkMe is segmentation which enables presenting different content to users for various use cases, and personalization that enables users to deliver employee and customer experiences that drive action, with names displayed alongside a contextualized call to action.

In addition, with a library of pre-built templates based on industry best practices, the organization’s most critical workflows on the most popular business applications are easily automated. And ultimately, with patented native AI technology, WalkMe technology outperforms all other offerings.

The post The Definitive WalkMe vs. Pendo Comparison appeared first on Digital Adoption.

Whether you are seeking advanced, data-driven features for complex enterprise environments or simplified tools for straightforward onboarding processes, this guide will help you discern which platform offers the most value to your organization. By highlighting the advantages and potential limitations of both platforms, we aim to provide a balanced view to inform your decision-making process.

Please note that this post will be continuously updated to reflect the evolving landscape of technology, market trends, use cases, and feature updates in both WalkMe and Whatfix platforms.

Both WalkMe and Whatfix are well received by users and industry analysts. But not all DAP solutions were created equal. So, how can you know which is right for you? The first step would be to outline your objectives and priorities beyond the need to streamline onboarding and training with walkthroughs. 

This may include accessing user behavior insights, automating tasks, applying cross-app analytics, and optimizing software licensing, among others.

Once you’ve got your list in hand, a side-by-side comparison of features, capabilities, and user feedback will go a long way towards helping you gain clarity about which solution is best suited for your organization’s digital adoption needs.

WalkMe and Whatfix at a glance

WalkMe is long recognized as an industry leader, having received widespread acclaim for its digital adoption platform. Recent accolades include InfoWorld Technology of the Year Award 2022, Software Asset Management Solution of the Year 2023, Forbes Cloud100 World’s Best Cloud Companies, and many more. 

The platform is well noted for enabling organizations with effective and fast digital adoption. And the company is also regarded for continually introducing innovations that extend the value of DAP, such as its conversational interface that leverages NLP for chat-based interactions.

Whatfix is well known for offering an affordable platform that performs well on delivering core DAP functionalities. The platform is focused on streamlining software onboarding and providing real-time task guidance for reducing the number of inquiries that the help desk receives.

The Whatfix solution is best suited for organizations that have prioritized quick wins over customization depth and self-serve independence.

User sentiment for WalkMe across the leading software review websites is extremely favorable, achieving a nearly perfect score overall, with very high ratings in key criteria, such as ease of use, customer service, and value for money. 

Among the most noted ‘likes’ are WalkMe’s comprehensive feature set, enabling non-technical users to build solutions quickly, extensive customization for tailoring experiences for different users and use cases, streamlined workflows, and automated tasks.

Whatfix comes in with solid reviews, earning positive feedback regarding the platform’s overall capabilities and customer service. The offering is noted for its core functionalities for software onboarding and real-time task guidance. 

Though it’s important to note that reviewers would like to see more customization options and to avoid the need for technical support when making certain configurations and content updates.

WalkMe vs. Whatfix: Data and analytics capabilities

WalkMe is designed for organizations seeking to embrace data-driven decision-making without excessive time and resource investment. With WalkMe, you can track all data related to digital adoption within your organization. This includes individual user and account usage insights, as well as automated discovery of applications across your tech stack, complete with usage analysis. Additionally, WalkMe offers features such as auto tracking, enabling visualization and analysis of every click, hover, and interaction with pre-selected on-screen elements.

Through WalkMe’s application discovery feature, you can automatically view all applications in your tech stack, including total users, usage duration, and frequency. This helps identify potential areas for cost optimization, app consolidation, and license allocation.

Workflow analytics enable you to understand user interactions within apps in the context of specific tasks, identifying drop-off triggers, and improving process efficiency. With guidance analytics, you can track user engagement with on-screen guidance and predefined elements.

Furthermore, WalkMe provides form completion analytics to uncover insights into user bottlenecks, time wastage, or process abandonment. User interaction playback sessions allow you to capture, analyze, and replay entire user sessions. Finally, WalkMe offers customizable reports, providing deeper and more valuable insights into user experience.

