A Guide to Product Usage Analytics and Measuring Software Usage

If you have a fantastic product, but people just don’t see it, there might be a certain point where users get stuck or give up on the product before reaching the ‘’Aha!’’ moment.

I hear you asking, ‘’how do I know that people fully benefit from my product?’’

Easy:

You make Software Usage Analysis a must in your business.

Without further ado:

What is Software Usage Analytics?

Software Usage Analytics is putting analysis over how and how much your customers use your product. Analyzing your product usage is essential to know if the customers are using the key features of your product and get that ‘’Aha!’’ moment.

If they don’t, your product might go down, just like any other possibly brilliant product that failed due to wrong execution.

Don’t get me wrong, analyzing product usage might not be efficient enough on its own. But it is a fact that using Product Usage Analysis and Product Success KPIs together will leave almost no space for mistakes and failure in your product.

What makes Analyzing Software Usage so important?

Product Usage Analysing: What makes Analyzing Product Usage so important?

Creating a good product and letting it wander alone in the market is no longer enough since it’s 2021, and the competition is tighter than ever.

Analyzing your Product Usage allows you to:

  • See your strongest and weakest features from the users’ eyes,
  • Channel your time and priorities to what needs more attention and what needs more push,
  • Evaluate the stickiness of your features,
  • See how the different segments use your product.

Most companies already do Product Analysis and PX improvements to get the product to its best form possible.

But

What you think and what the users think differs almost every single time

– it is impossible to make a perfect product without knowing what the users think of it.

And most people just abandon a product they don’t like. Literally, no one bothers giving feedback, even if it’s as simple as a few words (‘’I didn’t like the design’’ is one of the simplest examples).

Well, there is only one option left: analyzing the users’ journey in the product, therefore, knowing what they did and didn’t like without them saying it.

For instance, when I’m writing an article, I ask for my teammates’ comments and opinions to make sure that everything I’m trying to convey to the reader is clear. What I think that sounds clear and simple does not always seem as simple to everyone.

Also, using Product Usage Analytics in the early periods of your product can help you identify the key features that you might not have foreseen to become ‘’key features’’.

Things don’t always go as planned after all, right?

“The most dangerous kind of waste is the waste we do not recognize.”

Shigeo Shingo

Let’s think:

You have a product that enables the users to create different kinds of lists (playlists, watchlists, book recommendations, etc.).

Instead of being another notebook, this product also enables the users to share and follow different lists and see the ratings and comments of every movie, book, song, and even list.

You thought that being able to see the ratings and comments was the most crucial feature of the product and put it into the premium version.

But people liked it so much that everyone wanted to become an influencer on the platform. Being able to promote and share the lists became the most crucial feature of the product, without you even realizing it.

In the end, no one cared about the comments anymore, and no one paid any attention to the premium features since they could become influencers without it.

If only you had traced the usage of your product and made the ‘’create your own list’’ feature a paid feature in the early stages. Because if you do it now, you will lose credibility.

The moral of this little story:

If you have a freemium product model, you have to put the ‘’key features’’ into the premium version, or else no one will pay for an upgrade.

I know that not all products have free and premium features put together.

If you have a 100% free product, you have to make people prefer yours and get as much traffic as your product can.

And for that, you need to know which features need improvement and which need more attention. In other words, you need to know what features your users use the most and which ones they don’t even realize.

Well, I’m not even talking about paid products. At this point, it is somewhat obvious that you have to serve the customers what they want, more importantly, what they need to make them keep using the product.

There are 2 ways to get to know what the customer needs: the traditional way and the 21st century way

Let’s agree on one thing: methods evolve and change within time, so, ‘’the best’’ doesn’t remain the actual best forever.

By far, you might have thought: ‘’why would I bother on analyzing chunks of numbers instead of directly asking people what they want?’’

Don’t worry, I have 3 strong opposing arguments (I was in the debate society in high school):

  1. First of all, people know what they want, but not everyone wants the same thing. Something that is essential to 10 users might not be such a big deal for other 1000 users who didn’t participate in the survey. This means, if you listened to a minority of 10 people, you would have wasted tons of effort and time.
  2. What people think they want, might not be what they actually need. Don’t forget that customers are neither product specialists nor developers. Almost every single product that launched or grew extremely strong managed to do so thanks to their innovative ideas. They knew what people needed before people knew they needed it. I have proof.

And about the ‘’chunks of numbers’’, thanks to the 21st century, you don’t have to be a data scientist nowadays. You can just basically use analytics tools to get the data simplified, explained, and visualized for you to understand.

If we’re all on the same page about ‘’why’’, let’s get to the ‘’how’’:

5 Tips to better track Product Usage

Analyzing Product Usage: 5 Tips to better track Product Usage

Before getting into the tips, don’t forget that the results are supposed to be going according to your expectations. Higher or lower, the numerics of the result is not what you are trying to achieve.

“Quality is never an accident; it is always the result of high intention, sincere effort, intelligent direction, and skillful execution; it represents the wise choice of many alternatives.”

William A. Foster

#1 – Usability Testing and Beta Testing

Usability Testing is conducted before the launch of the product. Yes, even before beta testing.

You ask a few representative users to complete a number of tasks to prove that the product is usable. This enables you to know that your product is ready to be used by real users without crashes or technical problems.

Then comes the Beta Testing phase. By giving the early version of your product to a limited amount of people, you don’t just make them feel special, but you also trigger curiosity in people who are not beta testers.

