Unless you’ve been living under a rock the past decade, you’ll know that data is key to the success of any SaaS product. Perhaps the most important data at your disposal is product usage analytics.
In this guide, we’re going to look at:
- What product usage analytics is
- Why product usage analytics is so useful
- How segmentation takes your data to the next level
- How to use product usage analytics to boost product engagement
Let’s get started!
What is product usage analytics?
Product usage analytics is a process in which you analyze data concerning how your users interact with your product.
The idea is you track your users as they use your product. You can see which features they use, how they navigate round your product, and ultimately how much value they get from it.
You can then take that data and use it to identify areas of your product that need improving or tweaking in some way in order to boost user engagement.
There’s a wide range of different things you can learn from product usage analytics, including:
- Your most popular features
- Issues that your users face
- How “sticky” a feature is
- How adoption differs between user segments
- When customers need an extra push
- The results of A/B testing
That’s not even half of the things you can find out with product usage analytics.
The wealth of information you can uncover with product usage analytics makes it an integral part of product management.
But what makes it so important?
Why is product usage analytics so useful?
Product usage analytics is integral to the success of a SaaS product. The insights it gives you can make or break your product.
There are many factors that make product usage analytics incredibly useful. For the purposes of this article, let’s focus on three:
Product usage analytics is objective
When it comes to learning how your users interact with your product, there are two main routes you can take.
The first route is to speak to your customers. You can talk to them about how they use your product, what they like and dislike, what they want to see you build next.
This is valuable information, and should definitely be on your to-do list if you aren’t doing it already.
However, the issue with the data you get from surveys and interviews is that it’s a little subjective. People often don’t quite realize exactly how they use a product. They just use it, often on autopilot.
As for predicting what they want from a product, well, that’s not always accurate either. Most of us don’t truly know what we want. That’s why the best advice is always to seek problems from customers, and then create the solution yourself.
This lack of accuracy and objectivity presents a problem. If you’re going to be basing product decisions on inaccurate data, then you could end up wasting a lot of resources.
The solution, of course, lies with product usage analytics.
The key difference here is that product usage data doesn’t lie. It doesn’t get it wrong. Rather than relying on what people say they do, you can simply see what they actually do.
A quantitative approach to data means you can draw realistic, actionable conclusions from it. That’s what makes product usage analytics so useful.
The bottom line is that surveys and interviews are helpful, and speaking to customers is never a bad thing. However, you need to balance that with more objective product usage data.
Product usage is specific
Imagine that you recently launched a new feature, and you want to know two things:
a) how many users have adopted it, and
b) how they first discovered the new feature within your product
Now the first of those two things is fairly general. It’s relatively easy to figure it out.
You can either take a quick look at your product usage analytics, or you can use a slightly longer method and send out a survey.
The second question requires a little more nuance. It’s a lot more specific. What you’re essentially trying to find out is the path that users take to reach this new feature.
Imagine asking users that, and expecting them to come up with an actual answer. If you asked me how I first reached a new feature in your product I’d honestly have no idea. I’d probably say something along the lines of:
“Well I guess I was at the dashboard, then I think I went into the reports and clicked around. Then I ended up at your new feature.”
Unfortunately, that doesn’t tell you much at all. Clicking around on the reports is very vague, and doesn’t give you any valuable insights. It’s not specific enough.
That’s where product usage analytics comes in.
Product usage analytics can tell you exactly the route that users took to reach your new feature.
That’s because the data you collect is comprehensive. Everything that a user does inside your product, every click, every scroll, every interaction, is recorded.
Product usage analytics gives you the full picture, so you can dive in deep and find specific answers to your questions.
Product usage is efficient
If there’s one thing you don’t have a lot of when building or improving a product, it’s time. The SaaS world moves fast, and that means you need to move even faster.
That’s one of the biggest issues with surveys and interviews. They take a lot of time. With surveys you have to wait for replies to trickle in. With interviews you need to actually be there to conduct them.
Often, this is time you simply can’t afford. Especially given that you’ll need a lot of survey responses or interviews to get any genuinely useful results and insights.
You need something more efficient. Fortunately, you can’t do much more efficient than product usage analytics.
Sure, it might take a bit of time to implement at the start. Sure, you might need to learn some basic statistical analysis. But once you’re up and running, you can get the answers to your questions in a matter of minutes.
It takes a few clicks to delve into the data, and you can do it all from your computer in your own time.
It’s quick, it’s easy, it’s efficient. What more could you need?
How segmentation takes your product usage analytics data to the next level
Clearly, usage analytics is a great tool to have at your disposal.
Before we move on to how you can use the data to boost product engagement, we’re going to touch on segmentation.
Segmentation is the process you use to split your users into different groups.
