Software Usage Analytics Guide for Product Managers
Data is power. Any savvy product manager should be looking at how they can leverage software usage analytics to make more informed decisions and boost product growth.
In this article, we’re going to unpack exactly what usage analytics is, why you should care about it, how to use it in your product, and the best tools for the job.
What is software usage analytics?
Software usage analytics (sometimes referred to as product usage analytics) describes the process of capturing, analyzing, and utilizing data on how your users interact with your product.
There’s an enormous amount you can learn from product usage analytics:
- Which of your features are the most popular
- Feature ‘stickiness’
- The impact on different segments
- Friction points and drop-off points
- Information on hypotheses you’ve explored with A/B testing
That barely scratches the surface, but it’s important not to get overwhelmed by the detail. Put simply, it’s about tracking your users as they use your product.
Product usage analytics vs marketing analytics
There’s a common misconception that marketing analytics and product usage analytics are one and the same thing. On the contrary, there are clear distinctions.
Marketing analytics primarily focus on external data and metrics related to customer acquisition, inbound marketing channels, website attribution, and engagement with your community. Google Analytics is a massively popular tool in this space.
Product usage analytics is far more focused on in-app user behavior and engagement.
Here’s the rule of thumb: think external versus internal.
Why is it important to track product usage data?
Product managers are busy people. Why is it worth spending your time on product usage analytics? Here are a few key factors to consider:
- Improve decision-making. How can you make informed decisions without the right insight? Software usage analytics helps you adopt a fact-based, data-driven mentality – and that’s the best way to inform your decision-making and prioritization.
- Reduce friction. If you don’t know where your users are getting stuck, you can’t do anything about it. Use analytics to identify friction points in the customer journey and focus your efforts on removing them.
- Boost user experience. Analytics provides a whole host of valuable insights into how users interact with your product. Harness this data to make improvements throughout your app and drastically enhance the user experience.
How can PMs monitor in-app user behavior and user engagement?
As a product manager, you have two primary methods of gathering information about in-app user behavior and engagement.
- The traditional approach: reaching out directly to users. Whether you’re conducting customer interviews, gathering feedback from surveys, or running focus groups, this is a proven way of collecting valuable data. However, it’s costly and time-consuming, and you always run the risk of bias bleeding into the process.
- The modern approach: software usage analytics. Quantifiable, hard data on feature engagement, user behavior, and more.
How to conduct product usage analysis in your SaaS?
Next, we’ll break down exactly how to explore software usage data in your own product.
Define goals behind analyzing product usage data
A famous quote from author Simon Sinek is “Start with why.”
This is good advice in the product world, too!
Beginning with an idea of where you want to end up – the reason you want to conduct software usage analysis – gives you a much higher likelihood of succeeding in your goals.
Let’s say you want to increase retention. That will inform and direct all your efforts.
Different goal-setting frameworks, like OKR or the Golden Circle framework, can be used to determine your objectives.
Choose the right product metrics
Here are some of the key metrics to measure. Remember, metrics are different from analytics. Analytics deals with collecting and analyzing data, whereas metrics focus on evaluating a company’s success.
- Activation rate. The proportion of users who’ve been activated (i.e., experienced value). It is calculated by dividing activated users – as you’ve defined activation – by the total signed-up users during a time period.
- Adoption rate. This gives you an idea of your overall product adoption (i.e., the percentage of users regularly using your product).
- Feature usage rate. This figure gives you an idea of feature adoption (i.e., the percentage of users regularly using a given feature).
- Customer engagement score. This composite metric will help you understand how users really feel about your product: how engaged are they, and how likely are they to keep paying for your services?
- Daily active users or monthly active users. A useful proxy for overall product stickiness, tracking this metric will help you figure out whether you’re doing a good job of keeping users engaged and retained.
Select data collection sources and gather customer usage data
You’ve set the direction, and you’ve worked out which metrics to track. Fantastic! Next, you need to think about gathering data. Here’s how you do it.
Events and feature tracking
Both event analysis and feature tracking can help you better understand user behavior. In a nutshell, you can tag important events, features, and milestones in the customer journey to track how users are interacting with them (or not, as the case may be).
What makes this particularly useful is the ability to dive deep by segmenting the data of distinct user personas (remember your users are not one homogenous group).
Heatmaps
A heatmap is a visualization (using colors) that demonstrates how users are interacting with your UI. They show clear evidence of which parts of your product your users engage with.
There are many types of heatmaps: feature click maps, hover maps, eye-tracking maps, and scroll maps. They are all useful for product teams – and can help them make targeted improvements – but must be considered carefully.
Remember, sometimes understanding which features are ignored is the most valuable data: it’ll indicate which features you can retire.
Session recordings
Session recordings allow you to re-watch a recording of your users interacting with your product. You’ll be able to see what features they’re using, how they navigate through your product, and potential areas of friction.
Because of the replay factor, you can gather by far the most detail of any of these options: each time you re-watch you’ll learn something different!
Analyze data collected and identify usage patterns amongst different user segments
As we’ve discussed, your users aren’t one homogenous group. Look into the data you’ve collected with a critical eye: are there themes and patterns you can identify amongst distinct user groups?
There are various types of analysis you can conduct – it’ll all depend on the goal you’ve set.
- Customer journey analysis. What are the primary drop-off and friction points you can identify as a user progresses along their journey?
- Milestone analysis. How many users are reaching key milestones (as you’ve defined them) throughout your product?
- Retention analysis. Are you doing a good job of holding on to your existing users?
- Churn analysis. How many users are leaving your product in a given time period?
Implement findings through in-app communication
Once you’ve analyzed and acted on user data, make sure you’re doing a good job of communicating with your users about what features you offer and how they help.
It could be that the reason behind low adoption is simply that your users aren’t aware of what’s possible – luckily, that can be easily rectified. Userpilot makes it simple to build in-app walkthroughs to boost feature adoption.
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