10 Steps To Get You Started With Behavioral Analytics

The core of behavioral analytics is events. Events describe any action a user can perform in your application (like opening the app or creating an account, for example) or any activity associated with the user (like push notifications).

Sending optimal event data to your analytics platform is the single most important step toward understanding how your users are engaging with your product. If you’re too hasty in instrumenting your analytics you may never get the full value of your data.

Follow these 10 steps to start off analyzing user behavior the right way.

Step 1: Define your business and analytics goals

What type of company are you? What does your company care about? What kind of metrics and insights do you want to get from your analytics? What experiments will you want to run in the future? Depending on what stage of growth you’re at, you may focus on measuring onboarding funnels, retention, conversion, revenue, and more.

Step 2: Think about what events correspond with your business goals

It’s great to be able to track all the data you want, but if you start tracking everything without thinking about what value the data provides, you’ll quickly find yourself unable to sift through all the noise. Instead, think specifically about the critical paths that a user can take–that is, the sequence of actions a user can do, which aligns with the app’s core experience.

Example: Suppose you have a gaming app. A critical path in the onboarding flow for the app could be broken down into four distinct events: user opens app >> user registers >> user verifies account >> user completes tutorial


When starting out, make sure to track only the events that are essential to answering your business and analytics goals. If you need to, you can always add more events later.

Step 3: Organize your event taxonomy

Keep track of your events, event properties, and user properties in an easy-to-read document for your team’s reference.

Download our sample ‘gaming’ app event taxonomy.

Step 4: Understand how users are being identified

Most analytics platforms require you to configure some kind of identifier–a username or email, for example–in their mobile SDKs or HTTP API for keeping track of unique users. This lets you match data from multiple devices and sessions to one user. Because of this, it’s important to make sure the user ID is set to something that will not change.

Another important thing to note. Most analytics platforms count unique users when they ‘see’ a new device or a new user ID (if the user is signed in). A challenge arises when a device ‘anonymously’ logs an event that was actually performed by a user already in the system. Amplitude solves the challenge of attributing anonymous events to the right users by using the ‘amplitude_ID’ identifier.

Step 5: Decide if you need cross-platform instrumentation

If you’re tracking data from mobile and web, iOS and Android–should you tie all your data together or keep them separate?

The answer to this question depends on your application itself. If you’re expecting user behavior to be different across platforms, you’ll want to know how each platform performs independently of the others; cross-platform instrumentation probably won’t be a priority.

If you want to understand user behavior holistically, irrespective of how they act on certain platforms, make sure that your analytics solution can do cross-platform instrumentation. Grocery shopping app Instacart is an excellent example of a product that utilizes cross-platform tracking; Instacart’s users span both mobile and web.

For more information on deciding cross-platform instrumentation vs. separate platform instrumentation, check out this article.

Step 6: Establish the ‘Minimum Viable Instrumentation’

Once you’ve spent some time thinking about how to set up your analytics and organizing your events, it’s time to start accessing some basic app metrics. You should now integrate your analytics solution’s mobile SDK and/or HTTP API and assign your user IDs.

Step 7: Track your events

Start tracking the events you brainstormed in Step 2. You don’t necessarily have to track every action possible in your app, but do make sure to track events that are key steps in onboarding, conversion, and retention.

Step 8: Set user properties and event properties

Assigning user properties and event properties can give you deeper insight into the behaviors your users are exhibiting as they engage with the app.

A user property describes attributes of an individual person using your app (e.g. age, gender, location). An event property describes a property of an event (e.g. how long someone performs the event).

Example: Going back to our gaming app example, here are some examples of user and event properties that we can set up for our onboarding flow.


Step 9: Check your instrumentation

How do you know if you’ve instrumented everything correctly? Use a test device to progress through the app. If you can view your analytics in real-time, you should be able to see your device firing events at each step. Be sure to check out these 10 Pitfalls To Avoid When Instrumenting Your Analytics. Once your test data works, it’s time to start sending live data.

Step 10: Understand user behavior

You’re all set! It’s time to slice and dice your data, create cohorts, run experiments, and see how users are engaging with your app.

Getting Started with Behavioral Analytics CTA