$70M of incremental revenue: @postmates + @stripe.
https://stripe.com/newsroom/stories/postmates … https://twitter.com/patrickc/status/1329105655265861632 …pic.twitter.com/dkZCh1UMhD
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My naive answer is:
@stripe wants their users to make more money -
Unless Patrick has crossed into Chuck Norris territory, the answer has to be more specific than that.
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Insanely more money.
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Maybe it's like eating veggies, it's not the veggies directly that make you rich, but the fact that you want to eat veggies may be a good indicator that you make good decisions, and good decisions make you rich if you want that.
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Less failed transactions
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My guess: a lot of money left on the table from not being able to accept cards, random reasons for payments not succeeding on their first try, and other miscellaneous edge cases Stripe handles for.
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Less chargebacks and good fraud detection with radar , maybe ?
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A very long list of small optimizations in card network requests. Cardholder banks have weird and inconsistent decision engines; we reverse engineer them across the Stripe network with ML. This gets better with scale!
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I read a Stripe guide on this recently, really great feature to optimize on since it can learn past authorizations as the input to the model on what can be tweaked for successful auth /retry strategy. Funny stuff like John Smith fail but Jon SMITH passhttps://stripe.com/guides/optimizing-authorization-rates …
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A few things are mentioned in the case study: Reducing lost income with features like auto retrying cards when they fail, auto-updating card details when they expire... I’m curious about point #2: the consultation services to reduce network fees...
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