New: Scaling Contextual UA Campaigns to Apps With Similar Audiences

Dataseat’s Inventory Discovery module just got a unique upgrade, giving our advertisers exclusive access to next-level insights into where to spend to best deliver on their performance goals.  

Meet Dataseat’s newest addition: the Cross-app affinity tool. It lets app marketers find evasive top-performing inventory across 50 billion daily impressions. We are expanding your targeting lists with apps where your users actually spend their time, efficiently scaling campaigns beyond similar-category apps.

Lack of behavioral data in the ID-less mobile world is forcing advertisers and ad tech vendors to look at contextual targeting, applying different principles to reach similar goals. 

As the IDs on iOS fade away, advertisers need more out-of-the-box opportunities to boost efficiency of contextual targeting for UA. 

This is where the data.ai-powered Cross-app affinity comes into play. For an advertiser, it opens up the black box with insights on where your target audience is spending their time – and where to find more of them.

The addition of data.ai’s Cross-app affinity is the latest development in Dataseat’s long track record of leading the contextual user acquisition game. Our robust in-app inventory discovery (enhanced with the recent app genre/subgenre taxonomy) is powered by machine learning and reinforced by our long-standing expertise in contextual campaign measurement and optimization.

Scale mobile campaigns to where your audience spends time

Once we’ve got a publisher app target list and know the apps where your user acquisition is effective, obviously we want to scale UA beyond those few publishers/apps.

Expanding the target list can be hard. A more basic and widely used approach is using app categories as a guidance for selecting more target apps to test, and then evaluating performance in test campaigns.

The new approach, powered by cross-app affinity scoring is quite different: instead of looking for similar apps, we can go deeper and look for apps with similar audiences. 

Finding apps with audiences similar to your app’s known effective publishers helps you scale user acquisition and expand your target list.

Dataseat lets UA managers look across the whole pool of inventory, including non-similar app (sub)genres, finding the apps that your audience uses, and targeting those (sometimes topically irrelevant) publisher apps to reach the desired audience.

This approach allows us to go beyond targeting “any” user in a similar context – to targeting a similar user in a similar context, or targeting a similar user in a different context – thus targeting campaigns to a bigger available audience with a higher degree of confidence.

Finding the evasive UA top performers: Cross-app affinity

This essential step of finding other apps frequently used by the same audience is achieved by utilizing cross-app affinity scoring provided by data.ai.

Cross App Affinity gives you insight into how likely it is that users of app A will also be interested in app B.

For an advertiser on Dataseat, this means that once we have established a shortlist of top performing publisher apps, we are able to find more of top performers quickly and with high confidence. 

More importantly, looking beyond the “typical”  target apps gives Dataseat advertisers an edge in finding relevant inventory which may have been less obvoius to their competition. – Rich Jones, Product Director, Dataseat

Here is a sneak peek of how the cross-app affinity data looks on Dataseat’s DSP UI:

What happens next with the identified inventory?

After the similar-audience apps have been identified, we add them to the testing queue. Good news here is that Dataseat is able to further test inventory not only for Android apps but also on iOS, using SKAN at its advantage and actually getting actionable data to analyze publisher apps efficiency and feed the ML models.

Explore		Exploit
The newly-found apps with high user affinity enter the Explore phase of Dataseat’s Explore-Exploit cycle. We will track inventory performance, identify high-potential publisher apps, and inform further UA decisions with data. The campaigns are also used to train ML models for further steps.		Depending on the inventory performance, we remove certain apps from targeting and move strong apps to the following Exploit phase. At this stage we will also apply machine learning and creative testing to maximize performance.

Conclusions for a mobile UA manager and expected impact 

Altogether, Dataseat’s ability to target deep (sub)genre and expand supply search beyond typical app categories gives UA managers the competitive advantage of precise in-app targeting and reaching more users at scale – thus accelerating campaigns and saving UA dollars.

Cross-app affinity is a powerful and underused tool for finding effective spending opportunities and acquiring quality app users. For Dataseat advertisers this gives them an upper leg in competition as long as they are quick to target the freshly discovered apps. 

On the Dataseat side, manual setups combined with ML models let us quickly and confidently test and either stop UA campaigns or scale them to more apps and maximise efficiency using custom ML models.

Let’s talk about contextual campaigns!

Dataseat is the transparent privacy-ready contextual mobile DSP, the longest-standing expert in SKAN and one of the early partners for Android Sandbox. 

We are open to talk. Let’s discuss your case and think together of a solution to make contextual in-app advertising work for your particular apps. Get in touch with Dataseat experts.