Product Usage Segmentation – A Short Guide For SaaS
What is product usage segmentation? How can you harness product usage data to improve user segmentation and boost the growth of your SaaS?
You’ll find answers to these questions below.
This guide will help you get a basic understanding of different types of usage data and how you can use them to improve your product and user experience.
- Product usage is all the user interactions with the product, service, or its features
- Product usage rate is how much of the product is utilized by a user during a specific period of time
- You can leverage product usage data to help the product and customer-facing teams improve UX
- Product usage data gives you objective insights into customer behavior
- A product manager should pay attention to the kinds of product usage data about user in-app behavior, like their actions, achieved goals, retention, or feedback
- Product usage data allows identifying the most popular features, their stickiness, issues or friction across the user experience, or variations in feature adoption between different user segments
- Some relevant product usage metrics include product onboarding engagement rate, product activation rate, or product adoption
- One of the biggest benefits of product usage tracking is accurate user segmentation
- Product usage data tracking will help you reduce churn and boost satisfaction
- There are a lot of tools available for collecting and analyzing product usage data, such as Userpilot, Heap, Fullstory, Mixpanel, or Iteratively
- Userpilot not only lets you track and analyze customer behavior but also design bespoke in-app experiences to help them achieve their goals
What is product usage segmentation?
Product usage describes the interactions of users with your product, service, or feature.
Data about how, when, and for how long a customer uses the product. This type of data is generated whenever the user interacts with the product and is used to enhance informed decision-making.
Product usage segmentation is all about building very specific user segments based on how your users engage with your product, using the product usage data you’ve collected.
What is the product usage rate?
Product usage rate is simply how much of the product is used by a user within a specific timeframe.
In practice, this means the number of features used by a particular user group to achieve their goals. Users are often categorized as heavy, moderate, and light, based on their product usage rate.
Why is product usage data important for SaaS?
Product usage data allows SaaS product managers and developers to make informed decisions about product roadmaps and product lifecycle.
Product usage analytics is superior to other sources of customer behavior information such as surveys because they provide objective quantitive data on how the users really engage with the product.
Without such data, product and development teams would be left groping in the dark and trying to guess what the customers may need, which is particularly hard if they often don’t realize that themselves.
Types of product usage segmentation data
There are lots of types of product usage data you could collect and use to build specific segments.
Depending on what you are trying to achieve and your product, some of them are more relevant than others.
Product managers are interested in data on what user does within the app and whether they get the job done. That’s why they may be interested in looking at:
- Actions, i.e. what users do after they log into the product
- Achieved goals/completed tasks, i.e. if users accomplished what they originally intended, or if they finish an action after they started it
- Retention, i.e. if they return to use the same features of the product again, and how many subscription payments they didn’t miss
- Feedback, e.g. if they complete any surveys or interact with the support team while using the product
Product usage analytics can provide insights into a range of things, including:
- what the most popular features are
- what issues do your users face
- how “sticky” a feature is
- how adoption differs between different user segments
- what the friction points are and where the customers need an extra push
Product usage segmentation metrics to track
Choosing the right product usage metrics to track is essential. There are so many of them, that it is easy to get swamped with data if you are not careful.
As a result, you can miss the insights that really matter to your SaaS.
The aim of tracking product usage is to identify trends in how the users engage with the app, what they find difficult, what they find useful, and what increases their commitment to the product.
Let’s have a look at the top 8 product usage metrics, which may be of value for a SaaS product manager:
- Number of key user actions per session – how many times users complete core usage actions
- Product activation rate – the number of users reaching the activation point
- Time to value – the time needed by the user to reach the Aha! moment
- Product adoption – the stages the users reach on the product adoption journey
- Customer engagement score – the overall view of the user engagement, useful for identifying engaged and disengaged users
- Feature usage – the number of users engaging with particular product features
- Product usage stickiness – daily active users to monthly active users ratio, helpful for identifying groups with highest product usage and features that elicit the highest usage.
While measuring product usage, make sure to avoid vanity metrics.
They may make your product look really good on paper, but they are absolutely irrelevant from the perspective of product development.
What’s the benefit of knowing the frequency of use for a product manager? It tells you nothing about user in-app behavior.
