It’s difficult to overstate the significance of quality user onboarding and ongoing guidance regarding customer retention and loyalty. For example, Wyzowl found that 86% of customers will remain loyal if they receive proper onboarding and continuing product education support. Traditional video and one-on-one user onboarding delivered by customer success teams were established with this in mind, but as the SaaS market grows, companies struggle to scale these efforts.
Most organizations know that guided, self-service onboarding experiences are the key to scaling while still giving customers enough support to realize the value of their platform, and AI is making this vision much more attainable. In fact, according to ChurnZero’s 2024 Customer Success Leadership Study, 78% of CS teams used or were currently implementing AI technologies.
AI enables product and CS teams to personalize user experiences, optimize key flows, and support new users with self-service tools. For many companies, this innovative and scalable approach to guiding users is made possible by Whatfix, an all-in-one user onboarding platform that supports users and drives adoption.
In this guide, we’ll explore how you can use AI to create better and more scalable onboarding experiences for your users and highlight some practical strategies for doing it quickly and simply with Whatfix.
How Can AI Improve User Onboarding?
Using AI to Personalize Your User Onboarding Experiences
One of the most impactful use cases for AI in your onboarding experience is the ability to tailor it to each customer’s needs. This personalization ensures that each user discovers the value of your platform in relation to their specific needs as quickly and seamlessly as possible, increasing the chances that they will hit their “aha!” moment and retain.
In this section, we’ll detail the primary AI-driven strategies for personalizing onboarding and user guidance on your platform.
1. User segmentation based on user demographics and app usage
Though product analytics have long been a key element of product and user onboarding flows by helping teams cater to users with specific usage patterns or demographic properties, AI has exponentially increased the potential value of analytics.
With AI, teams cannot only track and monitor user behavior but also predict and react to it in a way that creates a personalized experience beyond what SaaS platforms have traditionally offered. Using machine learning and natural language processing, artificial intelligence analyzes user behavior and characteristics, identifying patterns that help your team segment users into highly nuanced groups.
For example, based on user data, AI-driven algorithms establish that users who don’t do a certain action on your platform within the first 3 days of onboarding are twice as likely to churn. Rather than waiting for this to happen to a certain percentage of users, these users can be segmented and offered extra guidance – perhaps a call with customer success – to help them overcome what’s stopping them from moving forward with that important action before the 3-day mark.
With an advanced tool like Whatfix Product Analytics, your team can track the success of your AI-driven personalization and iterate continuously for optimal results. With Whatfix Product Analytics, you can implement a no-code event tracking tool to monitor and analyze any custom user event, segment your data by user actions and behavioral data, benchmark key performance indicators, and launch data-driven tests.
2. Flow branching depending on user actions
Most SaaS platforms have complex and dynamic flows that offer different potential actions at every step of the way. Traditionally, teams relied on users to determine their next steps in any given user flow based on their own needs, but AI now offers the ability to guide users toward the actions that make the most sense best on their preceding behavior.
AI-driven data analysis involves analyzing large data sets to determine the most likely successful actions that come one after another. When you know the next likely actions based on these predictive algorithms, you can take users through the actions in the flow that make sense for them.
For example, perhaps you learn that users who add at least 3 properties to a report almost always preview the report before exporting. You could serve the preview and offer export as a next step without users having to click around, creating a smooth experience.
3. Content localization
Offering onboarding experiences in each user’s native language makes a huge difference in their ability to learn what they need to know to succeed on your platform.
In the past, localization was a complex and costly endeavor, involving translation agencies and a lot of implementation. Now, AI allows you to localize content, such as your onboarding flow, seamlessly and in real time.
With a global user base and the help of artificial intelligence, language barriers are becoming almost a non-issue for SaaS platforms.
4. AI-assisted onboarding copywriting
No matter how experiential and interactive your onboarding flow is, copy is still a key element for helping users learn and understand what they need to know as they familiarize themselves with your platform. Creating copy that is easy to absorb and communicates what your customers need to know has always been a challenge. With AI-assisted copywriting, however, teams are finding it much simpler to hit the mark with their copy.
AI uses machine learning and natural language processing to understand, from large data sets, which copy causes users to take action. Taking action implies that users absorb what to do next and are motivated to do it. What’s more, AI-assisted copywriting is iterative, so the AI learns as it goes and continually optimizes your copy.
While your copy still needs some human oversight, using AI-assisted copywriting in your onboarding flow can reduce the use of internal resources for copy and help you optimize the text in your flow faster.
