How novelty effects and Dopamine Culture rule the tech industryAI apps with shitty retention, consumers with zero patience, and what happens nextDear readers, My (very bad, very lazy) excuse is that I wasn’t very active on blog anyway, being heads down on my book, and as a result, I didn’t want to undergo the big project of transitioning platforms. For now I’m going to keep andrewchen.com where it is for the SEO juice, and will just do my writing here. Anyway, onwards. Let’s talk about “Dopamine Culture” and this provocative chart via Ted Gioia: If you stare at this graphic for a moment, you’ll note a few things:
You could look at this chart and it’s a bit of a Rorschach Test on how you feel about the conversion of IRL/slow experiences into digital/interactive moments. The term “Dopamine Culture” is sort of negative in that it implies that we’re hacking our own biological systems, but let me actually argue the opposite. This is instead, a result of everything…
We could debate all of this further, and we’ll have a grand ol’ argument about whether this is all good or bad for us, but this essay isn’t meant to address all that. We’ll debate that in the cultural/political sphere for ages to come, but this essay is instead about the ramifications of this new accessibility — particularly in the world of building/launching/growing tech products. A couple observations on how all of these trends manifest into tech:
Let’s break each of these down in more detail. Shitty retention is ubiquitous
When you reflect on these metrics, they are actually outright terrible, but I assure you that these particular benchmarks are in fact the good numbers! (That is, most of what I see in pitches/data rooms/etc are much worse than this). In other words, tech products live in a world where you can lose ~90% of our DAUs after a month, and >75% of your user might be inactive. And that’s not only acceptable, but it’s actually good! I’ve written much more about these disturbing metrics here and here, and in general it’s a depressing topic. But obviously a small % of products do succeed each year. The important part and how it fits into Dopamine Culture is that whatever value your product provides, it has to deliver it fast. If you don’t provide value in the first session and the first day, you’ll have such severe drop-off that you won’t get a second chance. If you had “Products” as a row at the top graphic, you’d get something like this:
Good luck. How Novelty Effect impacts our product growth curves In other words, there’s a Novelty Effect. In the early era of a technology S-curve, novelty means that every new interaction hits dopamine hard. Click a button, and something magical happens. Post a demo, and all your followers ooh and aah. Talk about your experiences with a new product, and people think you’re a genius. And the Novelty Effect has some very concrete actual effects on growth:
As many AI founders are figuring out right now, products are often finding spiky growth metrics, popping with each new model release (or shiny new feature) but ultimately with bad long-term retention. A critic might say, easy come easy go. But to be honest, it’s a good trade. At least you’re getting new users, lots of engagement/activity, and thus a lot of investment activity as well. Better to be in a high novelty S-curve and have a chance to be successful than a tired curve where you have to pay/grind for every new customer. Product management culture Product Management at most tech firms have thus aligned to quarterly review schedules where each team promises they’ll raise one metric or another by (a rather unambitious) 2-3%, and then try to do exactly that. If they fail, they blame seasonality, and if they succeed, they try to get promoted :) Jokes aside, the easiest way to deliver on these small promises is to grind out incremental progress — I’ve referred to this as the Next Feature Fallacy — particulalry at helping users get their dopamine hits. This means using algos to help users scroll, or to help them invite their friends. Or to recommend the next bit of content that will keep them engaged. Even small % gains in these core areas drive so much growth that it’s worth it. I argue this is mostly a good thing. We are giving people what they want. And coupled with an engagement-driven business model (online ads) and access to real-time metrics/dashboards, it means we are constantly driving towards making it even more efficient over time. Tap into Dopamine Culture, or counterposition - both can work Perhaps after watching one short form video you might watch hours and hours of video from a creator you like. Or after you read a funny tweet from someone, you decide to subscribe to their Substack or 1-click buy their book on Amazon. Yes it’s a dopamine hit to be able to get the book onto your Kindle quickly, but it’s also an entree into a multi-hour reading experience. On the other hand, it’s also obvious that a new product has to tap into any new emergent culture in order to succeed. In a world where visual media is the dominant force — whether that’s photos, videos, or clips — any product that figures out how to naturally produce media in its usage will succeed. No wonder we’ve seen the Novelty Effect of diffusion models that produce media, being shared on social media, become so viral so quickly. And finally — yes, ride the Novelty Effect. Build upon Dopamine Culture. But also keep in mind that to be successful in the long-run, your product must also be useful. It must retain. Because when the S-curve progresses to the next stage, anyone who is novel but useless will surely come to an early end. |