Analytics - 4 min read  - April 15, 2019

3 Ways Ad Revenue Attribution Scales a Mobile App Business

Tracing back the revenue each in-app ad delivers can feel like an overly-complicated task, but that doesn’t mean it should be ignored all together.

If you launch User Acquisition (UA) campaigns, at any time, and need to find your ad whales – those high-quality, high-profit users bringing in the dollars – your primary business goal should be one of two things: 1) implement an Ad Revenue Attribution tool; or 2) scale your current Ad Revenue Attribution strategy.

The benefits of attributing your ad revenue back to specific UA campaigns are many, but for this post we’re focusing on the top three.

Align User Acquisition and Monetization

Ad Revenue Attribution helps publishers trace and monitor the user journey from impressions to installs to whether or not a user is retained and turned into an active (regular) user. This path from point of acquisition to profit-generation and retention means that UA and monetization leaders can achieve greater results by working together.

Essentially, Ad Revenue Attribution serves as a bridge between the two functions. It helps to quantify Return of Advertising Spend (ROAS) and identify the most successful UA campaigns based on the Lifetime Value (LTV) of each user. This information gives monetization managers more to work with then just clicks and installs, and can be used to optimize the retention rate of users, especially the right (profitable) users.

Calculate and Optimize ROI

Calculating and optimizing the ROI of marketing campaigns is another big industry challenge. In fact, many are neglecting it entirely – with approximately 65% of mobile app developers failing to create a comprehensive plan to determine, evaluate and track it, according to BusinessofApps.

Many publishers measure the ROI of their marketing campaigns based on impressions. But since impressions don’t always result in profit potential, this approach isn’t optimum and can result in a false ROI calculation. A user watching 30 rewarded video ad impressions without clicking on any of them or without installing an app or a game is not actually bringing in profit. There are many unknowns that need to be understood. If a user installs an app, are they using the app on a regular basis? What makes users leave or disengage with an app or a game? What is the best time to initiate an ad based on unique user segments? What is the correlation between advertising and engagement?

Ad Revenue Attribution helps app businesses respond to these questions by using in-app analytics to drill down data all the way to the ad that first engaged a user.

When it comes to optimizing ROI, Ad Revenue Attribution can improve results by analyzing results from each ad network and offering the insights you need to choose the ones that fit your unique business needs. Facebook and Google are – not surprisingly – among the top, with their high rankings in low click-to-install ratios and retention rates. But it’s important to know that there are other options and that working with more than a couple will maximize your revenue.

Identify and Acquire More Ad Whales

The users with the highest Ad LTV – a major component of Ad Revenue Attribution – are identified as ad whales. These are users who go beyond a click or an impression to the act of installing an app and using it on a regular basis. They usually account for the majority of ad revenue.

Once ad whales are identified they can be multiplied by creating “lookalike” audience campaigns designed to find more of the same high-value users. These “lookalike” campaigns use insights such as optimal ad frequency and ad location in order to influence user experience and increase retention rates.

The cautionary note here is that accurate Ad LTV measurement is difficult to do. This is largely due to the lack of data transparency in tracing ad revenue back to each individual user. Ad networks have been notoriously uncooperative in releasing this type of data, and building the technology to track down the necessary information in-house requires very significant investments in learning how every ad network operates. But this will hopefully be less of a challenge in the future as publishers and brands begin to work more closely together to demand increased data transparency.

To get around this problem, publishers can partner with services providers like Stack. Our Ad Revenue Attribution tool predicts Ad LTV by monitoring the actions users take after their initial engagement with an ad.

Takeaways:

  • Any business using mobile ads to acquire users needs to be doing Ad Revenue Attribution in order to maximize their ROI.
  • Ad Revenue Attribution serves as a bridge between UA and Monetization to increasing efficiency and optimize profits.
  • Ad Whales – the customers who drives the highest profits – are identified and multiplied through careful monitoring and tracking of Ad LTV.

Interested in learning more about how you can take advantage of ad revenue attribution using Stack? Find out how in this post.

Gergana Pomerantz
External Comms and Content Development

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