Every Shopify brand heading into Black Friday Cyber Monday faces the same squeeze: customer acquisition costs climb as more brands crowd into the same feeds, right when you’re about to commit the biggest ad budget of your year.

If you’re doing $1M to $10M and your pre-launch creative testing is basically “spend money on Meta and see what sticks,” this episode is for you.

Tamera spent more than 15 years leading sales and marketing teams in tech. Most recently she ran Evolve24, a data science firm that studied billions of online conversations a day to help some of the world’s largest companies set strategy. She saw how much of an edge that insight gave the biggest players, so she built Clarvos to give growing businesses the same footing. Clarvos finds the people most likely to buy from you, grouped by what they care about rather than by age or gender. Then it lets you test your creative against simulated buyers before any budget goes live.

On the show, Tamera walks host Steve Hutt through how that testing works, why it’s different from asking a general AI tool to invent a persona, and how you can still put it to work before the holiday rush.

What you’ll take away from the episode

Stop paying ad platforms to learn. Meta and Google figure out what works by spending your budget on live tests. You’ll hear how testing creative before launch reverses that order.

‍Find buyers by values, not age brackets. A smaller, better-matched group of people can cost less to reach and is more likely to buy.

‍See inside a 50-person simulated panel. Each person has a name, a job, a family, and a way they spend their free time. The panel helps estimate which creative is most likely to land.

‍Learn why a marketing-specific AI behaves differently from a generalist. Steve’s doctor analogy makes the difference clear.

‍Cut through 9,000 targeting combinations. Meta offers roughly 9,000 ways to combine interests, behaviors, and demographics. You’ll learn how to stop guessing which one works.

‍Try it without betting your whole holiday plan. Start with one collection, compare the results with your own picks, and decide from there.