Most commonly, these groups will correspond to different user personas. However, you can split your users up based on all kinds of data, including:
- Demographics (age, gender, location)
- Psychographics (personality, values, concerns)
- Behavioral (usage, engagement, pricing tier)
Segmentation is key to personalizing your product to each user. By understanding how each user segment interacts with your product, you’re able to customize the product to each group.
Personalization plays a big part when it comes to driving engagement with your product. Anything you can do to appeal more to users will help hook them into your product.
That’s the main reason we preach about the power of contextual onboarding. You can send the right message to the right user at the right time.
EDITOR’S NOTE: We wrote a lot more about contextual onboarding, and how you can get started with it, in our article here.
The only way you can do this is by separating your users into different segments. Product usage analytics can help you figure out what those segments should be.
How to use product usage analytics to boost product engagement
Now that you know what product usage analytics is, and why it’s so useful, it’s time to move on to the how.
Step 0: Set up your tracking
Before you do anything else, you need to make sure you’re collecting all the product usage data that you’re going to need.
The easiest way to start tracking user behavior is to use a product analytics platform. The most popular of these are Mixpanel, Heap, and Pendo.
We personally love Heap, but feel free to go and try all of them out and see which suits your organization best.
Implementing the tracking software may take a bit of time and technical knowhow. But it’ll be worth the investment.
Once you’re up and running, you should spend some time getting to know the analytics. Learn how the software works, how to generate reports, and how to get the answers you want.
Once you’ve mastered it, and you’re sure you’re collecting accurate data, then it’s time to get started.
(Also it’s worth pointing out that you may need to wait and gather more data before you carry on with the next steps.)
Step 1: Choose a goal
It’s best to take a focused approach when it comes to product usage analytics. A lack of focus will mean you spend a lot of time coming up with nothing much at all.
Your goal will ultimately be dependent on your current business needs, as well as your product strategy.
Chances are a lot of different stakeholders will have a say in this. Your best option is to have a short meeting in which different goals and outcomes are discussed.
Once you settle on a goal, make sure everyone is aware of it. Anyone who will be working with you on this project needs to be fully behind the goal as well.
Step 2: Gather benchmarks and ask questions
Now that you have your goal, you need to know what you want to measure.
Different goals will require different product metrics. If, for example, your goal is to retain more customers, then you need to know current retention and churn figures.
This is also where you start asking questions. You want to try and understand the why behind the measurements.
To continue with our retention goal, you should now be wondering why customers are churning. What are they doing, or failing to do, before they churn?
Make a list of relevant questions that you need answering. Somewhere between 5 and 10 is a good amount for one project.
Step 3: Dig into the data
Now for the fun part. It’s time to take a look at the data you’ve been collecting and get those questions answered.
Let’s stick with our example of wanting to reduce churn.
We could start by looking at the segment of users who have churned. We can then look at things these users have in common.
Perhaps every customer that churned didn’t go through our onboarding process. Maybe most of our churned customers never updated their profile, or connected their email account.
We’re bound to find some useful product areas that we can focus in on.
Remember that it’s easy to get carried away with all this data. Make sure you stick to your goal, and the questions you wanted answering.
Once you’ve found the relevant bits of data you need, you should export it so that you can easily share it with other relevant team members.
Step 4: Start experimenting
The data you’ve collected gives you a benchmark to work from. You can now start trying to improve on that benchmark by making tweaks and improvements to your product.
Start by picking out the 2 or 3 key insights that your product usage analytics has given you.
For the purpose of our example, let’s say our insights were:
2: 60% of churned users didn’t complete the initial onboarding flow.
At this point, you can sit down with other relevant colleagues and start brainstorming ways in which you can improve your product.
EDITOR’S NOTE: We wrote an article with some tips and tricks on how to increase product engagement. You can read that here.
Remember that it’s more effective if you A/B test these changes. You already have your benchmark, so try out different improvements and see which works best.
Key takeaways for using your product usage analytics data
We’ve covered a lot in this article, so let’s recap what we’ve learned…
- Product usage analytics is where you analyze your users’ in-app behavior.
- It gives you valuable insights into how you can improve product engagement.
- Product usage analytics are objective, specific, and efficient.
- It’s important to segment your users. This allows you to better understand them, and to personalize their user experience.
- Tools like Mixpanel and Heap make it really easy to get up and running with product usage analytics.
- A rough process looks like this: choose a goal, gather benchmarks and ask questions, dig into the data, start experimenting.
Hopefully you now understand the power that product usage analytics can bring to your product.
If you’re looking for an easy, code-free way of making improvements to your onboarding, then why not give Userpilot a try?
About the Author
Joe is a UX and content writer, with several years of experience working with SaaS startups. He’s been working with SaaS startups that are focused towards product management, product marketing and customer success for the past couple of years.