..here is what actually does work.

In this episode, we explore the limitations of contextual targeting in mobile advertising. While matching ads with relevant content sounds promising, only past purchase behavior truly predicts conversions. I’ll break down why self-attributing networks that leverage purchasing data perform better and how to prioritize these networks over context-based DSPs.

Contextual targeting in mobile sounds great in theory because your app is showing up in apps that are relevant to your audience. You could be showing up on their Twitter feeds, you could be showing up on news articles relevant to them. Certainly, there are DSPs and native content networks that treat this as a USP.

Does this lead to great performance? Here’s the truth: context is a very poor predictor of performance. Related content or interest does not mean that users will actually purchase. The only predictor of performance is past purchase behavior because while context captures interest, past purchase behavior captures the ability and willingness to spend.

I may be interested in something, but that does not mean that I’m willing to spend money on it. Therefore, you should be looking at contextual traffic, like DSPs, on native content ad networks only after you’ve tapped out networks that lean on purchaser data, like self-attributing networks.

BEFORE YOU GO

I have a very important favor to ask, which as those of you who know me know I don’t do often. If you get any pleasure or inspiration from this episode, could you PLEASE leave a review on your favorite podcasting platform – be it iTunes, Overcast, Spotify, or wherever you get your podcast fix. This podcast is very much a labor of love – and each episode takes many many hours to put together. When you write a review, it will not only be a great deal of encouragement to us, but it will also support getting the word out about the Mobile User Acquisition Show.

Constructive criticism and suggestions for improvement are welcome, whether on podcasting platforms – or by email to shamanth@rocketshiphq.com. We read all the reviews & I want to make this podcast better.

Thank you – and I look forward to seeing you with the next episode!