Whatfix’s platform offers guidance analytics and a funnel report (called Flows), shedding light on user behaviors. Additionally, Whatfix offers data and analytics features that provide visibility into user interactions with their guidance, and help identify the most and least used content. This is a key strength, as it enables businesses to understand user behavior and adapt their strategies accordingly. However, several users have noted that these analytics can be somewhat unclear and lack comprehensive insights, indicating room for improvement. 

The tool also offers a degree of customization, such as the ability to tailor welcome messages and pop-up triggers, an appreciated feature by users. Despite this, users have expressed a desire for more flexibility in customizing conditions, triggers, and logic that control behaviors. This suggests that while Whatfix’s data and analytics capabilities have strong foundations, they may not fully meet the needs of businesses seeking complex customization and deep analytical capabilities.

Addressing more complex needs requires an IT-level understanding of how data is tracked and monitored. Moreover, while the organization can get reports on user interactions, discovering applications and related interactions is coding intensive.

WalkMe vs Whatfix: Content building capabilities

WalkMe and Whatfix both offer notable content-building capabilities, but there are some distinct differences between the two. WalkMe excels with its ease of use and robust personalization options. Its user-friendly platform employs an intuitive drag-and-drop interface, coupled with detailed guides and tutorials, which makes it an accessible tool for non-technical users. 

WalkMe supports complex business logic and processes with configurable user workflow templates. Users can select the user workflow that aligns to their organization’s most pressing business issue, choose the relevant tasks, and then easily configure and customize WalkMe in-app guidance content to their needs. 

The platform’s superior personalization capabilities stand out, allowing users to tailor their walkthroughs based on user preferences, roles, and behavior, facilitating a more engaging and relevant user experience. Additionally, WalkMe goes a step further with its advanced segmentation and branching capabilities, enabling users to create unique paths based on user responses or behavior. 

WalkMe’s broad language support also makes it a suitable option for global businesses that need to create and manage content across various regions and user groups.

On the other hand, Whatfix is equally praised for its intuitive interface and easy-to-use editor. Users appreciate the platform’s straightforward content creation and management capabilities, as well as the quick setup process; however, some have noted a learning curve associated with more advanced customizations. 

Whatfix also offers personalization options, such as custom welcome messages and user-role-based guided tours, but users have shown interest in a deeper level of personalization capabilities. Whatfix provides segmentation features, allowing content to be customized for different user segments, but lacks the depth of WalkMe’s branching capabilities. Lastly, while Whatfix does support multiple languages, a bonus for international customers, some users have reported occasional issues with translation accuracy.

WalkMe vs. Whatfix: Automation and workflow support

WalkMe offers robust automation and workflow support with features such as smart walk-throughs, onboarding flows, and automation bots. The platform excels in providing interactive guides and smart tips to support users throughout their workflow journey. Additionally, WalkMe provides easy-to-use tools for creating custom workflows, allowing users to design and implement user paths tailored to their specific needs.

On the other hand, Whatfix also offers interactive guides and smart tips, assisting users in their workflow journey. While it allows for workflow customization, some users have reported limitations in the flexibility of conditions, triggers, and logic that control behaviors. Furthermore, there has been user feedback regarding limitations in the integration capabilities of Whatfix, which may hinder workflow efficiency.

Both WalkMe and Whatfix support task automation, enabling businesses to streamline operations and improve productivity. However, it is important to note that the extent of automation capabilities may vary depending on the specific requirements of the business.

WalkMe vs. Whatfix: Enterprise readiness

WalkMe demonstrates a strong capability in scalability and governance, due to its robust feature set that can easily adapt to diverse enterprise requirements. The platform provides comprehensive analytics and reporting tools, offering insightful data that can inform decision-making processes. 

WalkMe has a mature partner and community ecosystem, with many third-party integrations and a highly engaged developer community. The platform also leverages advanced technology, such as ML/AI, to personalize user experiences and streamline processes. However, in terms of change management, WalkMe users have reported challenges in the setup and configuration process, suggesting the need for robust technical support.

