New Doordash Rating System
Last updated December 19, 2025
Starting November 2025, Doordash moved over to more of a reaction-based rating system predicated on three key new changes:
- Moved over to a like/dislike/love emoji-based rating for users instead of a five star system
- Rolling in improved tag selections
- Adding more item-based reviews
Superorder has built the following updates to be able to handle Doordash's new system
Filters Changes
- To accommodate both the 1-5 based rating system and the reaction based system, we’ll be rolling out the following mapping between the two systems
- Love Reaction: 5 Star
- Like Reaction: 4 Star
- Downvote Reaction: 1-3 Stars
Average Rating Changes:
- To be able to process a consolidated view of average ratings across platforms and rating systems, we’ll use the following calculation: average calculation will be a weighted average of reviews with the following mappings:
- Love Reaction: 5 Star
- Like Reaction: 4 Star
- Downvote Reaction: 2 Stars
OSAT Changes:
- We’ll be converting the OSAT definition to be (5 star review count + love review count)/ total review count to adjust across platforms and ratings systems
Review Template Changes:
- For review template automations, the star rating filters will use the same mappings as for filter changes.
- We will convert the “With Comment” option to be “With Comment or Tag”
Inbox + All Reviews Page Changes:
- Within the inbox and all reviews pages, users will be able to see the like/dislike/love-based rating as well as the tags and item-based reviews all within the existing view of the review
- For the rating, the like/dislike/love-based rating will be displayed where the rating currently is
- Review tags will be placed above the review and below the rating (as they currently are for UberEats tags)
- Item-based reviews will be placed under the Rating and Rating Text (if available). It will include Item name, modifiers for that item, and the corresponding rating
Insight Page:
- All new tag + item rating data will be pulled into Item level analytics, Common Theme Analytics, and overall review level insights.
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