Enhance Your Product Adoption Strategy with These 3 UX Analytics Tools

UX research can go a long way in solving recurrent usability problems at every stage of the user journey. But it’s especially important during the onboarding and adoption phase when users are still assessing whether they will stay and enjoy using your product – or churn and never return. You need to make sure your users are so delighted that they not only decide to stay but also recommend your product to everyone willing to listen. But how do you do that? Let’s unpack a bundle of three UX analytics tools that will come in handy in this quest to craft a truly outstanding user experience!

First up: what is UX analysis and why should you care about it?

UX analysis is a systematic approach to evaluating user experiences with digital products or services. It involves collecting and analyzing with the end goal of understanding user behavior, preferences, and pain points. This helps in identifying areas for improvement and optimizing the overall user experience.

UX analysis is not just about collecting data for data’s sake. It requires a deep understanding of user psychology, as well as the ability to interpret data and identify actionable insights. UX analysis is also not just about making things look pretty, but about improving the usability, accessibility, and overall satisfaction of a product/service for the user. It is a crucial part of the UX design and development process that helps ensure that digital products/services meet user needs and expectations in the best possible way.

To put it briefly, if you care about what happens to your customers after they’ve converted, you should read on – no matter if you are a UX researcher, product manager, or engineer in search of UX analytics tools.

Let’s define the adoption stage!

It’s sometimes tricky to define what stages a user goes through on their way to fully adopting a product. The adoption stage in the user journey can loosely be described as the phase where users decide whether or not to continue using the product. It comes right after the activation stage when users are introduced to the value that can be potentially delivered and then convert in anticipation of discovering more. During the adoption stage, users are assessing the value proposition of the product and whether it meets their needs and expectations. If the product fails to do this, users are likely to abandon it and look for alternatives.

One of the key challenges during the trial > activation > adoption sequence is onboarding. Many products and services fail at this point because they don’t invest enough effort in showcasing the value of the product upfront. This requires clear and concise instructions, intuitive navigation, and minimal friction. Poor onboarding experiences often lead to frustration and confusion, churn, and negative reviews. Yikes.

Another challenge during adoption is building trust. Users need to trust that the product will deliver on its promises – and that their personal information is secure. This requires transparent communication and a focus on data privacy and security.

During the adoption stage, users are highly oriented toward achieving the desired outcome that led them to the product in the first place. For example, if the product is a fitness tracker, the main goal of the user will be to quickly assess whether the mobile app can help them achieve their fitness goals. 

Common misconceptions about the adoption stage include the belief that users are already invested in the product and will be forgiving of usability issues. In reality, users are still evaluating the product during the adoption stage and are more likely to abandon it if it fails to meet their expectations. Another misconception is that users will take the time to learn how to use a complex product. Sorry to break it to you but users nowadays don’t have the time or patience to navigate complex UIs unless the value they will get is very high.

Understanding the challenges and goals of users during the adoption stage is crucial for designing a successful product. Fortunately, UX analytics tools can help identify issues and areas for improvement, leading to a better user experience and increased adoption rates – so let’s jump ahead.

Qualitative and quantitative data: which is better during the adoption phase?

The simple answer is both. It will be very difficult for you to make an informed decision based on only one type of data. Quantitative analysis can give you broader strokes, but qualitative data will be able to give you the finer details.

Modern Digital Experience Analytics platforms combine quantitative and qualitative data within one interface, saving UX analysts time and money on expensive customer surveys. For example, SessionStack can give you the benefits of full-blown user segmentation and funnel analysis – but also session replays of matching user sessions to finish the entire process of searching for the UX truth. 

Imagine you are the product manager of a meal-planning mobile app and you want to improve the adoption rate of a new feature that helps users discover new recipes by other users. Currently, the overall adoption rate is far lower than that of the classical recipes feature. By doing quantitative analysis – user segmentation, you realize that the majority of the users who haven’t used the new feature are using your Android app. On the contrary, users of iPhones are doing great and using the feature extensively. You dig deeper by creating a funnel of the user journey with the new feature for users in the Android segment and notice that they drop off at the second step – which is browsing other users’ recipes. At this point, you know that something on this screen is not entirely all right but you don’t know what. So, you select a few of the sessions in this segment and go through them with a session replay. It turns out that there’s a technical issue and users are seeing only one recipe on the list! A quick engineer debrief and a few days later the bug is fixed. Ta-da, the adoption rate among the Android segment is up!

3 UX analytics tools to help you boost adoption rates

As tricky as it is to have visitors convert to users AND make them stay, it’s actually a pretty simple task from the perspective of psychology. You need to empathize with them. By understanding your users’ true pain points, the journeys they take with your product to solve these pain points, and the issues they encounter along the way, you’ve unlocked an achievement on your path to growth. 

To help you do that, UX analytics tools come in handy. While there are dozens of tools available on the market, today, we’ll focus on the three we believe have the biggest impact for analysis during the adoption journey. 

