Nobody in this community needs convincing that conversion rate isn't the whole story. Profit per visitor over CVR, we mostly get it. When we had @Luka Nikolić on Live with Intelligems recently, the interesting part wasn't the pitch for it, it was how much time he spent on why it's so hard to actually run a program this way. His answer came down to data and financial literacy. Getting profit into a test means getting COGS out of a client, and that's a harder conversation than it sounds, especially when they aren't used to sharing it. He's had to fight for those uploads. An agency can run a retainer for months, tweaking buttons, and never touch the number that actually decides whether the business is healthier, because nobody ever put the real financials in front of them. His pitch was to close the laptop on the AI tools for a bit and go read the boring spreadsheets instead. Return rates, supplier terms, how customers actually segment. The unglamorous stuff practitioners tend to skip is usually where the profit lever is hiding. His line for it: "revenue is vanity, profit is sanity." The full interview is attached below if you want to watch the whole conversation. Curious where this community lands. For those tracking profit per visitor, how did you get COGS out of a client who didn't want to hand it over? Have you ever shipped a test that won on conversion rate and later realized it hurt margin? And is there a "boring spreadsheet" you've gone into that ended up reshaping what you tested next?

Most store owners pick $50 or $75 because it sounds right. But your customers are already showing you the real number. Here's how to let the data decide: 1. Graph your order history Plot your orders by value over the last 90 days. You'll see natural peaks where customers tend to land. These clusters reveal spending comfort zones you didn't set... they emerged on their own. 2. Find your abandonment cliffs Pull cart abandonment rates by value. Look for sharp drops at specific price points. That's where your current threshold creates friction that kills conversions. 3. Watch what gets added last Check which products appear in carts just above your threshold. Stickers, samples, cheapest items in your store? That's customers telling you the threshold feels arbitrary. They're buying stuff they don't want just to hit the number. 4. Test at natural pile-up points Run threshold tests where orders already cluster. But don't measure AOV alone. Profit per visitor tells the real story. A lower threshold with higher conversion often wins. Your data already has the answer. You just have to ask the right questions.

In your opinion, what is it? We all use heatmaps, surveys, customer service reports, analytics, etc. But do you have a “secret” research method that worked wonders for a particular client, or your own brand?

One of the hardest parts of the G.E.M. framework is the Explore phase. Not because of a lack of ideas, but because most tests start too close to the solution. One of my favorite ways to uncover your next multiplier test is to slow down and ask a few simple (but uncomfortable) questions: • What’s keeping you up at night (or your boss)? • What’s the most strategically important thing right now? • If you could wave a magic wand and change one thing, what would it be? Then keep asking “why?”Over and over. Until the answer turns into something you can actually experiment on. That experiment shouldn’t just tweak a page; it should help you answer a real question or validate a decision that gives you more confidence to explore further. When Cameron from Bare Bones and I first started talking, his initial idea was straightforward: Remove flavor options from the PDP to reduce decision fatigue. Great idea. But… why? As we kept digging, the real question surfaced: Why do Amazon buyers behave so differently from Shopify buyers? That insight completely changed the direction of the test. Instead of a narrowly defined PDP cleanup, we ran a theme test: One theme with a traditional Add to CartOne theme with a “Buy on Amazon” CTA alongside it. What started as a UX test turned into something much bigger. It helped Cam: • Better understand the post-ad buyer journey • Invest more confidently into Meta acquisition • Make a strategic decision with real signal behind it I’ve attached the full conversation so you can watch how that exploration actually unfolded. And here’s the follow-up discussion if you want to go deeper:https://youtu.be/PUpCc4GEaOE?si=IGFHvl5gvuaRpUV7 This is a great example of how asking better questions in Explore leads to better experiments — and much bigger outcomes.

Couple headline tests that have RIPPED for me lately, and kinda made me re-think my approach to testing. For the first time ever, I wrote headlines with specific intentions, deeper than just "make more money" ... On the first test here, I wrote specifically to increase CVR, the headline was geared at convincing more people on our website that our products were good enough quality and worth more to them than the price we offer it for... That's usually how I write... But now that I'm at a supplements brand, I took a swing at writing headlines that would persuade people to subscribe, rather than one-time-purchase our supps. The headline & subtext is more about how our products already fit it to their daily routines and how it can improve them. CVR and Rev Per Session were basically flat on that test, but the Sub % rate was WAYYY higher, so that's a huge win for us. Anyone else have examples of content tests designed to move specific metrics like this?