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I think the trap here, a function of scaling any business, is that what's best for most of your customers isn't necessarily best for all of your customers. Ano
by teej 13y ago
I think the trap here, a function of scaling any business, is that what's best for most of your customers isn't necessarily best for all of your customers. Another perspective is that what's right for your 2013 customers isn't necessarily the right thing for your prospective 2014 customers.
One possible outcome of your decision is that you're optimizing for customers who have repeat business and against customers with one-off business. That may well be right thing for Stripe.
I am a strong supporter of opinionated software but I think that view has to be colored with "this solution will be wrong for some customers" and "we are not building a solution for every customer". I imagine these assumptions are implied in your explanation above.
- pc 13y agoFor sure. We haven't seen evidence yet that there are things that are amazing for some segments and bad for others -- but if we did (or if we do in future -- we're still measuring), that'd certainly inform our approach. Also, it's probably worth emphasizing that the traditional Stripe integration options are all still present and always will be.
- benmathes 13y agoYou could also automatically run split tests on a per-merchant basis, thereby automatically auto-tune the checkout for each merchant.
- pc 13y agoThat's a neat idea.
- benmathes 13y agoAnd you can use it for just 5% of any profits made on it. but seriously, have at it. Guaranteed there's prior art.
- Robin_Message 13y agoIf recurring vs not is important to how Remember Me is perceived, and you've been a/b testing it, you could probably test this particular hypothesis easily.
- loceng 13y agoProbably want the business's prior permission first before testing their revenue funnel - and not just sitting comfortable with a "things will be evolving and changes might happen" as acceptable.
- amirmc 13y agoMaybe. Unless the merchant is also changing site content that you're not aware of and then everybody ends up making decisions based on flawed data and assumptions.