What Product Managers should know about Product Analytics
This article was originally published in my newsletter The Growth Weekly.
If you have any questions on product growth, don’t hesitate to reach out. And please let me know what you think about this article.
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Digital Product Analytics
So, last week we were talking about retention as a very big driver of product success. But before you can do something about your retention rates, you’ll have to be able to measure them.
Coming from web analytics myself, getting into product or app analytics was daunting. The amount of tools available on the market is enormous and they are very fragmented. In order to possibly help you out on this, I’ll outline some of the tooling categories you might need.
Behavioral Analytics
The first thing you’ll want to do is knowing what your users are (not) doing. Behavioral analytics will be able to show you just that. There’s a lot of tools that you can use to do this, but before you go around shopping, you should set up a data taxonomy.
It’s one of the most boring jobs in the world, but it really pays off to do this. Give a name to every screen, event, object or user property within your product. For example, this is the one Twitter used:
After this, you can decide on tooling. I see most people use either Firebase Analytics and Google Analytics for Firebase. Mainly because they’re free. Google has been moving its mobile apps analytics from Google Analytics to Firebase and will continue to do so. There’s still some friction to overcome (e.g. in limits of parameter reporting etc.) but for a free tool, this is a great starting point.
However, the tools I greatly advise you to give a try is Amplitude or Mixpanel. These are product analytics tools that are much more adapted to the current needs in event tracking and cohort analysis. They give you a lot of freedom in how you set up your event tracking and run your querying.
Amplitude also has a cool guide on mobile analytics:
You can of course build your own product analytics by logging events, warehousing and visualizing data through other tools. It’s not something you should put time and effort in as long as the above tools can help you out at a reasonable cost.
If you decide on doing this, here’s an awesome article from Samson Hu, who built up product analytics at 500px.
Attribution
If you’re running campaigns to acquire new users, another thing you’ll want to know is how these different channels and campaigns are performing.
This is where attribution tools like Adjust, Branch or AppsFlyer come in.
It’s a lot harder to attribute app users to a channel than it is for website visitors because the app stores are in between the install and the channel. So mainly what these tools do, is tracking the app store url clicks and then matching them to new users.
You could solve this problem by installing the SDK of the network you’re using (e.g. Google Mobile Ads SDK, Facebook SDK, …) but it’s not really a scalable option in the long run.
So when choosing an attribution tool, make sure they have the right networks they partner with. Built-in attribution features in Google Analytics or Firebase don’t work with the Facebook network for example.
Also important in this decision is if and how they handle (deferred) deep linking. This allows you to send people directly to a certain place in the app. And if they don’t have the app yet, deferred deep linking will send them to the correct app store first before bringing them to the right screen.
Qualitative Analytics, A/B Testing, …
And then there’s all the other categories. I’m not going to go into these right now, but if you want me to, please let me know.
- Qualitative Analytics to help you get even closer to your customer by making heatmaps, session recordings. (e.g. Appsee)
- A/B testing to test different versions of your app. (e.g. Apptimize)
- ASO tools measure your app store positions for important keywords or categories (e.g. AppAnnie)
- Performance to see whether your app crashed, runs slow…
- Tag Managers help you send data to the different tools you need it in. (e.g. Segment, Google Tag Manager)
- Dashboards that gather data from different sources and showing the bits a team or person needs.
- Marketing Automation that either feeds of your existing event tracking or needs its own.
Everyone gets data!
The danger that lies in this complexity of tools is that you’ll have one go-to data person or team. They specialize and ‘own’ the data. Once your data infrastructure is somewhat in place, it’s a good thing to put some effort in getting data (knowledge) to the rest of the team.
It will be an ongoing effort but in the end it will make sure people can make better decisions with more confidence. There are some great articles on this subject linked below:
What’s next?
Phew 😅 Managed to get through all of this?
I’d love to get to know what you think about this and what subjects you want to read about more!
Next week, I’ll talk about growth accounting and modeling.
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