WalkMe prides itself on its commitment to data security, demonstrated by its numerous security certifications. The platform is ISO 27001 certified, signifying adherence to international standards for information security management. Furthermore, WalkMe holds the SOC 2 Type II certification, an endorsement of its robust controls for security, availability, and confidentiality. WalkMe is also the only DAP that has achieved Fed-RAMP Ready status, fulfilling the rigorous security and privacy requirements set by the US federal government. The presence of these certifications underscores WalkMe’s commitment to protecting customer data and maintaining a high level of security within its platform.

Whatfix’s enterprise readiness is seen in its advanced technology capabilities, where it employs ML/AI for personalization to enhance the user experience. However, Whatfix falls short in aspects of scalability and governance, mainly due to its limited customization options and a somewhat complex implementation process. Its reporting and analytics capabilities, while helpful, are said to be lacking in depth, limiting the insights gained for data-driven decisions. 

Moreover, Whatfix’s partner and community ecosystem shows room for improvement, as users have indicated that the community forums and developer resources could be more active. In terms of change management, reviews suggest that the setup, configuration, and content updates can be challenging, necessitating the need for technical support. 

WalkMe vs. Whatfix: Customer support

When comparing WalkMe and Whatfix’s support and customer success, there are several factors to consider. WalkMe is known for its high-quality customer service, with most users praising their quick response times and problem-resolution skills. They offer a wealth of online resources, including video tutorials, webinars, and a comprehensive FAQ section, which are highly appreciated for their usefulness and ease of use. WalkMe also has a vibrant online community where users can engage with each other, find solutions to problems, and share tips and tricks. 

On the other hand, Whatfix’s customer support receives mixed reviews. While some users find the response times slow and post-support follow-up lacking, others appreciate the support team’s helpfulness and responsiveness. Whatfix users suggest a need for more comprehensive educational resources and documentation. However, they do provide embedded on-screen help and interactive walkthroughs during onboarding, which are highly valued.

Whatfix does not have a specific community engagement platform or user forum. They do, however, provide a basic community area for discussions, posting tips, and answering customer inquiries.

WalkMe vs. Whatfix: Business value and ROI

When evaluating the business value and return on investment (ROI) of WalkMe and Pendo, there are several factors to consider:

WalkMe, with its robust set of features, provides significant business value. Its advanced automation capabilities can lead to substantial time savings for businesses, effectively increasing productivity levels and reducing operational costs. The platform’s detailed analytics can also provide valuable insights into user behavior, enabling businesses to optimize their software usage and improve overall user experience. These improvements can lead to higher customer satisfaction levels, increased customer retention, and ultimately, increased revenue.

In terms of ROI, WalkMe’s users often report a swift return on their investment. The efficiency gains from using the platform can lead to significant cost savings. Furthermore, businesses can expect increased revenue from improved customer satisfaction and engagement, further enhancing the ROI.

Whatfix delivers value to customers through enhanced user experience and measurable impact on ROI. Customers report a significant reduction in training and support costs, faster onboarding, and increased user engagement, all leading to enhanced productivity and performance. 

Users also benefit from improved application usability, faster onboarding, and increased user engagement, leading to enhanced productivity and performance. Moreover, the tool’s impact extends to improving sales processes, boosting conversions, and fostering customer independence and self-sufficiency, thus resulting in a positive ROI. 

While WalkMe offers a more robust and feature-rich solution, Whatfix provides a more streamlined and cost-efficient alternative. 

WalkMe vs. Whatfix pricing comparison

WalkMe 

WalkMe offers two pricing packages, WalkMe for Employees and WalkMe for Customers. Both are designed to be flexible for accommodating any organization at any stage of the DAP maturity lifecycle as well as for easily picking the package of capabilities and pricing that’s right for them.

The WalkMe for Employees package includes a subscription model for the WalkMe Core offering with optional advanced add-on modules. This approach enables alignment between required features and corresponding pricing, where organizations that need only core features are not required to pay for additional DAP capabilities and functionality.

