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Novelty effects: Why features get boosts
Ever notice how your team gets ridiculously excited about a new feature launch, only to watch engagement drop off a cliff two weeks later? You're not alone. This frustrating pattern has a name: the novelty effect.
It's that dopamine-driven spike that makes every new release look like a winner - until it doesn't. Understanding this phenomenon isn't just academic; it's the difference between building features that actually stick and chasing metrics that lie to you.
The power of novelty: Understanding why new features get an initial boost
Here's the thing about new features: they're basically digital crack for our brains. When users encounter something novel, their brains release dopamine - the same neurotransmitter that makes you check your phone 47 times during lunch. The folks on Reddit's Oculus community know this pattern all too well, watching VR headsets go from "life-changing" to "dust collector" in record time.
This isn't just a tech thing. Teachers see it when they introduce iPads to classrooms. Dating apps experience it with every profile redesign. Even Apple Vision Pro users are already asking if the magic has worn off (spoiler: for many, it has).
The novelty effect is actually a brilliant growth hack - if you use it right. As Lenny Rachitsky points out in his newsletter about growth turbo boosts, novelty can be a legitimate lever for jumpstarting engagement. The problem? Too many teams mistake this temporary high for sustainable growth.
Think about it: novelty works because it hijacks our brain's reward system. New experiences light up our neural pathways, improve memory formation, and make us feel good. But like any good high, it doesn't last. And that's where things get tricky for product teams trying to build something that matters.
The fleeting nature of novelty: Challenges in sustaining user engagement
Let's be honest - novelty is a terrible foundation for a product strategy. It's like building your house on a sugar high. Sure, everything looks great at first, but wait a few weeks and watch those engagement metrics nosedive faster than crypto in a bear market.
The real danger isn't just that novelty fades. It's that it makes you stupid about your data. You launch a new feature, see a 40% engagement spike, and start planning your IPO. Meanwhile, your users are just clicking around because it's shiny and new, not because it's solving their problems.
Smart teams know this, which is why they:
Track metrics for at least 4-6 weeks before declaring victory
Look at retention rates, not just initial adoption
Pay attention to qualitative feedback (are users actually happy, or just curious?)
The teams at successful companies have learned this lesson the hard way. They focus on what Lenny calls delivering lasting value - features that users still care about after the new car smell wears off. This means building things that become habits, not just headlines.
Here's the uncomfortable truth: if your feature's success depends on being new, you've already failed. Real value persists. Everything else is just noise.
Navigating novelty effects in product development and data analysis
A/B testing during a novelty spike is like trying to measure ocean depth during a tsunami. The data's all there, but good luck making sense of it. Statsig's data science team discovered this when analyzing why A/B test results often differ from real-world outcomes - novelty effects were a major culprit.
The solution isn't complicated, but it requires patience (I know, I know - not exactly a Silicon Valley virtue). You need to let the novelty dust settle before making big decisions. This typically means running experiments for longer than feels comfortable - think weeks, not days.
Smart teams use a few tricks to cut through the novelty noise:
Time-based segmentation: Compare week 1 users to week 4 users
Cohort analysis: Track how different user groups behave over time
Pre-experiment baselines: Use techniques like CUPED to control for the novelty effect
That last one is particularly clever. As explained in Statsig's guide on making early decisions on experiments, CUPED uses pre-experiment data to reduce variance and reach statistical significance faster. It's like having noise-canceling headphones for your data.
The key is remembering that novelty effects aren't your enemy - they're just another variable to account for. Some of the best product launches deliberately leverage novelty for that initial momentum boost. The difference between success and failure is knowing it's temporary and planning accordingly.
Strategies to leverage novelty while building lasting engagement
So how do you turn that novelty sugar rush into sustainable energy? You don't fight the novelty effect - you surf it.
The smartest approach I've seen is what I call the "novelty treadmill" - keeping users engaged by continuously shipping small, meaningful updates. Not massive overhauls that confuse everyone, but regular hits of newness that keep the product fresh. The team behind many successful apps uses this strategy, as outlined in 60 growth boost ideas, to maintain momentum without exhausting their users.
But here's where most teams screw up: they focus on the wrong kind of novelty. Adding a new button color isn't innovation - it's procrastination. Real novelty that sticks has three characteristics:
It solves a problem users already have (not one you invented)
It builds on existing habits (don't make users relearn everything)
It creates value that compounds over time (think network effects)
Community is your secret weapon here. When users connect with each other, they create their own novelty through interactions, content, and relationships. Reddit threads about everything from psychology to VR experiences show how community discussions keep products relevant long after the initial buzz fades.
The other underutilized strategy? Let your users surprise themselves. Gamification gets a bad rap, but done right, it creates sustainable novelty through achievement, progress, and discovery. The key is making the game worth playing, not just adding points to boring tasks.
Closing thoughts
Look, novelty effects are going to happen whether you plan for them or not. Every new feature, every product launch, every shiny update will get that initial dopamine-driven boost. The question is: what are you going to do about it?
The teams that win don't pretend novelty doesn't exist. They also don't bet the farm on it. They use novelty as a launching pad, not a landing strip. They measure what matters over time, not just what spikes on day one. And most importantly, they build products that are still useful when they're boring.
Want to dive deeper? Check out:
Your own product's 30-day retention data (seriously, go look at it)
Hope you find this useful! And remember - the next time someone gets excited about a day-one metric spike, be the person who asks, "Yeah, but what happens on day 30?"