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.

What is Impression-Level Ad Revenue attribution?

Ad revenue attribution is how publishers can measure the profitability of user in-app actions and track the essential metrics related to ads  — Ad LTV, Retention Rate, eCPM Decay, etc.

Impression-level data has not been easily available, instead you had to rely on incomplete data based on large user segments that often leads to misreporting. Today, it is finally possible to get to the bottom of where your ad revenue comes from on impression level.

Impression-level raw data gives you the most precise information about how much each impression costs and, consequently, the LTV calculations are much closer to the real state of things. When you put effort into interpreting the data that is not random, you can understand what strategies work best in bringing you more users and more revenue.

When analyzing ad revenue sources it is also crucial to link all processes — from user acquisition to ad monetization — and glue data points coming from different sources into the big picture. Once you’ve identified your high-value users and your ideal target audience, you can capitalize on making that audience the focus of your campaigns.

How does Ad Revenue attribution work?

Ad Revenue Attribution is basically about dissecting your current user audience and determining what users are valuable and are worth of additional engagement. This data helps you optimize your ad decisions and create solid strategies for attracting your main focus group.

Spending on random or under-performing users is a waste of a budget and, therefore, those user segments should be weeded out sooner rather than later, clearing the way to understanding your high-value audience.

What DataCore Business Intelligence Solution Does

The increasing revenues reflect the value of the product, so it is a logical step for publishers to track and target high-value users, employing as many tracking parameters as possible.

With our Business Intelligence solution, DataCore, publishers who monetize with ads, can effectively track a variety of crucial metrics, such as revenue and eCPM (average cost per 1 thousand impressions), number of ad requests and ad impressions, number of fills (fill rate), clicks (CTR), Display rate, and Ad LTV.

Apart from those essential metrics you can also get statistics on ROAS (Return on Ad Spend), highest-paying user cohorts and eCPM decay. This whole set of data intelligence can be easily exported for further analysis.

Publishers are free to interpret the results on their own or use a third-party data tool for in-depth analysis. This ensures that the data is always under publisher’s control.

Top 3 Benefits of Using Ad Rev Attribution Powered by DataCore

Why do you need this solution? Here are three main benefits you will reap if you tie your monetization to thorough work with data:

Building effective LTV models
You routinely buy traffic and want to determine where exactly your revenue comes from and build ad LTV model based on accurate numbers. Since it is remarkably challenging to understand how much money each traffic source brings, once you do figure it out, it’s easy to pinpoint channels with high quality users and optimize ROAS (Return Of Ad Spend).

DataCore does impression-level analysis and, in addition, tracks metrics numbers that are not that common.

Let’s take an eCPM decay metric. It’s a metric that can be very useful — it focuses on price drop dynamics per each impression (the first impression price is usually the highest, the rest falls behind). With eCPM decay statistics at your disposal, you can determine how to limit the number of impressions for it to be the most effective for a particular device.

For example, if you see that impression prices get drastically low after a certain level/point in an app, you can stop spending resources on serving impressions at that point. Instead, you could, for example, introduce cross-promo and, thus, engage your users more effectively.

Identifying ad whales
One of DataCore’s major strengths is identification of ad whales for particular apps. Ad whales are 20% of users who bring you 80% of revenue.

You can feed that data about them into the BI tool. It is a sure way to further capitalize on an opportunity to find more high-value users. This data can also be used to create lookalike audiences for user acquisition campaigns in other channels (for example, Facebook and Appgrowth).

Revenue Deciles show the percentage (10%/20%/30%) of ad whales for devices and their respective revenue numbers.

Learning the exact impression prices
If you wish to know the exact price for each impression, you can predict them by using our algorithms. Now, if you use programmatic channels, the calculations are more accurate and efficient.

While networks and mediation companies only share aggregated data without specifying the price for each impression, programmatic channels deliver accurate impression numbers, which paves the way for more accurate predictions.

For example, if you sell traffic with BidMachine, the ad exchange part of Stack, you will have 100% programmatic demand and know prices for each impression. Apart from impression prices, with DataCore you’ll be able to understand how many new users you get daily from each media source and observe exact retention and life cycle numbers.

How to Start Working with Data

You can pull the data from several sources:

  • BidMachine’s ad exchange
  • Appodeal’s ad mediation platform
  • 3rd party ad mediation platforms
  • 3rd party attribution providers
  • 3rd party analytics system (such as Firebase)

We then feed it into Redshift’s data lake where it can be further analyzed via DataCore’s standard data dashboard or any 3rd party business intelligence platforms, such as Tableau or QlikView.

We want to make sure that publishers are in control of their data every step of the way.

In a nutshell, DataCore Ad Revenue Business Intelligence solution is a development of our unique system that is backed by the Customer Success team. This solution helps publishers address very specific needs of their business and, as a result, increase the profitability of both ad mediation and user acquisition.

The conclusion is simple: the more access to data you have, the more effectively you can work with it. Undeniably, data is as valuable as revenue. DataCore is a comprehensive platform designed to help keep everything on the pulse — being able to work with every piece of data and arrive at a place where your business thrives thanks to it. You can further use the attribution data to make informed decisions concerning UA.

If you’re already an Appodeal user, you have an opportunity to experience the power of DataCore. Talk about implementing Datacore to your account manager or reach out to support@appodeal.com.