The WalkMe Core package includes analytics and reporting, interactive in-app guidance, unlimited user workflows, pre-built or bespoke, omnichannel experiences, and admin security controls including access management, privacy settings, and data hosting and residency. 

Advanced add-on modules feature expanded DAP capabilities that extend the value of the Core package. Available modules include enterprise analytics, customization and collaboration, connected workplace, and enterprise security.

WalkMe for Customers is a package for customer facing applications. It includes advanced analytics and reporting, interactive in-app guides, tooltips, notifications, a self-serve content creation engine, smart audience targeting, enterprise-grade security, personalized onboarding and product tours, customer sentiment via NPS and surveys, and multi-language support, along with branding and white labeling.

WalkMe also offers a slimmed down, more affordable option called WalkMe Essentials. This is a package that comes at a fixed price with a fixed scope that is ready to roll out in four weeks. It includes up to two pre-built sales and HR workflows which are deployed for one of the following apps – Salesforce, Microsoft Dynamics, Workday, or SAP SuccessFactors, with professional services support. 

Whatfix 

Whatfix has two main pricing packages – one for DAP and one for product analytics. The DAP package is then further broken down to web, desktop, mobile, and enterprise plans. For a web deployment, there are standard, premium, and pro options. The first two options are designed for employee or customer-facing applications, with the pro option intended for customer facing applications with over one million users.

Each web package option includes features such as in-app guidance, surveys, and content aggregation, with progressively more extensive capabilities depending on the package level. For example, surveys in the standard package are out-of-the-box, but in the premium package they may be customized.

The DAP desktop, mobile, and enterprise packages have two options – standard and premium, both for employee or customer facing applications, and each with a certain features set, based on the level selected.

The enterprise package is the only one that covers an unlimited number of web-based employee-facing applications.

The product analytics pricing package also comes with a standard or premium option. The standard package is designed for a cloud-based deployment plan that is available with any web, desktop, or enterprise plan. The premium package is designed for cloud-based deployment of web-based and desktop-based employee or customer-facing applications.

Among the features available in both are user action tagging, dashboards, funnel insights, event properties, and more, where the standard package allows for 25 tag user actions and the premium option is unlimited.

Pricing for each package is comprised of a flat fee along with user license fees, which are defined as based on the type of user who will access the application.

Whatfix product and service add-ons include out-of-the-box content templates, integrations, and analytics, white-labeling, professional services, and more.

Whatfix offers a free trial to interested organizations.

The WalkMe advantage: extending the value of DAP 

WalkMe is the pioneer of DAP. With a transparent overlay it provides in-app guided tours and walkthroughs that assist users both internal and external users of enterprise software, home-grown applications, and digital tools, on any channel including desktop, mobile, and web.

It offers a feature set that is comprehensive yet easy to manage for non-technical users. WalkMe also offers extensive customization options for addressing numerous user types and use cases.

One of the most widely appreciated benefits of WalkMe is how it extends the value and promise of DAP with unique features such as cross-app automation, cross-application analytics and insights, and an ActionBot that is powered by conversational automation.

The Whatfix advantage: quick wins at an affordable price

Whatfix is well positioned for organizations seeking basic capabilities that accelerate enterprise software onboarding within a modest budgetary framework.

The platform offers simplified content creation for deploying real-time task guidance and reducing training and support efforts.

With a range of self-serve features, Whatfix is ideal for teams who prefer a collaborative approach and are open to engaging with the company’s support team to unlock additional capabilities.

WalkMe vs. Whatfix: What is the best digital adoption platform for you? 

Bottom line, which is best for you? As was noted in the beginning of the review, it all depends on what you need.

WalkMe is right for you if you have different types of users who need to be onboarded to numerous new apps and digital tools, or their new features, quickly and easily, and on an ongoing basis. 

WalkMe is also for you if you’re looking to gain clear, data-driven, and actionable insights into how you can maximize usage and optimize your software investments.

If, on the other hand yours is an organization whose processes are not marked by complexity and you don’t mind workarounds to issues that are specific to your workflows, then Whatfix is for you. 

