Intelligems
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Calibration
Founders Newsletter | Issue 70
Why it works
- A personal work story gives the central idea context before the email turns to advice for readers.
- The progression from simple comparisons to A/B testing makes the guidance easy to follow, while the closing request keeps the next step clear.
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Calibration Founders Newsletter | Issue 70 Adam Kitain Before Intelligems, I worked in corporate America on an internal strategy team. After a new project got funded, my team’s job was to measure that project’s impact on the business. A lot of times, though, it felt like corporate feel-goodery. We would go through rounds of analysis, alignment and buy-in meetings, all to land on a number built with a method that felt hand-wavy at best. I was using my whole brain to decide how much credit someone deserved. None of it brought in a dollar. Now I run a company, and I make my team do it constantly. Sort of. What I missed back then, and what I think people still miss now with calculating impact, is what the number is for. One project asked whether a group of salespeople should stay on their accounts or move to different ones. It’s easy to interpret that as a “report card” on particular sellers. But these types of analyses are rarely about an individual’s performance; they’re more often about whether an individual should even be doing the thing they’re doing. This has become clearer to me as a founder. My hours, budget and team are all limited, and I want them pointed at the work with the biggest impact. So before we start anything, I ask whoever is leading it what impact they expect. We write the guess down. Usually we build the thing anyway. Once it ships, we compare the result to the guess, and the actual effort to the effort we planned for. The gap between the two tells us how well calibrated we are. Without a written guess, a team can believe for years that its work is having a big impact, because it has nothing to check the results against. The same discipline applies to your site. Most brands start by just doing things, like adding the product or turning on checkout. Then they start measuring the change, adding a free shipping threshold and checking what happened to AOV. Eventually they A/B test, which keeps seasonality and swings in traffic mix out of the result. Each stage is more precise than the last. How much precision you need depends on the size of the bet: a small store can live with a before-and-after comparison, but a brand putting a team or millions in spend behind a change should test it. Not because you need to measure someone’s performance, but because you need to decide whether they should be doing that thing to begin with. ❤️ Loving Intelligems? Share a review Intelligems, 15 Maiden Lane, Suite 900, New York, New York 10023, USA Manage preferences