Omniata BlogJuly 29, 2015

Implementing Basic App Analytics & Metrics

After defining your data vision as highlighted in the previous post, it's time to enable some basic metrics in your product. These metrics provide an overview of your product’s health.

While you are focused on getting your product out the door, you should spend some time integrating basic industry standard metrics in your product as a means to gain high-level insight into your user behavior, product, and general business model. These metrics can be obtained easily by integrating SDKs provided by most of the app analytics tools available today. As with any analytics implementation, it is key to think about what are the performance indicators (KPIs) that are most important for your app and business model. The metrics we dive into here are just the beginning ones for you to think about.

How to look at the metrics

A good way to look at these metrics is on a daily, weekly, and monthly basis on a timeline. Furthermore, depending on the metrics, they should be filtered by:

  • Acquisition Source
  • New vs Returning Users
  • Country
  • Language
  • Device
  • Platform
  • App Version
  • Device OS Version.

Below we will review these basic metrics and highlight their importance.

User Acquisition

The acquisition metrics provide insights into the channels that are driving users to your app or website. These channels could be organic, paid ad campaigns such as Google Adwords or Facebook, cross-promotion campaigns, emails, referral, or any other channel specific to your product.

The common acquisition metrics to track are:

  • Downloads
  • Ad Spend
  • Cost Per Impression (CPM)
  • Cost Per Click (CPC)
  • Cost Per Install (CPI)

These metrics will tell you how your app or website is finding users, and how much is it costing you. Please note that the true campaign optimization should be based on ROI, not CPI. We will cover this in a subsequent blog post.

First Time User Experience

The first time user experience plays a critical role in converting a new user to an active user who will engage with product and monetize in future. These metrics, also called as activation metrics, are generally measured as funnels of all the critical paths involved in user activation.

A basic example of such a funnel would be:

  • App Open -> View product intro slides -> Click on Sign up -> Enter email and password -> Action inside product

Similarly, for a game:

  • App Open -> View Intro screen -> Tutorial Step 1 -> Tutorial Step 2 -> … -> Tutorial Complete

It is critical to optimize the funnels and remove all the points where user drop off in the first time user funnel.


The basic user metrics lay the foundation for advanced metrics required to get deeper insights into user behavior, and are necessary to understand how your users are using the app. The most commonly measured usage metrics are:

  • New Users
  • Returning Users
  • Active Users
  • Number of Sessions
  • Average Session time

As mentioned above, you can get deeper insights by filtering the information. For example, you can split users by Country, Language, Acquisition Source, or Platform.


Retention metrics are arguably the most important metrics because highly engaged users generally monetize at much higher rate than non-engaged users. A baseline start is to track Day 1, Day 2, Day 3, Day 7, Day 14, and Day 30 retention of users.

Retention is viewed in a cohort table with each cohort corresponding to the acquisition date. The trend helps you identify if your app’s retention is improving over time.

A sample cohort looks like this:


These metrics tell you how much money you are making, and from whom. Based on these insights, you can take action to improve your monetization methods by optimizing your product.

The most common monetization metrics are:

  • Life Time Value (LTV)
  • Revenue
  • Conversion Rate (if freemium model),
  • Number of Paying Users
  • Average Revenue per User (ARPU)
  • Average Revenue per Paying User (ARPPU)
  • Number of repeat purchases
  • Number of first time buyers
  • Number of repeat buyers
  • Average order value (ecommerce product)
  • Average value of (ecommerce product)
  • Number (and %) users with items in cart (ecommerce product)
  • Items purchased by category (ecommerce product)
  • Renewals (subscription based product)
  • Renewal rate (subscription based product)
  • Cancelled subscription (subscription based product)

Apart from these metrics, the purchase funnel plays a very important role and should be tested and optimized to maximize revenue.

A sample purchase funnel can be:

  • View Item -> Save to Cart -> Opencart -> Review -> Enter purchase Info -> Verify Order -> Purchase


The Table below summarizes the basic metrics:

Going beyond basic metrics to custom metrics

All said and done, these metrics only provide you a very high level of visibility. The next step in your data journey is to start thinking about custom metrics. We will begin discussing this in our next blog post.