Supporting New Customers With AI-Powered Self-Service
SaaS platforms are complex, and typically, there is a lot of user documentation and a relatively steep learning curve for new customers. In the age of artificial intelligence, we have a unique opportunity to not only provide resources but also give users extremely nuanced help at exactly the right moments.
Let’s examine two of the most powerful AI-driven strategies for empowering your customers with self-service support.
1. AI help centers and chatbots
Your organization probably has several knowledge repositories where platform instruction is stored. Here are some examples:
- Customer-facing learning management system (LMS)
- FAQs
- Technical documentation
- Release notes and changelogs
- Knowledge base
- Support ticket canned responses to common issues
The challenge has always been directing users to the right source of information, which can be difficult when there are so many potential sources of information. AI help centers and chatbots can solve this problem because you can train them based on the aforementioned knowledge repositories, and they learn to give users the information they need in the moment, regardless of where that information lives.
In practice, if a user asks your chatbot a technical question, the AI knows to serve something from your technical documentation. Similarly, if a user asks about a key feature for which you have great instructions in your knowledge base, it can provide the right links.
Many companies choose to use Self Help, the AI-powered knowledge base within the Whatfix DAP, for a quick and easy solution that integrates all sources of truth about your platform and seamlessly serves it to your users. From a user experience perspective, this creates a reality where users no longer have to click around to figure out where relevant information lives—the AI can direct them right away.
2. Using support queries to identify and create new help content
Since AI’s superpower is learning and predicting based on large data sets, it gives teams a unique opportunity to find gaps in their knowledge base.
Specifically, you can export data from AI chatbot conversations with customers in addition to search queries within your knowledge base, and the AI can suggest new knowledge base and support articles to write based on what people ask and search for.
Over time, this reduces the resources required of your customer support team by creating self-serve resources for the things users frequently struggle with. It also facilitates a better user experience because users are more likely to find the help they need when they look for it.
Not only can AI help you identify new and necessary topics for knowledge base and support articles, but you can also use AI to help draft the content itself. Often, tools like ChatGPT can generate high-quality drafts and then your team can edit as needed and add complementary visuals when it makes sense.
AI-Powered User Onboarding Flow Optimization
In this section, we’ll discuss the top 3 strategies for optimizing your onboarding flow with AI so that you and your team can start with a new, user-centric flow that’s likely to help with your topline KPIs.
1. Using AI to analyze user behavior and identify friction points
With AI-powered product analytics, you can spot where dropoff or confusion typically occurs in your onboarding flow and identify which actions suggest that the value of your platform isn’t being realized by users.
At first, this may sound similar to what you’ve always done with your user behavior analytics, but AI adds another layer of functionality to behavioral data. For example, if you use a comprehensive platform such as Whatfix Product Analytics with AI functionality, you can:
- Generate automated analyses that don’t require a data analyst based on app usage and custom events.
- Get insights about the user experience throughout your onboarding flow, including predictive metrics based on user behavior.
- Easily share these insights with product and CSM teams so that they can quickly react to any opportunities for an improved flow.
Whatfix Product Analytics offers no-code AI functionality, which means that anyone on your team can access and utilize these insights without the help of analysts or the tech team.
When you’re using AI-powered analytics, it helps to look at insights by user segment. You can use Cohorts in Whatfix Product Analytics to group your users by demographic or behavioral characteristics and then understand and react to their onboarding experience according to their specific needs. Overall, this will help you have a more strategic approach to onboarding that goes beyond one-size-fits-all, which is rarely the case when it comes to SaaS platforms.
2. Suggest content improvements and user flow changes
Once your team has begun to collect AI-driven insights based on your analytics, you’ll need to create action items based on what you learn. The iterative flow looks like this:
With such nuanced insights, you’ll have a lot of opportunities to ideate iterations for your onboarding flow. Here are some examples:
- Improve your content to match user needs better: When you see that users struggle or drop off at specific points in your onboarding flow, you can update content, such as your knowledge base, to provide more context where needed.
- Add guidance to minimize user friction: You can use a tool such as the Whatfix DAP to implement and test in-app pop-ups, product walkthroughs, and beacons highlighting support content when your insights tell you that users are struggling with something.
- Change user flows to create clarity and a better user experience: While content and guidance are helpful, you may also get some insights that point toward more fundamental changes in your user flows. For example, if you find that doing a certain action on the platform within the first session is correlated with a higher likelihood to retain, you may want to include that action earlier in your onboarding flow.
