Impression-level data is rapidly transforming user acquisition

There is power in granularity when it comes to optimising user acquisition.

At a time when a strong user acquisition strategy can be the difference between growth and stagnation, app publishers using advertising to generate revenue are relying on paid user acquisition (UA) to reach new consumers. As a result, an in-depth understanding of the cost to acquire each new user is the basis of a successful strategy.

Until now, attempts to calculate return on investment (ROI) and build lifetime value (LTV) models have mostly relied upon data based on averages, which are therefore less accurate and do not allow publishers to adapt as quickly as possible when required.

Optimising for acquisition

David Gregson, Product Manager at MoPub, a Twitter company, is part of a team creating solutions to address the most pressing monetization issues for mobile app publishers today. He believes that because a majority of ads are provided by ad networks, it is difficult to provide truly accurate impression-level data:

“Where others in the industry do provide network data, it's generally an aggregate even there. It's really the average CPM for a given network: you look at how many ads had been served by that network and you sum it up.

“Our goal is to provide an extra level of clarity for app publishers to understand how much revenue is actually attributable to a particular user.”

Gregson argues that only since the advent of in-app bidding has significant progress been made towards providing more  accurate data in real time, since it previously required  talking to a network after the fact, tying it back to the impressions. As he says, “it all got very messy”. Now, however, as in-app bidding gains traction, particularly in EMEA, which invested early, monetization platforms like MoPub have the ability to understand the value of each ad at the moment of impression. Consequently, they can deliver that information in real time, allowing publishers to adapt their strategy far more quickly and cleverly.

The primary use case for a solution of this kind is in impacting how publishers approach UA, since it allows them to accurately track whether the users they acquired ultimately delivered more value back to the business than they cost to attract. While Gregson notes that gaming and games publishers are among the primary beneficiaries of a system like MoPub’s, it has ramifications for other marketers as well.

Future trends towards accuracy

Accurate impression-level data is now effectively just table stakes for any publisher looking to succeed in-apps and on platforms. In order for accurate impression-level data to become industry standard, however, there are a number of trends that need to run their course. One, an overall industry move towards bidding, is currently in progress, though Gregson notes that there are those who will ultimately choose not to use it. Despite that, he notes the overall trend is positive:

“I think it's definitely taken a while for the industry to finally align on this. MoPub especially is finally seeing a lot of movement on it since the latter half of 2018.

“I think that there's a sort of snowball effect where everybody will eventually start moving to bidding. It's now an inevitability because what we see on our own side is that the yield for publishers is much greater.”

Another trend, one that MoPub is ahead of with its new product, is greater demand for transparency from all corners of the industry. While a walled garden approach has historically been beneficial to some of the bigger players, the majority of the industry has made a move towards less opacity for some time, and accurate impression-level data delivers that.

Gregson believes that as the quality of user data improves over the next few years as a result of the above trends, MoPub will be able to improve the precision of that data as a matter of course: “We have a particular field associated with the data that we pass to publishers around precision. What we hope is that more and more of the data that we pass, will have the exact flag in that precision field so that publishers can be more confident that it's exactly what they were earning.”

It’s a far cry from the days when a certain amount of fudging around UA was accepted due to the restrictions around, and limitations of, measurements. Now publishers are able to adapt their marketing strategies on the fly, as the real cost and return of acquiring new users becomes readily apparent.

Featured by The Drum