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Restaurant Location Accuracy Improvement

2 posts · Apr 2019

What this trail covers

Grab has evolved its restaurant location accuracy by leveraging driver-partner GPS data and timestamps to infer pickup locations. This involves filtering GPS data based on quality metrics, defining 'at the restaurant' based on time spent within a radius and longest streak analysis, and ranking restaurants for manual verification based on order volume, pickup location deviation, and distance. This system has led to a reduction in median error distance and a 5x decrease in cancellations due to incorrect restaurant locations.

All Grab trails
  1. Guiding You Door-to-Door via Our Superapp!This post introduces a new feature for improving pickup point selection at large venues like airports and shopping centers. It addresses the challenge of inaccurate GPS signals indoors and the difficulty of finding designated pickup points. The solution involves identifying "Entrances" (pre-designated pickup points) and providing in-app photo and text directions to guide users to their selected pickup point. This builds upon previous efforts to reduce "rendezvous distance" by providing more granular navigation within venues.
  2. How We Harnessed the Wisdom of Crowds to Improve Restaurant Location AccuracyThis post details the methodology for inferring restaurant pickup locations using driver GPS data and timestamps. It explains the filtering of sub-par GPS data, the definition of 'at the restaurant' based on time spent within a radius and longest streak analysis, and the ranking criteria (order volume, fraction of invalid pickups, median distance) used to prioritize restaurants for manual verification. The results show a reduction in median error distance and a 5x decrease in cancellations due to incorrect locations.