Estimated time of arrival determinations in an online concierge system

A non-transitory computer-readable storage medium storing instructions that when executed by one or more computer processors perform actions comprising:

• receiving an indication of a set of items from a user;
• computing a first ETA for delivery of the set of items to the user;
• generating a set of candidate ETAs based on the first ETA;
• for each candidate ETA of a plurality of the candidate ETAs:
• estimating, using an acceptance prediction model, a likelihood that the user will accept the candidate ETA for delivery of the set of items, wherein the acceptance prediction model is a machine-learning model trained to predict acceptance based on features including properties of prior user orders;
• estimating, using a cost prediction model, a cost of delivery of the set of items given the candidate ETA;
• computing a score for the candidate ETA based at least in part on the likelihood of acceptance and the cost of delivery;
• selecting a first one of the candidate ETAs having a highest score;
• and
• presenting, to the user within a graphical user interface, the selected ETA as an option for delivery time for the set of items.

A computer system comprising:

• one or more computer processors;
• and
• a non-transitory computer-readable storage medium storing instructions that when executed by the one or more computer processors perform actions comprising:
• receiving an indication of a set of items from a user;
• computing a first ETA for delivery of the set of items to the user;
• generating a set of candidate ETAs based on the first ETA;
• for each candidate ETA of a plurality of the candidate ETAs:
• estimating, using an acceptance prediction model, a likelihood that the user will accept the candidate ETA for delivery of the set of items, wherein the acceptance prediction model is a machine-learning model trained to predict acceptance based on features including properties of prior user orders;
• estimating, using a cost prediction model, a cost of delivery of the set of items given the candidate ETA;
• computing a score for the candidate ETA based at least in part on the likelihood of acceptance and the cost of delivery;
• selecting a first one of the candidate ETAs having a highest score;
• and
• presenting, to the user within a graphical user interface, the selected ETA as an option for delivery time for the set of items.