With Whatfix you’ll get straightforward onboarding processes and affordability without the depth and breadth of a wider DAP offering.

The post The Definitive WalkMe vs. Whatfix Comparison  appeared first on Digital Adoption.

This environment makes it essential to consider what an AI-driven digital transformation should look like and its benefits and limitations to accelerate digital transformation and bring investment for a fast ROI. 

70% of digital transformations fail, but using AI to drive your large-scale changes could be the key to the success you have been searching for. 

Add to this the fact that enterprise AI adoption hit 35% in 2023, and projections suggest that the global market value of AI will reach USD 738 billion by 2030. It becomes clear that now is the time to invest in AI-driven digital transformation. 

This article will dissect AI-driven digital transformation, encompassing its definition, elucidating its significance in 2024, outlining its pivotal role in the current landscape, and delving into the manifold advantages organizations reap from embracing AI-driven digital transformation strategies.

What is AI-Driven Digital Transformation?

Digital transformation is making radical changes to your organization’s operations, and AI-driven digital transformation is simply leveraging AI to make changes most efficiently. 

This type of transformation puts automation driven by machine learning and generative AI at the forefront of the tech stack, ensuring that your organization benefits from AI in every way possible to succeed against competitors. 

Using AI to steer digital transformations can be beneficial in business IT projects and corporate processes like customer service, software development, and life sciences.

Why is AI-Driven Digital Transformation Important in 2024?

Enterprises have been implementing AI tools for decades now. Still, it was only really in March 2023, when Chat-GPT4 exploded onto the scene, that AI became the most desirable technology every enterprise wanted in their tech stack.

2024 will, therefore, be the year of AI, as more enterprises begin to ensure that generative AI tools like ChatGPT and similar AI tools like Google Bard and Microsoft CoPilot become the tools CEOs want to help their organization stay on top. 

There are three reasons why AI-driven transformation is essential in 2024.

Increases developer efficiency

Organizations are adopting generative AI in the form of software coding assistants. Developer productivity is the lowest priority in terms of the adoption of LLMs.

It also enhances developer efficiency by automating repetitive tasks, providing data-driven insights, optimizing workflows, and facilitating rapid problem-solving. These benefits result in accelerated development cycles and improved organizational productivity.

Revolutionizes customer experience

AI transformation is making significant strides in reshaping customer support, placing it at the forefront of business processes. Movate, headquartered in Plano, Texas, specializes in digital technology and customer experience (CX) services. 

Approximately 60% of the company’s business operations are centered around CX and technical support services. This is an example of a company where customers primarily engage with the support center through digital channels like the web or chat, using AI as the core of their digital transformation. 

Provides industry challenge solutions

AI assumes vital roles in diverse sectors, notably in life sciences. Fujitsu Ltd. and the RIKEN Center for Computational Science collaboratively employ generative AI for drug discovery and analyzing electron microscopy images. 

This innovative approach predicts protein structural changes, envisioning a groundbreaking life sciences platform that drastically streamlines drug discovery timelines and costs. 

Fujitsu sees generative AI as a transformative force in digital transformation, adept at swiftly navigating the dynamic and unpredictable business landscape of a VUCA (volatility, uncertainty, complexity, and ambiguity) world.

Consider why AI-driven digital transformation is essential in 2024 to realize why you should invest in this approach to stay ahead of competitors and maintain success.

The Role of AI-Driven Digital Transformation in 2024

The role of AI in any digital transformation has changed from several decades ago when it was a minor technology in its infancy. 

In 2024, enterprises must consider three elements to ensure AI-driven digital transformation success, putting AI at the forefront of all new technology investments:

1. AI-driven strategy.
2. AI change management support.
3. AI-driven Digital Transformation Technologies.

1. AI-driven strategy 

There are five steps to ensuring a robust and successful AI-driven digital transformation strategy, beginning with establishing goals. 