How to use product usage data to segment your audience
User segmentation is the main reason for tracking product usage.
Product usage data segmentation based on in-app engagement
Users that engage with your product regularly require a different approach from those that don’t.
By looking at key metrics such as customer health score or customer engagement score, you can segment your user base into those two groups. Once you know which users have the highest usage and which lowest, you can engage them more effectively with your messaging.
You can also track the engagement frequency of your core features and build user segments of your highly engaged users or the opposite, disengaged users who are at risk of churning. Once you have these, you can reach out with personalized messages to each.
Product usage segmentation based on user journey stage
Where your user is in their journey will have an impact on what type of marketing message will be most effective for them.
Track milestones using goals- a set of custom events or in-app engagements or simply build segments tracking when specific events happened altogether, meaning the user has reached a specific milestone.
The groups that are stuck at a particular stage may need help and the communication should aim to help them move on.
Messages introducing advanced features, on the other hand, maybe completely lost and possibly even frustrating to users who haven’t started using the app (aka engaged with its main key features).
Conversely, the users who have swiftly and fully explored the core product features may benefit from in-app messages introducing more advanced functionalities.
Product usage segmentation based on feedback collected
For example, you could use the NPS score to divide them into two main groups: loyal customers and detractors.
Next, the first group can be contacted for a more detailed review.
The latter group, on the other hand, could be offered a helping hand so that they don’t churn.
How to use product usage segmentation to improve customer retention and satisfaction
There are a few ways in which product usage data can be used to improve customer retention and satisfaction.
Identify active user behavior trends that correlate with retention
Looking at your most active users (based on LTV) can help you understand which parts of your product are driving value.
For example, let’s imagine that user segment A that uses the product to complete JTBD no 1 consistently uses features X-Y-Z.
If you understand this, you can reach out to other users who are only using features X and Y and use in-app guidance, as the tooltip in the example below, to help them discover feature Z that will bring value.
That will translate into greater user retention.
Convert trial users to paid
Tracking product usage will help you convert free trial users into paid customers.
If you use user segmentation to understand where your customers get stuck, you can support them by offering contextualized guidance.
Celebrate each milestone they reach and tell them what the next step that they should be taking is.
By exploring the product and engaging with its features, the users discover its value and are more likely to commit to the paid version.
Identify and remove friction across the journey
It’s not only the trial users that get stuck but also the paying ones, and they all need your attention if you don’t want to lose them.
Product usage data tells you which users and what part of the product they find hard to use.
Armed with that knowledge, you can build interactive guides to help them engage with the relevant features for the first time.
Would you like to see a good example? Have a look at how Userpilot helped Rocketbots to guide their users to Aha! moment.
Upsell relevant features to each user segment
Using product usage data lets you create segments and identify the users who would benefit from specific premium features.
Build better products that bring value to users
Behavioral segmentation allows you to identify the most loyal groups of users, who can be a source of invaluable feedback.
Having identified the users with positive KPIs, you need to ask them about the changes and improvements they would like to see in the product. Satisfied customers are more likely to provide in-depth feedback that you can use to guide further development.
Just don’t take them for granted and make sure you offer them some incentive to take part in your surveys.
Access to beta features or a gift voucher could be a good start, and with time you could develop a comprehensive loyalty program.
How to collect data: Product usage analytics tools
Let’s have a look at a few digital tools which you can use to track user engagement and retention inside the app (which distinguishes them from tools like Google Analytics which are designed to focus on the acquisition stage of the user journey.)
Note though that it is only a short guide to product usage and we already have a dedicated article on choosing user journey analytics tools for your SaaS, so this section is by no means meant to be comprehensive.
- Userpilot – apart from tracking user behavior, our tool’s main focus is on allowing you to build real-time, personalized in-app experiences for your users
- Heap is a user and account-level tracking tool
- Fullstory is a user analytics and session recording tool
- Mixpanel has a vast array of capabilities for tracking and collating user data
- Iteratively allows you to combine data from all your tools in one place
Product usage data tracking gives you a chance to make informed decisions about product development, marketing, and user experience.
If you would like to see how Userpilot could help you leverage product usage data to improve user experience, get a demo!