Food delivery company DoorDash says personalized restaurant recommendations based on AI are seeing a significant lift in orders, compared to regular recommendations based on popularity.
In an interview with VentureBeat, DoorDash product manager Jimmy Liu said customers who saw personalized recommendations on average “were over 25 percent more likely” to place an order versus people who saw the most popular restaurants in their area.
We talked with Liu on the eve of the company’s announcement today that it’s rolling out these machine-learning based recommendations to all of its users, after testing it on increasing percentages of its customer base. Millions of users have already seen the recommendations, the company said.
Liu said the 25 percent lift from recommendations came specifically from email campaigns. Machine learning (ML) based recommendations made within DoorDash’s app saw a lower lift on orders, Liu said. That’s logical, he said, because if someone is already within the app, they are already showing an intent to order — and so getting an additional lift from recommendations is comparably harder to do than for email, where someone may not be actively searching. Above: DoorDash now provides real-time location of their delivery person The results come six months after DoorDash announced […]