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Dan Romero
@dwr.eth
Consumer social products and marketing 1. Marketing creates 1) awareness and, hopefully, 2) demand to sign up 2. For nearly all consumer apps, ~50% of new sign ups never come back to the app after the first day! This declines over the next 30 days to get to a measure of day 30 (d30) retention. 3. Ideally, this decline curve “flattens” (i.e. asymptotic) or even “smiles”. This means you have a retentive product and you can measure $X spent turns into Y downloads and into Z sign ups and into A retained users. 4. However, if your product does not have a retentive curve, then all spending will do is make metrics go up for a bit and then air will slowly come out of the balloon. 5. Retentive social products work because their core value proposition and product / functionality / features creates long-term retention. Exceptional products do that and have a viral growth component (k-factor). 6. So before spending time and money marketing, be sure you have a product that benefits from the marketing.
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MJC
@mjc716
two qs how do you model the fact that most of your target audience is on a singular alternative platform? (i.e. you know who they are and where to find them again) considering that crypto social is a lot more financialized, do you think web2 user acq frameworks apply cleanly?
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Dan Romero
@dwr.eth
1. Makes it harder, especially if your UX is mostly a derivative of said platform. The more we diverge from X / Twitter, the better for Farcaster. That said, the differentiation needs to yield sufficiently interesting content / experiences. 2. Retention is retention whether web2 or web3. You can only create durable value if users stick around.
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christin
@christin
at the sf farcaster meetup some other techies came up to us to ask what meetup it was and we were all like FARCASTER and they were like whazzat and we mumbled "ᶜʳʸᵖᵗᵒ ᵗʷᶦᵗᵗᵉʳ" what would be a better way to shorthand describe farcaster?
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MJC
@mjc716
questions are more around the role of kickstarting viral loops to generate engagement and thus interesting content it seems your model is full utility value with no concept of giving yourself as many chances to get lucky obv too many founders rely too heavily on the latter but there’s still truth to the approach
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