Analytics - 5 min read  - September 2, 2019

Turning Mobile App Data Into Actionable Insights

How do you work with extensive and complex business intelligence data without losing control and sight of the vital metrics? Taking advantage of your mobile app’s analytics and extracting the profitable insights to your immediate benefit is not an easy feat.

If your team is ready to align user acquisition and monetization data to pursue that goal, the first step is to adopt an analytics tool that enables you to do that with efficiency. DataCore is an actionable intelligence solution that was created to facilitate work with your app’s data and turn insights into profits.

Mobile data is so valuable and so abundant. Sometimes it’s challenging to gather all the data points in one place and make the most out of it by focusing on the right metrics.

That is why at DataCore we provide access to your data in a very simple manner with a customized dashboard. That way your analytical priorities are highlighted and never overlooked. And you don’t need to struggle aggregating data from other platforms and third-party solutions yourself.

Bidding Farewell to Disparate Data with DataCore

First things first, our team chooses the best platform to work with data based on the price to quality ratio. The starting stage can take a lot of work and time, so we take care of the preliminaries and ensure a quick start by:

  • setting up the platform,
  • building a sustainable BI system,
  • creating a customized dashboard for your specific needs,
  • organizing syncing with mobile attribution and third party out-of-the-box analytics solutions.

Our solution takes care of all the jumpstart hassle to help you become independent in your journey to structurized and more effective analytics. Moreover, by syncing all your solutions that provide analytics you align monetization and user acquisition data. The more data you can sync, the more insights you can obtain.

Since each team’s needs differ, our team can build a customized business intelligence dashboard specifically for you and help streamline user acquisition for optimal results. Through it, you can have your data in one place and directly work with insights that can be turned into action.

Ad Revenue and Users by Date is one of the basic metrics you can track in DataCore dashboard; it gives you a quick overview of ad revenue generated and new users for a given time period.

We know that tracking various metrics is a standard way of evaluating how well your app performs. All of them seem important, but are all of them relevant for your app success? It’s more effective to focus on those that answer these questions:

What users bring you the most money? Via what channels?

What cohort of active users turning into passive and why?

How well are your users engaged?

3 metrics that drive actions in DataCore

What are some metrics that drive action? Based on our experience of working with publishers, we chose the ones that may be overlooked or not properly looked into. However, if all of these metrics are monitored regularly, they can provide extremely useful insights.

Ad LTV

LTV prediction is traditionally taken into account, whereas Ad LTV is overlooked for various reasons. Ad LTV Prediction deals with trends for user retention, ad impressions and estimated revenue from all networks for a given cohort of users. Ad LTV can be hard to calculate, because ad networks and demand partners do not always provide eCPMs on the user and impression level, but rather scatter data by GEOs and platforms.

That is why it is best to work with programmatic demand sources that provide precise impression-level data (Appodeal and BidMachine provide data at the impression level). The more impression-level and user level data a publisher possesses, the more accurate and wholesome Ad LTV picture becomes.

Looking closely at Ad LTV gives us an understanding of where the primary source of revenue comes from. For example, if you see that you last 3 campaigns attracted more female users and the Ad LTV of these newly acquired female users is $1.50 higher than that of male users, you might want to target more female users during your next UA campaign.

Ad LTV is key to identifying ad whales and refocusing your campaigns to target high-value users. Carefully measuring ad revenue gives you a good understanding of ROI (Return on Investment) and helps channel your efforts into the traffic sources that bring paying users.

Track Ad LTV data conveniently broken down by install dates for selected periods.

eCPM Decay

How do you make sure that users in your app continue interacting with ads? eCPM decay metric helps monitor eCPM tendencies. eCPM, or Effective Cost Per Mille, is a vital performance metric for measuring an app’s success as it gives you an idea about how much money users bring for each 1000 impressions. Usually, when one user engages with the first ad, the eCPM is at its peak. In a user journey the first ad is always seen by a user, however after the 4th ad onwards users tend to stop interacting with ads. That’s when eCPM starts declining.

eCPM decay is inevitable for a variety of reasons — from repetitiveness of ads to low quality of creatives. For example, for the first ad that led to app install, advertisers will pay $7, which results in a higher eCPM. For the ad that is 8th or 9th in the user journey where they are reluctant to interact, advertisers will pay $2, which results in a lower eCPM.

The best tactics to keep eCPM steadily growing is to focus on the quality of the first impressions that user will see in your app and to lower a number of impressions for users that stop interacting with ads after they’ve seen a certain number. 

Watch out for correlation between eCPM and number of impressions.

LTV by OS versions and models

This metric might seem less obvious compared to the ones covered above. But the reality is that with the frequency of OS updates, it’s important to track how ads perform in various OS versions across devices. Traditionally, more recent OS versions generate stronger numbers. So it is advisable to track how well various ad formats and campaigns perform across devices and OS versions. For example, if you see that performance for older OS versions on an iPad 5.1 shows low numbers, consider reducing the number of ads you want to serve for this OS version.

Ads usually perform better on devices with more recent OS versions.

Apart from these metrics, you can also track various others, focusing on both engagement and retention:

  • Impressions and Session Performance Metrics,
  • Retention Rates (per period, median and average),
  • Mobile Attribution Reports that consist of Revenue by Media sources, Attributed Devices Count for the particular app and date, LTV by media source.

Our team is here to add and customize any metric or filter that you particularly want to see in your dashboard. 

Syncing data for even better actionable results 

You can easily integrate with DataCore if you use any mediation, monetization and user acquisition services and start working with data from across all platforms. And if you’re using our other products like Appodeal, BidMachine or AppGrowth, the integration is even faster — it is automatic. 

The importance of aligning all data points and analyzing them in relation to each other cannot be overestimated. For example, BidMachine in-app header bidding results give us access to exact impression prices. That information can be used to set more accurate price floors. Better targeting is possible with AppGrowth — we collect data via machine-learning, further analyze the most profitable user base and identify lookalikes. 

Access to accurate and relevant data insights has helped in shaping successful analytics strategies for many mobile app businesses. At DataCore we made it our passion to align the disparate data to make it work more efficiently and translate into real results. 

Talk to us about how DataCore can address your business needs here.

Ekaterina Kupidonova
Product Marketing/Content Manager

Analytics - 5 min read

Ad Revenue Attribution: How to Take Advantage of Tracking Impression-Level Data

If you want to understand what your ad revenue is composed of on an impression level and predict LTV as accurately as possible, you need to use a sophisticated Ad Revenue attribution tool in alignment with your app growth strategies to make it happen.

Analytics - 5 min read

Ekaterina Kupidonova