As for the Product Usage benefits of Beta Testing, you get the first data from those people, meaning that you can start setting accurate goals and expectations now and compare them to your pre-launch expectations.

#2 – Related KPIs: DAU/MAU rate

The Daily Active User / Monthly Active User rate can tell you much about how people tend to treat your product. 

  • If you expected your product to be frequently used, the result should be closer to 1 (higher, basically).
  • If you have different user types using your product, you expect the admins to use your product less frequently. This shows the importance of evaluating different segments separately since otherwise, you would have gotten a misleading result.
  • If your product is supposed to work in the background or be used from time to time, your DAU/MAU rate is more likely to be lower.

#3 – Related KPIs: Session Duration

DAU may not be the ‘go’ tool for every product.

Not everyone might be using Youtube 5 times a day, but how long they stay in the product matters more.
Or if you have an app that is supposed to remind you to get away from the screen, you probably need the session duration to be shorter, and DAU to be higher.

By analyzing the average, minimum and maximum session duration rates of users, you can see if people understand how your product works, and if not, you will have an overall idea of what might be going wrong – or unexpected.

#4 – A/B Testing

In its simplest form, A/B testing is showing 2 different types of updates to different segments, and analyzing and comparing the success rate of each possible update.

Since A/B testing allows real users to evaluate your product, just like beta testing, the results you will get from the Usage Analysis and feedback will be more reliable and certain than any virtually conducted test.

#5 – Product Usage Analytics Tools

Product Usage Analytics Tools will help you get rid of the numeric burden that I mentioned before, and turn the results into visually appealing and understandable charts, lists, tables, etc.

If you haven’t been living in a cave for the past few years, you must have seen a Google Forms Responses page.

Product Usage Analysis - Tips and Tricks - Tools - Google Forms Responses Page

This is a perfect example to show what kind of info you need to expect while looking at the analysis results from a Product Usage Analysis tool.

In other words, don’t be shy to get help from tools when you need them.

But does every tool work and help the same way, or:

Which tools should you use to track software usage?

Product Usage Analysis - Best Tools To Use

#1 – Google Analytics

Google analytics is probably the most common free product usage analytics tool on the market.

Therefore, it can do what most others platforms can’t: it shows you where people come from to visit your website, so you will know if you should keep sparing a big budget to advertising, or focusing on interactions with other sites.

While it allows you to get almost every information that you need about the rates of your product, it doesn’t have an option to track singular data, meaning thet you can’t see the data of what one single user does.

One other disappointing thing about Google analytics is that, it doesn’t allow you to trace what a user does after entering the page, leaving you with only the surface of the data you need.

But, why I recommend this tool is that it’s totally easy to use, and would be a perfect start for your product usage analytics journey

So Google Analytics might be a good starting point to analyze Product Usage, it might not be enough on its own.

#2 – Mixpanel

Mixpanel is my personal favorite, since it allows you to track what every single customer does in real time.

And that is the most important kind of data when it comes to product usage analytics since it gives clear answers to:

  • What are the most used features of my product?
  • Which page do users spend most of their time on?
  • What kind of different cycles do different segments of users follow?

And so on.

Mixpanel also allows you to engage with your users through the product like sending in-app messages.

But of course, just like every other product, it is not divine, and has cons.

For instance, it doesn’t have the background tracing feature that Google Analytics has, leaving you with ‘’during product usage’’ data only.

#3 – Amplitude

Amplitude is the second most-used product usage analytics tool on the market with over 40k users.

Think of it as the intersection set of Google analytics and Mixpanel.

It was designed to be a substitute for Google Analytics, which is probably why they have so many users, and is very similar to Google Analytics in many ways.

While not being able to show any data about the user acquisition, it’s almost as simple to use as Google Analytics.

In addition to the similar features, Amplitude shows more detailed information about what each user does while using the app, just like Mixpanel.

Do they click on the professional photos you paid so much for?

Or do they have problems finding a certain feature and spend a lot of time at the help center?

#4 – Heap

Heap, like Amplitude and Mixpanel, also tracks “events” including button clicks, video plays, scrolling, gallery views, and so forth.

What makes Heap different from competing products is that it analyzes everything, without you having to do set anything, you just need to ask for the report.

This also allows you to get immediate access to a type of data you didn’t need by far, while in other platforms, you would have to create a new analysis order and wait for a few months.

Well, big data comes with big responsibilities, such as a need for bigger storage space, which can cause additional costs.

I know I didn’t go into much detail about the tools. That’s because there is an article that digs deep into each tool in a comparative way, you can find the article here.

Conclusion

Product Usage Analytics, while being highly underrated compared to Product Analysis, is a crucial part of the product for its growth and survival.

It allows you to hear the most and least important features from the users themselves, without them speaking an actual word, through analyzing their actions while using your product.

And it’s not a difficult or time-consuming thing to do, though. There are a variety of tools that are built to help you, some of them being free, some others being paid but affordable.


Frequently Asked Questions


What is usage analysis?

Usage Analysis is analyzing how and how much your customers use your product to know if the customers are using the key features of your product and get that ‘’Aha!’’ moment.


What is product usage data?

Product Usage Data is the data you get from Product Usage Analytics. This data helps you determine the most valued and used features of your product through the actions of the users.


Why is analytics used?

Google Analytics is mostly used to analyze and evaluate a product, but it can also be used to analyze product usage.

Hilal Yıldırım

Hilal is the Creative Content Writer of UserGuiding, specializing in onboarding and growth. When she isn't writing, you probably can't find her: she could be anywhere, taking photographs on her motorbike.