Currently the vast majority of mobile app advertising is used to generate new installs. At the same time, for some of the most successful revenue models, a small fraction of the most active users generate the bulk of the revenue. Free-to-play games are a good example of this model but there are similar in-app purchase driven schemes in other categories. Whilst a user is still very engaged with an app it’s likely that the most cost effective way to increase their spend is within the app. However, if an existing user stops using an app regularly ,then might there be more value in re-engaging users than acquiring a new user?
It’s an interesting prospect that requires analytics integrated with the ad networks across a large population of devices. An article by Peter Hamilton, who happens to be the CEO of a company offering (at least part of) such a solution, suggests this approach is already working well for early adopters. Although skepticism about the claims of someone who is trying to sell a solution is healthy, a shift towards a cost-per-action (CPA) advertising model rather than simply cost-per-click (CPC) or cost-per-impression (CPI) would be significant for mobile developers.
The main difference with CPA is who takes the risk in the relationship. The CPI model places almost all of the risk with the advertiser. The CPA model pushes all of the risk to the publisher (the person displaying the ad). Finally, the CPC model shares the risk more evenly between the two.
Rates for the different types of ad vary accordingly. Impressions are usually sold by the thousand with prices typically varying from 10s of cents to a few dollars. Single mobile clicks (we should really call them taps) are priced anywhere from a few cents to just over a dollar depending on keyword and/or demographics. On the other hand, actions have higher rates than clicks but are not very common currently.
For developers looking to tempt users back to an app to make another purchase, the CPA model is ideal. A decent fraction of the in-app purchase price can be offered to the ad publisher and a profit from the transaction is guaranteed. The only real risk is that ads will reach users that would have purchased anyway and the timing of the purchase has simply been shifted. This is highly dependent on the ability to target users who have become inactive, rather than just any users. This means that integration with in-app analytics is essential. The other side of the relationship has less clear benefits. Developers showing in-app or mobile web ads with no guarantees on their income. If ad inventory is otherwise unused or actual rates in practice are showing a better average than other models then this could become more popular. Another usage may be in genuine cross-promotion, such that two apps promoting each other have more balanced risk and reward.
Even if the ad payment model does not shift to CPA, the necessary tracking technology to match ad clicks up to in-app actions is potentially valuable to developers. It should enable more accurate measurement of the return on investment in any attempt of re-engaging users or increasing the engagement of existing users. Being able to measure the impact of individual campaigns and alternate creative content separately can allow developers to make multiple simultaneous experiments. Splitting out the purchases that are driven by ads to existing inactive users versus those made organically by new users and existing active users can inform decisions about where to focus future efforts at increasing revenue.
If you are building an app and are looking for more insights, here is an article on User Retention you might find useful.