Establish goals

Define your primary objectives before embarking on AI transformation to assess its impact on growth. Common goals include reducing operational costs, enhancing efficiency, understanding customer behaviors, and saving time on repetitive tasks. 

Start small, focusing on one main goal, implementing AI workflows, and gradually expanding to other areas. Ensure clarity and measurability in your team’s goals, following the SMART (Specific, Measurable, Achievable, Relevant, Time-bound) framework for effectiveness. 

A weak goal like “Reduce operational costs” becomes a SMART goal when specifying a 10% reduction in monthly expenses within four months through energy-efficient solutions, supplier contract renegotiation, and streamlined processes. 

This comprehensive approach ensures clear objectives and helps minimize costs while maximizing profitability.

Build your AI-driven digital transformation strategy

Now that your goals are set let’s dive into the exciting part: crafting your AI strategy. Outline your goals, strengths, weaknesses, and a three to six-month action plan. Clearly define how success will be measured. 

Specify the tools your team should explore, designate leaders, and identify projects for AI integration. Set ground rules, recognizing that while AI is powerful, it requires human input and quality control—combining human creativity with AI talent. Take this opportunity to anticipate potential errors and establish preventive measures.

Identify an entry point

With your strategy set, it’s time to implement your plans. To ease into AI for non-technical users, start with user-friendly tools. 

To initiate your AI-driven digital transformation, define clear objectives and assess your organization’s strengths and weaknesses. Start small, experimenting with user-friendly AI tools to build familiarity. 

Set measurable goals, integrate AI gradually, and ensure human collaboration for optimal results. Regularly evaluate and adjust your strategy as needed for continuous improvement.

Offer a robust AI training program

Ensuring successful AI adoption involves offering internal training courses to your employees. This builds confidence in using the tools, encourages solution creation, and enhances understanding of optimal utilization. 

While AI tool providers may assist with training, additional internal efforts are crucial. This includes suggesting input ideas, integrating AI tools into the existing tech stack, promoting usage among top performers, and celebrating and incentivizing small wins.

Create incremental processes

While demanding, this concluding step proves highly effective when executed. As your team initiates the AI strategy rollout, designate a point person to assess and document each process’s effectiveness. 

This evaluation lays the groundwork for crafting standard operating procedures and best practices, ensuring ongoing success. These procedures facilitate scalable operations and accommodate the increasing sophistication of your processes.

2. AI change management support

AI is one of the best examples where staff need change management support as fears of job losses due to automation run high. 

Therefore, It is essential to consider the approaches below to ensure staff receive adequate support to implement your change management strategy. At the same time, stress and burnout are low, and employee retention remains high to ensure a human-centered AI approach. 

Predictive Analytics

Employing AI to analyze historical and real-time data helps identify patterns and trends, enabling organizations to foresee potential obstacles, resistance, or areas of success in the change management process. 

Through predictive analytics, decision-makers can foresee challenges, proactively devise strategies to address them, and minimize risks while maximizing the likelihood of success.

Employee Sentiment Analysis

Leveraging AI-powered sentiment analysis allows evaluating employee attitudes, emotions, and perceptions of change initiatives as you build your AI-augmented workforce.

By scrutinizing data from diverse sources like surveys, social media, and internal communications, AI offers insights into employee sentiment, pinpointing areas requiring additional support, contact, or intervention. 

Decision-makers can customize change management strategies to address specific concerns, boosting employee engagement and buy-in.

Recommender Systems

AI-based recommender systems can recommend pertinent resources, training programs, or best practices to employees based on their roles, skills, and needs. 

These systems analyze individual and collective data to provide personalized recommendations, aiding employees in adapting to changes more effectively and enhancing their performance during the transition.

Real-time Analytics

AI empowers organizations to analyze data in real-time, furnishing decision-makers with up-to-date insights into the progress and impact of change initiatives. 

Real-time analytics help identify bottlenecks, measure the effectiveness of interventions, and facilitate agile decision-making, enabling organizations to make timely adjustments and optimize change management strategies as needed.

