That’s the Tea Session 3: How to measure the impact of your mobile marketing

Our first virtual conference was a huge success, with over 950 experienced colleagues sharing the latest trends, challenges and opportunities in the mobile growth realm. Here's the session that will lead you out of the measurement darkness.

By Ben Sack, Head of Polarbeam’s customer org and Jason Conger, Head of UA at Wooga

Even now with all our access to data, it’s a tricky business understanding the outcome of our mobile marketing efforts and if campaigns are performing well, but figuring out how you’re going to measure ROI once we lose the ability to target as we do now, is a whole different kettle of fish. Like other facets of the industry, user acquisition experts’ mindsets will soon have to change to stay ahead of the curve and a top tip that came out of this session is knowledge sharing between teams will become vital. Luckily for you, Jason and Ben in their session unpack three strategy model options you can consider implementing in the future, plus Jason spills the tea on how Wooga measured organic installs from a TV Campaign – really useful stuff. Here are the main takeaways:

  • Some channels are easier to measure with MMPs and looking at direct ROAS, but to measure the impact of lots of your mobile marketing, you’ll need to work closely with your data science team to isolate different variables. According to Jason, your DS team will be your new best friends.
  • After the changes from iOS 14 set in and targeting is broader, the mindset of UA teams will have to change to become more experimentative. The direction the UA teams are headed towards is one where other teams already are – they’ll have to learn from what organic teams had to prove. Knowledge sharing between teams will be vital and you’ll need to take the data you know and look at it at an aggregate level.
  • When it comes to measuring organic installs from a TV campaign, Jason acknowledges there are a number of challenges to overcome; it’s not possible to perform a standard A/B test, it’s too optimistic to attribute all organic installs to the TV campaign and you can’t remove the average level of organic installs due to seasonality & user acquisition efforts that impact installs. But you can use your data science team to predict the future baseline organic installs by using the past data to break apart the paid portion from the organic.
  • When we lose the IDFA, decision making will become very difficult for the day to day operations of the UA manager and for sorting out the ROI of paid UA efforts to allocate monthly budgets and manage the growth of your business. When your targeting becomes very broad you lose the ability to do LALs, custom audiences, ROAS targeting, exclusion lists, etc so you will have to use (with difficulty!) your creatives as a lever for finding different types of users. You’ll have to condense your campaign structure using country/language in LTV buckets or by Region/Language and communicate to the networks with the Conversion Values which combinations are successful. Lots to think about but a creative tip is changing your design approach – don’t create thirty iterations, create with a target in mind. 
  • The three main strategy models you can think about to analyze/action/measure your ROI and marketing decisions in the post IDFA world are Aggregative (likely to be the most popular using aggregated data – analyze performance based on time series, user-agnostic performance using data that’s available rather than assigning individual trackers), Deterministic (based off of actual data – Use opted-in users, whose full data you have access to, to make decisions and predict ROI) and Probabilistic (logic/algorithmic-based – Use logic and proprietary algorithms to create predicted return on ad spend (pROAS). 

Watch Jason and Ben’s discussion and download the deck:

About Esther Rubin
Esther has worked in mobile marketing for years, writing for hi-tech companies and game & app developers. She's British but doesn't know Mary Poppins, before you ask.