DoorDash has rolled out three new advertising tools that use machine learning to help restaurant chains find and convert higher-value customers on its delivery platform.
Why it matters: Advertising is becoming a critical revenue stream for delivery platforms. As commission rates face regulatory and competitive pressure, ad products let DoorDash monetise its data without raising fees on restaurants or customers.
The new tools
Brand Interest Targeting shows ads to users whose order history suggests they are likely to try a particular restaurant. In lift studies, campaigns using this feature delivered an average 14% increase in return on ad spend compared to untargeted campaigns.
Average Ticket Size Targeting segments customers into high, mid, and low spending tiers. Restaurants can focus their ad budget on customers who typically place larger orders. Early tests showed a 35% increase in average ticket size and nearly four times the return on ad spend.
Brand Sales Growth Reporting benchmarks a restaurant’s sales trajectory against similar businesses over the past three months. The tool is designed to show whether advertising is driving growth or merely capturing orders that would have happened anyway.
The bigger picture
DoorDash joins Uber Eats and Instacart in building advertising businesses on top of delivery logistics. The model mirrors Amazon’s retail media playbook: use first-party transaction data to offer targeted ads that competitors cannot replicate.
For restaurants, the tools promise more efficient spending. For DoorDash, they represent high-margin revenue that does not depend on delivery volume.