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Stories don't end's avatar

Former DD employee here. Can co-sign that the largest ordering segment was low SES millennials. I worked at Caviar which was eventually acquired by Doordash and my biggest shock post acquisition was how many low ticket size orders were going to low/middle income zips. Caviar only operated in big cities and our client base was wealthier. So it wasn't strange to see $200 of Han Dynasty going to the upper west side. But once inside Doordash, I was flabbergasted to see that their median order was a $12 junior bacon cheese burger meal going to a working-class neighborhood in Phoenix (+$10 in delivery fees, maybe a tip, maybe not. Sorry y'all. Doordash's hard data makes it clear that low income people are very bad tippers. $0 tips are WAY more common than you think. Doordash got sued for not giving all tip money directly to dashers. What you didn't see on the outside was that 100% of that money was making it to dashers, but they had some socialist redistribution going on to prevent anyone from ending up at the $0 tip. The lawsuit forced them to stop this practice)

I was so convinced that their business model was doomed to fail-propped up by stimulus checks from modest income housholds- that I sold all of my stock immediately after I left in '21. I greatly underestimated how many people are insanely bad with money.

Yes, there are some sympathetic cases in here of people with kids who want to save time but that's not most of what's going on. This is is driven by the same forces driving up gambling usage: a lack of cultural habits that engender pre-frontal cortex thinking/behavior.

Sam Tobin-Hochstadt's avatar

I'm very confused about the data analysis here. It sounded like you had a bunch of anonymized credit card transactions with amount/date/age/location. And then you did something with census microdata that let you figure out how much that person was making? How does that work?

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