1. User segmentation

A type of quantitative analysis, user segmentation helps you understand how different groups of people use your product. User segmentation groups users based on common characteristics – such as demographics (age, location, role), events (specific clicked elements or visited pages), or session data (browser, technology, session length, etc). Armed with this data, you can gain a better understanding of what different user groups find helpful – or frustrating, and act on the knowledge to deliver a better experience. For example, compare segments of users who use specific browsers and notice if there is a difference in their usage patterns – maybe there are more rage clicks than usual, maybe the CR is significantly lower, or maybe they perform completely different user interactions than users on other browsers.

2. Funnels

Funnels are amazing UX analytics tools to measure the success of a specific user journey – or discover new ones. With funnel analysis, you can discover drop-off points at scale and work from there to improve the conversion rate. Add user segmentation, and you have a holistic overview of how different users move through the user journey, inspecting the impact of various technologies, for example. Funnels are a great way to validate your A/B testing or other improvement strategies – benchmarking against an existing funnel analysis can quickly show you whether your assumptions were correct. 

3. Session Replays & co-browsing

While funnels are indispensable to discovering the bigger picture, it’s product usage visualization tools that show what’s really happening during an individual user session. Session recording tools are nifty snippets of code that record and replay whole user sessions with a pixel-perfect session environment (called session replay). A common misconception is that it is a video recording of a session. In reality, it is a recording of the whole user environment, with console logs and errors, that recreates not only the visual part but also the underlying experience in detail. After you have segmented your users, mapped the user journey onto a funnel, and pinpointed problematic areas, you probably have an assumption as to what happened. But is it valid? Watching a few user sessions can give you that answer much more quickly than trying to reach out to users individually or waiting for someone to report a problem. Remember – during the onboarding stage, users are not as hooked up as you might think. If not happy, most of them will simply walk away, never revealing the reasons behind their decision. 

If session replay sounds too good to be true, wait till you hear about co-browsing! Collaborative browsing can be a true gem during the onboarding process. For example, it allows customer success agents to hop on a call with a user who is having trouble navigating the product and guiding them to success in real time. For high-profile customers, this can allow customer success teams to easily schedule a training session that doesn’t bore the customer to sleep. 

Contextual Metrics and KPIs to Monitor with UX analytics tools

Every UX analysis begins with a good strategy involving specific KPIs and metrics to track. Since the adoption stage is not isolated, it is a good idea to track adoption as part of a broader KPIs structure. Here are some core metrics to include in your reports so that you can analyze adoption in a context rather than as an isolated event. These may not be strictly in the domain of UX tools, but they can help you pinpoint areas where a UX analysis is needed to alleviate issues and suggest improvements.

• Time to Value

Time to value is a metric that is specific to each product or service. One way to define it is the time it takes for the user to realize your product or service is indispensable to them (some call it the Aha moment). Time to value is connected to activation rate as oftentimes, the key event in the activation sequence is the one that brings the Aha moment. The shorter the TTV, the better – as we all know, modern users’ attention spans are quite short…

• Conversion rate

Conversion rate is the percentage of users who complete a desired action, such as signing up for a trial or making a purchase. It can help identify areas of the product that are causing friction or confusion and can be used to optimize the user onboarding process. As mentioned above, funnels can be indispensable in measuring and optimizing conversion rates, as well as validating tests following UX adjustments.

• Activation Rate

The activation period is described as the period between trial and adoption when your users are becoming paying customers. It is crucial for the adoption stage as it has to prove to the user that your product can deliver in the long run and is worth the money just spent. The Activation rate can be tied to key activation events – the use of specific features or fulfilling specific onboarding milestones. In the case of the fitness app, this may be the percentage of people who successfully create a fitness routine and log at least one fitness session with it.

• Adoption Rate

Adoption rate is measured as the percentage of users who use a specific feature compared to the overall number of users of the product. By segmenting adoption in this way, you can evaluate which features are suffering from adoption issues and define a strategy for improvement in your next product iteration cycle. If you need to take a broader look at adoption, usage frequency or certain customer success KPIs might come in handy.

• Usage Frequency 

Usage frequency is defined by the number of users who log in to your product/service for any given period of time. It may not be specifically tied to logins, though – maybe you need to track only users who log in and use a specific feature? The ratio of Daily Active Users and Monthly Active Users is handy in assessing the overall ‘health’ of your offering. It’s also called stickiness (a term coined at Facebook to measure their app’s engagement).

• Churn rate

The saddest of all metrics to keep an eye on, non? Churn rate is measured by calculating the number of customers leaving compared to your total customer base. It is important to monitor the churn rate as it can be an indicator of major issues – both in terms of usability and value. Another metric that also speaks to negative customer experiences is the rate of downgrades.

To put it in a nutshell…

The product adoption phase is critical to growth. If users don’t adopt your product or service, you will lose them along the way – thus losing valuable opportunities for sustained revenue, upgrades and upsells, word-of-mouth recommendations, and creating brand advocates. The best way to stand out from the crowd is to deliver an outstanding product that has strong retention rates throughout its lifecycle. UX analytics tools for usability testing such as user segmentation, funnels, and session replay can prove invaluable in the quest to improve adoption. Remember – a long-term growth strategy requires you to look beyond the ‘bottom’ of the funnel – and into a Happily ever after phase.