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Baemin's 1.7-times accuracy claim implies merchant-typed ETAs were right under 30% of the time

Korea's largest delivery app says its model now clears 50% accuracy on arrival times, more than 1.7 times what restaurant owners managed typing the numbers in by hand. The old baseline was under 30%.

The Investor · Invest desk

Illustration accompanying Baemin's 1.7-times accuracy claim implies merchant-typed ETAs were right under 30% of the time

What happened

  • Baemin will start showing automatically predicted delivery times at the point of order next month, replacing the cooking and delivery estimates restaurant owners had been entering by hand.
  • Baemin says the AI forecasts now exceed 50% accuracy, more than 1.7 times the accuracy of the owner-estimated method they replace.
  • Coupang Eats' store-coordinate optimization analyses pickup locations, rider movement data and road information to steer riders to a restaurant's exact location instead of its GPS pin.

Compiled by The InvestorSomething wrong?How this is made

Why it matters

  • exposure While owners typed the estimate, a late order was the owner's number. From next month the displayed time is Baemin's model output, and the miss belongs to the platform.
  • decision Both apps now have to decide how much of the free-delivery budget moves into forecasting, given that promotions are described as bringing in users who then leave over late deliveries.
  • constraint Automating the estimate removes the one lever a restaurant had to buy itself slack on a busy night, since it no longer sets the number customers see.
  • contradiction Baemin put a ratio and a percentage on its gain; Coupang Eats' official described falling location inquiries and fewer hour-plus deliveries without figures, so the two programmes cannot be compared on the record.

Fifty divided by 1.7 is 29.4. Taking Baemin's two disclosed figures at their floors, the cooking and delivery times restaurant owners typed in by hand were right fewer than three times in ten [5][1]. The article does not define what counts as an accurate forecast, so the tolerance behind both numbers is unstated [6].

What replaces the typing reads 58 kinds of data, among them order volumes at individual restaurants, congestion in the surrounding area and how many riders are free [4]. Baemin says it built the system to take the estimating burden off owners and cut forecast error [3].

Over the year to last month Baemin added 1.34 million monthly active users and Coupang Eats added 2.70 million, almost exactly twice as many [2][3][4]. Baemin's lead narrowed from 11.32 million to 9.96 million [5]. Coupang Eats now has 59.2% of Baemin's monthly user count, against 50.9% a year earlier [6].

Sedaily reports the industry is spending on accuracy because it treats the delivery quality users actually experience as the factor that determines repeat use, and that free-delivery promotions can bring in users who leave again as late-delivery complaints pile up [10][11]. A subsidy is paid on every order. A forecasting model is built once and then runs, and the substitution only pays if better arrival times hold users who would otherwise have gone.

I'd expect this to settle as a cost both platforms carry with neither taking users off the other because of it. Coupang Eats grew 23.0% over the year with a coordinate fix that shipped only recently, and its official said store-location inquiries have fallen sharply since adoption and that orders taking more than an hour also declined [13][7][9]. The 50% figure could equally reflect a strict tolerance, in which case the model is better than the number sounds [5][6].

"The fiercer the competition among delivery apps becomes, the more this will emerge as an important service advantage," an official in the retail industry said [14].

The check arrives in the monthly user counts after launch. If Coupang Eats keeps adding around 2.7 million users a year once Baemin's forecasts improve, the accuracy work is maintenance on a base of 24.4 million [3][12]. If Baemin's growth moves up off 5.8% without a new fee promotion, arrival-time accuracy is the plausible reason [12].

What to watch

  • Whether Baemin publishes a tolerance window with its accuracy figure once the system is live next month.
  • September and October monthly active user counts, and whether Coupang Eats holds a 23.0% annual pace after Baemin's launch.
  • Any move by either app from showing an estimated arrival time to guaranteeing one, with compensation when it is missed.
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