Uber Eats, the online food ordering and delivery platform launched by our founding customers, Uber, had an objective to drive scale and customer acquisition within a specific profitability target in their affiliate channel and chose to use Button Evolution™'s Actionable Intelligence to achieve these objectives.
Knowing that the lion's share of traffic in affiliate is dominated by loyalty publishers that offer rewards to consumers in the form of points, cash back, and other incentives, Uber was looking for deeper insights on how to spend smarter in these publisher apps and how the offers shown to users would impact their KPIs.
This is where Actionable Intelligence, the latest product in the Button Evolution™ suite, empowered Uber to run simultaneous multivariate tests across publishers showing users in different audiences different offers to determine optimal performance. These insights enabled Uber to identify the optimal offer to show users—to optimize yield for their objective of scaling user acquisition at their specific profitability target.
Based on Uber Eats' request, Button tested 11 different user offers (showing cash back discounts of 2% to 12%) simultaneously from March to April 2020 across Uber Eats' entire user base on Samsung Pay, by splitting users into 11 randomized audiences.
The optimal rate of 11% was higher than Uber Eats' original rate. Comparing test result of the optimal rate to the original rate, we saw:
For more on how these insights enabled Uber Eats to maximize scale while still exceeding their profitability target, download the case study today.
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