DoorDash’s delivery drivers — called Dashers — may be offered incentives such as peak pay (extra money) to improve supply during particularly busy times, in specific areas.
Tag Archives: Dasher and Logistics
A simulation and evaluation flywheel to develop LLM chatbots at scale
In DoorDash Support, we need useful automations to give our customers and Dashers easy access to quick and complete issue resolutions.
Previously, we hand-built detailed decision trees — workflows — that allowed users to navigate through selecting options or writing free text that was then mapped to available branches.
Precision in Motion: Deep learning for smarter ETA predictions
In the fast-paced world of food delivery, accurate estimated time of arrival, or ETA, predictions are not just a convenience; they’re a critical component of operational efficiency and customer satisfaction.
Path to high-quality LLM-based Dasher support automation
The independent contractors who do deliveries through DoorDash – “Dashers” – pick up orders from merchants and deliver them to customers.
Improving ETAs with multi-task models, deep learning, and probabilistic forecasts
The DoorDash ETA team is committed to providing an accurate and reliable estimated time of arrival (ETA) as a cornerstone DoorDash consumer experience.
How DoorDash Improves Holiday Predictions via Cascade ML Approach
At DoorDash, we generate supply and demand forecasts to proactively plan operations such as acquiring the right number of Dashers (delivery drivers) and adding extra pay when we anticipate low supply.
How DoorDash Built an Ensemble Learning Model for Time Series Forecasting
In real-world forecasting applications, it is a challenge to balance accuracy and speed.
Lifecycle of a Successful ML Product: Reducing Dasher Wait Times
Building an ML-powered delivery platform like DoorDash is a complex undertaking.
How DoorDash Upgraded a Heuristic with ML to Save Thousands of Canceled Orders
One challenge in running our platform is being able to accurately track Merchants’ operational status and ability to receive and fulfill orders.
Leveraging Causal Inference to Generate Accurate Forecasts
For any operations-intensive business, accurate forecasting is essential but is made more difficult by hard-to-measure factors that can disrupt the normal flow of business.