Simulations and Scenario Planning

AI-driven simulations can model different scenarios and their potential outcomes, allowing decision-makers to assess the impact of various change management strategies before implementation. 

Simulating diverse systems allows organizations to evaluate each approach’s potential risks and benefits, enabling them to make data-driven decisions based on likely outcomes.

Continuous Monitoring and Feedback

AI-driven monitoring systems can consistently collect and analyze data related to change initiatives, offering decision-makers real-time feedback on progress, adoption rates, and areas requiring attention.

3. AI-driven Digital Transformation Technologies

Entering 2024, the substantial influence of artificial intelligence (AI) on digital transformation becomes more apparent. AI is not a distant vision; it propels innovation, efficiency, and competitiveness in various industries. Discover below how AI trends will fuel digital transformation in 2024.

Elevated Customer Experiences

AI transforms experiences, enhancing customer satisfaction and loyalty through personalized interactions and other tools and experiences.

Technologies for this include:

• Tailored personalization: AI-driven algorithms analyze extensive datasets to offer customers highly personalized recommendations, content, and product selections, cultivating loyalty and boosting sales.
• Interactive AI: Advanced chatbots and virtual assistants with natural language processing (NLP) capabilities deliver seamless and efficient customer support, resulting in heightened satisfaction and loyalty.
• Voice and visual search: AI-powered voice recognition and image analysis technologies facilitate more intuitive and efficient search and shopping experiences, significantly enhancing e-commerce platforms.

Data Insights and Analytics

AI-driven transformation revolutionizes data insights analytics, enhancing efficiency and informed decision-making.

Technologies for this include:

• Anticipatory analytics: AI models predict trends, consumer behavior, and market dynamics with exceptional accuracy, enabling businesses to make proactive decisions, optimize resources, and capitalize on opportunities.
• Real-time analytics: AI processes vast data streams in real-time, enabling organizations to swiftly respond to changing conditions, from adjusting pricing strategies to optimizing supply chains.
• AI-enhanced business intelligence: AI automates data preparation, visualization, and reporting, democratizing data access across organizations and empowering decision-makers.

Operational Efficiency and automation

AI-driven transformation enhances efficiency, automating operations for streamlined and optimized performance.

Technologies for this include:

• Robotic Process Automation (RPA): AI-powered bots automate repetitive tasks and processes, reducing errors, enhancing efficiency, and liberating human talent for more strategic activities.
• Streamlined supply chain: AI optimizes supply chain operations by forecasting demand, managing inventory, and minimizing transportation costs, ensuring smoother logistics and cost savings.
• Quality control and maintenance: In manufacturing, AI-driven vision systems and sensor arrays ensure product quality, decrease defects, and minimize downtime through predictive maintenance.

Healthcare Evolution

AI transforms healthcare, accelerating innovation and improving patient outcomes and experiences.

Technologies for this include:

• Medical imaging: AI aids healthcare professionals by analyzing medical images, improving diagnostic accuracy, and expediting patient care.
• Drug discovery: AI accelerates drug discovery by analyzing extensive datasets, predicting potential drug candidates, and expediting development.
• Telemedicine progress: AI-powered telemedicine and remote patient monitoring systems enhance healthcare accessibility and efficiency, reducing the burden on traditional healthcare infrastructures.

Financial Services Advancement

AI propels finance, advancing services with precision, security, and strategic insights.

Technologies for this include:

• Algorithmic trading: AI-driven trading algorithms analyze market data, execute trades swiftly, and effectively manage portfolios.
• Credit risk assessment: AI evaluates creditworthiness using alternative data sources, broadening access to financial services for underserved populations and streamlining lending processes.
• Fraud detection: AI identifies fraudulent activities in real-time, fortifies security, safeguards financial assets, and protects sensitive customer data.

Sustainability and Energy

Sustainability and energy concerns can benefit from AI driving your digital transformation. 

Technologies for this include:

• Intelligent energy grids: AI optimizes energy distribution, reducing waste, costs, and carbon footprints while enhancing the reliability of energy systems.
• Climate modeling: AI assists in climate modeling, aiding governments and organizations in making informed climate change mitigation and adaptation decisions.
• Green technologies: AI-driven innovation accelerates the development and optimization of renewable energy systems, making them more efficient and economically viable.

Cybersecurity Reinforcement

The evergrowing concerns around cybersecurity can be resolved using a digital transformation using AI. 

Technologies for this include:

• Threat Detection and Response: AI-enhanced security systems detect and respond to cyber threats quickly and accurately, fortifying overall cybersecurity postures.
• Behavioral Analysis: AI examines user and system behavior to identify anomalies and potential security breaches, mitigating risks more effectively.
• Phishing Prevention: AI-powered email security systems detect and prevent phishing attempts, reducing the likelihood of successful cyberattacks.

Education Revolution

AI-driven digital transformation will fuel the education revolution via tailored learning, administrative efficiency, and accessibility initiatives. 

Technologies for this include:

• Tailored learning: AI tailors educational content and assessments to individual students’ needs, fostering better learning outcomes and engagement.
• Administrative efficiency: AI streamlines administrative tasks in educational institutions, reducing overhead costs and improving administrative efficiency.
• Accessibility initiatives: AI enhances accessibility by providing tools and materials for students with disabilities, promoting inclusivity in education.

Advantages of AI-Driven Digital Transformation

Despite its limitations, AI-driven digital transformation has many advantages to be aware of to ensure you need to invest in this technology. These advantages benefit business understanding, workflow, and transformation tooling. 

Enhanced business understanding

AI enables in-depth analysis of vast data sets, empowering organizations with profound insights into their business drivers. This knowledge empowers business leaders to steer digital transformation initiatives efficiently.

AI’s more accurate insights enhance the effectiveness of digital transformation by providing precise data-driven guidance. AI eliminates guesswork, ensuring transformation efforts align with a company’s needs, market trends, and customer demands. 

The ability to swiftly process large datasets and identify patterns leads to informed decision-making, resulting in more successful and impactful transformations.

Comprehensive workflow examination

Generative AI opens doors to holistic transformations, surpassing incremental improvements and expanding the scope of digital transformation.

Organizations can use generative AI to assess each step in a workflow process, identifying areas for improvement or cost reduction. Generative AI facilitates addressing tasks previously deemed challenging or lacking clear ROI, offering a cost-effective approach to experimentation.

Integrated transformation tooling

AI integrates into various dimensions of digital transformation, including essential subcomponents like data readiness, as used by Stellar, an AI services provider in Indianapolis. For instance, a business may need to establish new data schemas as the foundation for a new AI application.

AI tools, such as those developed by Stellar, assist in constructing the data layer supporting the top-tier system. Flinchum highlighted the deployment of a cloud data warehouse as a standard step in this process. While the initial schema may not be 100% accurate, AI tools accelerate data readiness. 

IBM Consulting employs a tool from its IBM proprietary AI advisor toolkit to enhance internal operations and client delivery. The company has also revamped its Garage Experience toolkit, incorporating generative AI to replace hand-drawn sketches with functional prototypes coded for agile co-development with clients.

AI-driven digital transformation becomes the conduit through which enterprises can unlock the transformative power of hyper-personalization, data insights, and operational efficiency. It’s about elevating customer experiences to unprecedented heights, streamlining operations with newfound efficiency, and making decisions backed by rich, data-driven insights.

The integration of predictive analytics, automated processes, and cutting-edge technologies exemplifies the tools at your disposal. Generative AI, in particular, emerges as a beacon, allowing organizations to keep pace with market trends and catalyze themselves ahead. This tool empowers enterprises to anticipate future developments, adapting strategies proactively rather than reactively.

Embracing the future of business innovation isn’t just a recommendation; it’s a prerequisite for sustained success. And the landscape is not just evolving. It’s becoming increasingly reliant on the agility and intelligence that AI-driven digital transformation provides.

As enterprises navigate this landscape, those who actively adopt and integrate AI will survive and thrive, setting the stage for a new era of unprecedented possibilities and achievements in the business world.

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