Latest / Marketing Psychology with Fexingo: Behavioral Triggers, Persuasion, and Consumer Behavior / How the Dunning-Kruger Effect Warps Consumer Confidence
Transcript
- Lucas: So there's this bias that explains why someone who just bought their first index fund will tell you they've got investing figured out, while a portfolio manager with twenty years of experience will say they still have a lot to learn. Luna: You're talking about the Dunning-Kruger effect. The classic finding that the less you know, the more confident you are. Lucas: Exactly. David Dunning and Justin Kruger published their paper back in 1999, and it's become one of those ideas that pops up everywhere once you know to look for it. The core is simple: people with low ability in a domain suffer a dual burden — they make mistakes, and they lack the expertise to recognize those mistakes. So they rate themselves as above average. Luna: And the flip side is that experts tend to underestimate their own ability, because they assume everyone else knows what they know. Lucas: Right. That creates a really interesting problem for marketers. If you're selling something that requires a bit of knowledge — financial products, software, health supplements — you're dealing with a customer base that's spread across that confidence curve. The most confident buyers are often the least informed. And the most informed buyers are often hesitant. Luna: I want to ground this in a real number. There was a study in 2024 on a DIY investing app — not naming names — but they looked at new users who'd been active for three months. 63 percent of them rated their investing skill as 'above average.' And over that same period, the median account was down about four percent. Lucas: That's a perfect example. And here's the thing — the app's marketing was heavy on 'you can do this yourself,' 'take control of your money.' It attracted people who were already overconfident. The marketing message validated their bias. Luna: So you're saying the marketing actually made the problem worse. Lucas: In a sense, yes. The company's growth strategy relied on that initial surge of confidence to get sign-ups. But over time, those users lost money, got frustrated, and churned. The retention numbers were terrible. Meanwhile, the users who came in with a more realistic self-assessment — they stayed longer, asked more questions, and eventually became profitable customers. Luna: So how do you market to both groups without alienating either? You can't tell the overconfident person they're wrong, and you can't scare off the cautious expert. Lucas: One approach is what I'd call 'confidence-calibrated messaging.' You design your content and your onboarding to meet people where they are. For the novice, you provide structure — maybe a quiz that gently reveals gaps in their knowledge. Not to shame them, but to show them there's more to learn. For the expert, you offer depth — advanced features, data, white papers. Let them self-select. Luna: There's a financial services firm I know that does this well. Their website has two paths: 'I'm just getting started' and 'I know what I'm doing.' Both lead to different onboarding flows. The beginner path includes educational modules about risk and diversification. The expert path jumps straight into portfolio tools. They capture both ends of the Dunning-Kruger curve. Lucas: That's smart. And it's not just about segmentation — it's about timing. The overconfident novice might not click 'I'm just getting started' on day one. But after they've made a few mistakes, they might be open to it. So you build in touchpoints — a check-in after a month, a performance summary that shows how their choices compare to a benchmark. That data can be a reality check. Luna: But if you deliver that reality check too bluntly, you risk losing them altogether. There's a fine line between educating and insulting. Lucas: Absolutely. Tone matters enormously. The best example I've seen is from a language-learning app — again, not naming names. They gamified the self-assessment. When a user overestimates their skill, the app doesn't say 'you're wrong.' It says 'interesting, let's see how you do on this challenge.' Then it presents questions at a slightly harder level. If the user fails, the app normalizes the difficulty: 'this level trips up a lot of people, want to brush up on the basics?' It frames the adjustment as a choice, not a correction. Luna: So you're letting the user save face while guiding them toward a more accurate self-view. Lucas: Exactly. And the same principle applies to expert users. They often underestimate themselves, so they might not engage with advanced features. You can surface those features subtly — 'users like you also use X' — and let them discover their own competence. That builds confidence in a way that feels earned. Luna: I think this bias also shows up in B2B purchasing. I've sat in on sales calls where a procurement manager with no technical background is absolutely certain about which software solution is best. Meanwhile, the engineer in the room is hesitant because they know the integration challenges. Lucas: Classic Dunning-Kruger in the wild. And the marketer's job there is to create materials that speak to both audiences. For the overconfident decision-maker, you need simple, compelling narratives that still contain accurate information. For the expert, you need detailed specs and case studies. If you only target one, you lose the other. Luna: It makes me wonder about product reviews. You ever notice how the most glowing five-star reviews are often from people who just unboxed the product? They haven't used it enough to know its flaws. Lucas: That's a great observation. The peak of the Dunning-Kruger curve for a product is right after purchase, before reality sets in. Smart marketers know that. They'll sometimes prompt for a review immediately, while confidence is high. But the more thoughtful ones wait — they ask for feedback after thirty days, when the user has a more balanced perspective. That gives you a review that's actually useful to future buyers. Luna: And it reduces the risk of a backlash later, when the initial overconfidence fades and the user realizes the product isn't perfect. Lucas: Exactly. Look, I think the real takeaway for marketers is this: don't exploit the Dunning-Kruger effect for short-term conversions. Yes, you can get a quick sale by telling someone they're a natural. But that customer will churn. If you want long-term relationships, you help people calibrate. You educate. You build actual competence. Luna: It's more work, but the retention data backs it up. The investing app I mentioned — after they redesigned their onboarding to include a knowledge check and a learning path, retention at six months went up by eighteen percent. Lucas: That's a huge improvement. And it shows that when you respect the bias, you get better outcomes for everyone. The customer feels more confident in a genuine way, and the business keeps them longer. Luna: It's funny — the more we talk about this, the more I realize how many marketing campaigns are built on the opposite premise. They want you to feel like an expert so you'll buy. Lucas: Right. And that works, but it's a short game. The brands that last are the ones that help you become actually good at whatever you're doing. That brings us to something I wanted to mention. Luna: Go ahead. Lucas: If these marketing conversations have sparked something you've actually used in your work or just thought about differently, that's exactly the kind of thing that keeps us going. We keep this show ad-free, which means it exists because a small group of listeners chips in monthly through buy me a coffee dot com slash fexingo. Luna: Yeah, it's not a big ask. It's literally what funds the research and the time we put into each episode. And we try to make every one worth your while. Lucas: So thank you to anyone who's already part of that. And if you're not, no pressure — the show stays free either way. But knowing that some of you find it useful enough to support is what lets us keep digging into these topics. Luna: Alright, back to the bias. You mentioned that experts underestimate themselves. How should a marketer handle that in a sales context? Lucas: For the expert, you want to validate their caution without undermining their confidence. Use social proof from other experts — case studies, testimonials from people they respect. Show them that their peers have succeeded with your product. That's one of the few ways to bridge the gap between their perceived ability and their actual competence. Luna: So it's almost the reverse of what you do for the novice. For the novice, you gently deflate. For the expert, you gently inflate. Lucas: That's a good way to put it. You're calibrating confidence in both directions. And if you do it well, you end up with a customer who trusts you — because you didn't lie to them or manipulate them. You helped them see themselves more clearly. Luna: That sounds like the kind of marketing that builds actual brand loyalty. Lucas: It does. And it's harder than just slapping a 'you're a genius' headline on a landing page. But the data keeps showing it's worth it. Next episode, we'll look at another bias that plays out in how we process information before making a decision.