Mobile App Analytics: What It Is and Best Practices

Mobile App Analytics: What It Is and Best Practices

There are many metrics in app marketing and there’s a lot of confusion towards which metrics we should use to analyze and monitor our app performance. Defining your key metrics or Key Performance Indicators (KPIs) for your mobile business, understanding trends and patterns or forecasting your app growth potential might not always be that easy. For this reason, we are introducing a Step-by-Step Guide to App Analytics, very useful to those who are starting in the mobile business.

What is App Analytics?

Mobile app analytics covers all topics related to mobile performance measurement: event tracking, conversion setup, performance analysis, trends and patterns monitoring, growth projections and revenue forecast.

To understand what app analytics is, we must identify the 2 main elements of  any mobile business: Marketing (or Promotion) and Product. The logic behind setting up your app analytics will take into account this division and will relate all pre-install metrics to the marketing team and post-install metrics to the product division. 

This way, Marketing will be mainly accountable for new users and overall user acquisition and Product will be responsible for monetization, app stability and user engagement. There are some cross-departmental topics and metrics involving all teams – in this case, we will need to define the mobile app analytics best practices we want to take when setting up your analytics roadmap. 

Anyway, keep in mind that post-install behavior is also a key element on acquisition so both teams should always work together.

Let us walk you through a Step-by-Step guide to Mobile App Analytics to understand what mobile app analytics is and how it should be set up for your business.

Step-by-Step Guide to Mobile App Analytics

We’ve got 2 main business lines in mobile  we need to keep an eye on when setting our app analytics plan: Marketing and Product. And as mentioned, acquisition will be related to marketing while all post-install behavior will be related to engagement and monetization within the product team.

On the acquisition or marketing team, we’ve got different activities like App Store Optimization, Content Marketing, Social Media and Community Management and Paid traffic acquisition.

On the developer side or product team, we’ve got analytics related to the product itself (app stability, crashes & ANRs), monetization actions (admon, waterfalls, IAPs, subscriptions) more related to user engagement metrics (user onboarding, signups, tutorials, ARPPU, DAU at D2, D7…)

Mobile app analytics best practices for Marketing and Product will need to correlate each of their efforts into 2 different types of metrics:

  1. User behavioral metrics – based on the scope of each action
  2. Revenue or monetization metrics – based on how user monetize

User behavior analysis respond to the scope of each action like for example, in the case of an App Store Optimization update, the number of visits, conversion rate percentages and installs uplift/ decrease after the action or the number of Impressions, CPMs, CTRs or tCPI for each ad network on the paid acquisition side.

Revenue or monetization metrics are defined by how users are monetizing after the action is taken. Here we include all revenue driven by our acquired users. In the case of paid UA, the revenue generated after d30 on a facebook campaign, or the revenue generated  after a better onboarding experience.

All these metrics will help us understand how our marketing efforts align with the business goals.

App Analytics for Marketing

We’ve covered the 2 types of metrics in mobile marketing analytics: the first type based on user behavior like CVRs, CPIs or Page Views and the second type of metrics, the revenue metrics, the ones explaining how users monetize, like LTVs, IAPs, sales revenue, etc.

To understand the key metrics and KPIs for Mobile Marketing we will follow the app analytics classification into behavioral and revenue metrics.

  • Primary metric to understand User behavior in Marketing: Daily Active Users (DAU)
  • Primary metric to understand Revenue in Marketing: Average Revenue per Daily Active User (ARPDAU)

Mobile marketing analytics is focused on Acquisition, on New Users. Thus, we should opt out from these marketing primary metrics the recurring or returning users and returning payers – as returning payers and users are more related to user engagement and monetization that are more related to Product rather than to Marketing.

In other words, the main KPIs for mobile marketing on the behavioral side are the DAU from New Users (Organic and Paid traffic) and on the revenue side, the main KPI is the ARPDAU – ARPDAU is the correlation between the Average Transaction Value and the Buyers Conversions. 

We will exclude from this metric the Returning Payers when analyzing marketing activities.

Secondary metrics in mobile marketing will depend on the traffic channel:

  1. Marketing activities related to organic traffic like App Store Optimization (ASO), Search Engine Optimization (SEO) or Social Media Management will have as secondary behavioral metrics installs from new users but you can also use another metric from early onboarding like organic signups and user conversion into payers from these new users, also known as the user churn rate.

Generally speaking, the impression-to-install conversion should be around 1 to 3%. Once the user installed the app, we will have conversions from 5 to 10%, so install-to-payer or install-to-early engagement conversion should be around 5 to 10% – but of course be careful with taking wrong benchmarks because they vary deeply from one business to another.

Feel free to keep reading about mobile ASO KPIs in our previous article where we describe more in-depth key aspects of this discipline. 

  1. Marketing activities related to paid traffic like Google Ads, Meta or Tik Tok Ads will have as behavioral secondary metric ROAS or eROAS (for the short-term efficiency) and LTV/CAC ratio (for long-term campaign efficiency) – Customer Acquisition Cost or CAC unlike ROAS does not reflect efficiency itself, it merely indicates the average cost for acquiring a new paying customer. That’s the reason why we use the LTV/CAC ratio because it compares the lifetime value of a customer to the cost of acquiring them.

If most of your revenue comes from new customers then you can probably rely on ROAS, but if a great share of your revenue comes from recurring purchases or subscriptions then your CAC is more valuable as well as LTV. 

We suggest picking the KPIs that are more appropriate to your business.

App Analytics for Product

We’ve talked about product and app development VS marketing analytics, when we take all post-install behavior related to engagement and monetization as well as metrics related to the product itself (app stability, crashes, etc.)

Following the division between behavioral and revenue metrics, we will classify Product analytics  into:

  • Primary metric to understand User behavior in Product: DAU at day 2, 5, 7, 30, 60… depending on your mobile business
  • Primary metric to understand Revenue in Product: Average Revenue per Daily Active User (ARPDAU) based this time on the overall conversions (including the Repeat Buyer Conversion) and the Average Revenue per Paying Users (ARPPU).

Secondary product metrics such as LTV, ROAS, ROI, etc. also need to be calculated using daily conversions as well as ARPPU making this analytics method valid for any business model.

On a Free2play model, the ARPDAU will be the correlation between the daily purchases and the ARPPU. On a subscription model, the ARPPU would be the average Price per Period and Pay Period Duration. This way the correlation between the price and the subscription duration plus the number of subscribers would give us the revenue value for our product.

Mobile App Analytics Best Practices

There are many tools and services helping you to track and monitor your app analytics. The idea behind mobile app analytics is to understand how your app is performing, identify trends and patterns as well as areas for improvement to be able to predict and forecast the app growth of your product and marketing activities.

We’ve distinguished some key metrics or KPIs for Product and Marketing and how to classify them. The main objective would be to align all these KPIs and secondary metrics with your business goals.

We understand as ‘business goals ‘ specific, measurable and achievable goals, easy to understand, to measure and to keep track of them, like for example, increase the impression-to-install conversion in the US by 1.2% or increase the DAU at D3 by 3%. These business goals must be realistic and based on data-driven decisions. It will help us understand how we are currently performing and forecast our growth opportunities based on our action plan.

All these business goals will be setup from the Product and Marketing team based on a previous analysis taking into account:

  • App performance
  • Benchmarks
  • Growth Opportunities & Areas for Improvement
  • Trends & Patterns Analysis

App and market analysis is fundamental to understand how users interact with your app, missed opportunities and growth potential to make data-driven decisions for your app’s success.

Feel free to reach us out in case you have any questions about this topic – we’re happy to help.

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