Moneyball for Marketing: Why you need to look beyond purchase data.

In baseball, home runs are flashy but rare, and games are won by getting on base consistently. Marketing is no different.

If you’re too focused on orders, you’re optimizing for those rare grand slams and missing the real game: the steady, predictable momentum that comes from driving clicks and getting more site visits. In a world where inboxes are crowded, attention spans are short, and attribution is messy, clicks are your at-bats. And the teams (or brands) that get more at-bats, win.

Welcome to Moneyball for Marketing—a smarter, data-backed way to drive revenue growth by focusing on the real predictors of performance.

Why Clicks Matter More Than You Think

Let’s say you run two email campaigns. Each one drives the same number of purchases and generates the same revenue. But one campaign gets 2x more clicks than the other.

Which one is better?

It’s the one with more clicks.

Why? Because:

More clicks mean more people are moving down the funnel.
Every click is an opportunity to learn more about intent, behavior, and timing.
A high-click campaign sets up future conversions—even if they don’t all happen today.

Clicks are leading indicators. They tell you what’s working before orders roll in. And unlike purchases (which are rare, lagging events), clicks give you volume and velocity—the raw materials you need to refine segmentation, test creative, and build smarter lifecycle programs.

Why Adding Non-Order Data Drives Better Segmentation

Most people on your list haven’t bought anything recently. Many haven’t bought at all. If your segmentation only looks at purchase behavior, you’re ignoring the majority of your customer base.

Instead, you need a segmentation strategy that considers:

Clicks and site activity
Lifecycle timing and cohort trends
Seasonal engagement patterns
Signs of renewed interest—even from long-dormant profiles

This is the foundation of Orita’s machine learning approach. By analyzing behavioral patterns across your entire list, we find the next best opportunities—the customers who might not have purchased yet, but are showing all the signs that they’re ready to.

Incrementality matters: looking at propensity to buy because of an email

Most predictive models estimate who’s likely to buy. But here’s the catch: many of those customers would have bought anyway, whether you emailed them or not.

Orita focuses instead on incrementality—finding the people who are more likely to buy because you messaged them.

It’s a subtle but powerful difference. It means: