Why Consumers Trust Data Over Senses

Instincts can lie. Numbers? They never do. Here’s what I learnt after running a startup for 4+ years (the not so obvious lessons) : For example - If 60% of students renew for a keyboard course but only 40% renew for public speaking, that’s a clear indicator that something isn’t working in the public speaking course. No amount of customer conversations can reveal the full picture the way numbers can. Or if one marketing channel is bringing in conversions while another isn’t, the data tells me exactly where to double down and where to pull back. Here’s what I’ve learned about making better decisions: 1️⃣ 𝐀𝐧𝐞𝐜𝐝𝐨𝐭𝐞𝐬 𝐂𝐚𝐧 𝐁𝐞 𝐌𝐢𝐬𝐥𝐞𝐚𝐝𝐢𝐧𝐠: Talking to five customers is useful, but it’s just a small puzzle piece. Individual feedback is often biased and situational. Data gives a broader, unbiased view of what’s actually working. 2️⃣ 𝐏𝐚𝐭𝐭𝐞𝐫𝐧𝐬 𝐃𝐨𝐧’𝐭 𝐋𝐢𝐞: Trends tell a bigger story. Retention, renewals, engagement—all these numbers reveal what customers do, not just what they say. And actions always speak louder than words. 3️⃣ 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧𝐬 𝐍𝐞𝐞𝐝 𝐒𝐜𝐚𝐥𝐞, 𝐍𝐨𝐭 𝐒𝐧𝐚𝐩𝐬𝐡𝐨𝐭𝐬: In EdTech, students typically stay for a few months and then move on. Making long-term strategic decisions based on a handful of conversations is risky. Data helps see patterns at scale, ensuring that decisions aren’t just based on one moment. ---- I still believe in listening to customers, but I’ve learned that what people say and what people do are often very different. Numbers don’t have emotions. They don’t have biases, and they tell the truth. The challenge? Learning to trust them over instinct. Because data doesn’t just guide decisions, it keeps you from making the wrong ones. #data #lessons #marketing #instincts

Trust has always been the glue of any functioning society, but historically, it was rooted in direct human perception: we trusted what we could see, hear, feel, and verify with our own senses, as well as the reputation and consistency of others. The digital era already strained this: when most interactions moved online, we lost our full sensory toolkit and leaned almost entirely on visual perception, the image, the video, the text, to decide what’s real. It worked because we assumed photos don’t lie, videos show what happened, and a “realistic” look signals authenticity. Generative AI breaks that last pillar. When you can’t trust your eyes alone, because anything can be synthetically created to look “real”, the burden shifts from perception to verification. So the new trust model is:          • Not what you see is what you get, but what you can prove is what you can trust.          • Not your senses, but the systems you rely on: provenance, credentials, reputation, technical proofs.          • Not a passive act, but an active practice: constant checking, validating, and re-checking. In this sense, the big shift isn’t that trust is new, it’s that its foundation is moving from our senses to our systems. We’ve never had to outsource trust to technology at this scale before. That’s what’s fundamentally different now. #TrustInTheDigitalAge #ContentAuthenticity #VerifyDontTrust #SeeingIsNotBelieving #ProvenanceMatters #visualcontent #visualtech

⛳️ Imagine spending years convinced you're left-handed, only to have data prove otherwise. That's exactly what happened at my first ever golf lesson.... I write right-handed 🖊️, kick a football right-footed ⚽️ but bat left-handed in cricket 🏏. When it comes to golf, I'm probably one of the few doctors without my own set of clubs mainly because I play so rarely and more relevantly could never decide with which hand to play. This often lead others to think I was hustling them! I recently and belatedly cashed in a father's day present for a golf lesson at a local course. At that lesson, my lifelong assumption of being a left-handed golfer was challenged by cold, hard metrics 📊 Despite my 'natural feel' (and left-handed cricket batting), the digital analysis was crystal clear: my right-handed swing was superior in every measurable way - speed, accuracy, and distance. The digital analysis software left no room for debate, even if my gut insisted otherwise. (Ironically, this lesson was at a golf club designed by Dr. Alister MacKenzie - a GP who traded stethoscope for golf course architecture. Perhaps he too understood the value of evidence over intuition?) This experience perfectly mirrors last year's book 📚 club choice with Ada Health colleagues 'Evidence-Guided: Creating High-Impact Products in the Face of Uncertainty' by Itamar Gilad. In digital health, we often face the tension between 'moving fast' and 'moving right.' Like my golf swing, what feels natural isn't always optimal. ⚡ In SaMD development, this balance is crucial. While rapid iteration is valuable, market validation helps with building products that consistently deliver their intended clinical benefit. Data-driven decisions might take longer initially, but they prevent costly course corrections later (pun intended). Whether it's golf swings or digital health solutions, the message is clear: trust the data, even when - especially when - it challenges your instincts. When there's little to no data, now that's a different matter altogether!