Before you decide how much you're willing to spend on a test, you should know what you're hoping to get out of it. After all, your budget should be driven by the value of the answer to your question. The dream outcome is obvious. You discover a channel full of your ideal customers, they're converting below your CAC target, and you've found your next growth engine. Ten or fifteen years ago, that happened more often. Today, it rarely does.

Every week, I receive cold emails from agencies promising dramatic growth. "We'll double your pipeline." "We'll triple your leads." "We'll 4X your customer acquisition." I've also had marketing firms suggest we make similar claims in our own outreach. One even recommended taking a case study where we helped a client grow customer acquisition by 4X and turning it into a promise that we'd do the same for every prospect. That's not a marketing strategy. It's a distortion of

Ad platforms rely heavily on machine learning to evaluate combinations of creative assets, audience signals, placements, and engagement patterns... rewarding those who provide a steady stream of creative variation and allow the system to determine what resonates with users. It’s no longer just about finding the best-performing ad. It’s about building a structured way to learn what messages, visuals, and narratives consistently connect with different audiences and improve per

One of the biggest complaints I hear from incoming clients is that their previous agency only reported metrics they didn't actually care about. Clicks. CTR. Impressions. Sometimes even leads. But nothing board-ready, financially-centered, or meaningful. If your agency can only explain performance through marketing metrics, the problem isn't your marketing literacy; it's their business literacy.