Reacting to AI-driven analytics is a cross-functional task. Be sure to include colleagues from product, design, support, sales, and tech when prioritizing and ideating iterations to your onboarding flow. A diverse group of perspectives will help your team come up with more nuanced and innovative ideas to continuously improve your onboarding flow.
3. Use user feedback to conduct sentiment analysis
Though your product analytics give much-needed insights, one thing that behavioral data can’t do alone is to tell you how your customers are feeling, and to what extent they’re satisfied. Customer sentiments are important for getting a complete picture about how we’ll you’re serving your users, and how likely they are to retain in the long term.
Artificial intelligence allows us to analyze data about user sentiments and clearly see what we’re doing well and what we can improve from a customer perspective.
Here’s how you can collect the right data and use AI to get an actionable analysis:
- Collect user feedback at the right moments: You can use a tool such as Surveys in the Whatfix DAP to ask users quick and engaging questions about their experience and satisfaction at specific moments in the onboarding flow. This can give you a 360 view of where in your onboarding flow users are perceiving value and at which moments they need more clarification.
- Conduct sentiment analysis using AI: You can upload both numerical data from user surveys and free text to a tool such as ChatGPT. You can prompt the AI to help you understand what this qualitative and quantitative data is telling you about user sentiments at different points in your onboarding flow.
- Work with your team to create relevant action items: After conducting your sentiment analysis, your team can ideate how to react to what you’ve learned. Where do your customers need more clarification of the value your platform offers? Where do they feel confused instead of confident? A cross-functional team can create a prioritized list of action items based on the answers to these questions.
User Onboarding Clicks Better With Whatfix
Whatfix partners with many platforms in the SaaS industry, offering an all-in-one user onboarding and growth platform. Whatfix has some of the most innovative AI features in the industry, enabling content creation, in-app personalization, intelligent self-service for your customers, data-driven analysis and recommendations for improving your onboarding and user experience overall.
In this section, we’ll go through some of the best strategies for powering up your user onboarding experience with Whatfix.
Use the Whatfix DAP to understand and guide your users
The Whatfix Digital Adoption Platform (DAP) helps your team to better support your customers by increasing your understanding of their experience at various points in the flow and enabling you to offer targeted guidance at just the right moment.
Here are some specific strategies for using the Whatfix DAP to improve your onboarding experience:
- Improve your knowledge base content with AI: The AI-driven features in the DAP offer content writing assistance and recommend content that your users need to succeed on the platform.
- Support your customers with an in-app, conversational Self-Help assistant: This enables them to get help and direction when needed, without waiting for your support team or having to search excessively for the right content.
- Offer customers highly personalized experiences: With the DAP, you can provide experiences tailored precisely to each customer’s needs through features like auto-translation and path recommendations based on user segments.
- Collect user feedback and conduct a sentiment analysis: Using Surveys in the DAP allows you to ask users for feedback at various points in the onboarding flow and then conduct an AI-powered sentiment analysis to identify points where your users may need more guidance or help understanding the platform’s value.
Overall, the Whatfix DAP is a no-code solution for creating a data-driven onboarding strategy that harnesses the power of AI to serve your customers a tailored, guided experience that increases the likelihood that they’ll stay on the platform long term.
Get more out of your behavioral data with Whatfix Product Analytics, powered by AI
Whatfix Product Analytics is a no-code event tracking platform that enables your entire team to track, monitor, and get insights from your behavioral data without the help of data analysts or developers.
Here are some specific examples of how you can use Whatfix Product Analytics to inform your onboarding strategy and better serve your new customers:
- Monitor user behavior in onboarding to understand effectiveness: Your team can create custom events throughout the entire onboarding process and look at where and how different customer segments experience friction. These data points give you critical direction in terms of opportunities to improve your onboarding.
- Use AI to identify areas of friction: Whatfix Product Analytics uses AI to serve up a fast and thorough analysis of your onboarding flow. The platform can identify where your users struggle without a time-consuming analysis on your part.
- Get AI-powered recommendations for giving users better guidance: In addition to identifying points of friction, Whatfix Product Analytics provides concrete recommendations for how to improve the experience for users who struggle. You’ll get suggestions for where to add guidance in addition to specific suggestions for new support content to author.
Are you ready to improve your onboarding results with Whatfix? Schedule a demo today!
