Most marketers want to test everything. But you don’t have unlimited budget, time, or team capacity. So you need to be ruthless about what actually gets tested. That means knowing where a test will generate the most value — not just statistically, but strategically.
Here’s how we help the best teams prioritize.
1. start with where your model is most uncertain
Uncertainty isn’t a bug in your MMM but a feature that tells you where to focus. The widest confidence intervals point to your highest-impact test opportunities.
At Recast, we highlight uncertainty bands around every ROI estimate. When you see:
- Meta Prospecting: ROI 3–4x
- Podcasts: ROI 1–10x
The podcasts channel becomes your priority, not because it might be better, but because resolving that uncertainty unlocks the biggest budget decisions. A tight range lets you move confidently. A wide range means you’re flying blind.
Same principle applies to conflicting signals between measurement methods. Those contradictions aren’t problems to ignore–they’re experiments waiting to happen.
2. measure the expected value of the learning, not just the statistical precision
Not every test needs to be a gold-standard RCT. The right question is: what will I do differently if this test tells me something new?
Let’s say you’re spending $2M/quarter in a channel with uncertain performance. Turning it off in a geo-heavy-up test might be noisy, but if it shows zero drop in sales, that unlocks millions in future savings. Even if there’s some uncertainty, the expected value of that learning is massive.
Compare that to testing two landing pages with slightly different button colors. Even if the result is clean and significant, the outcome won’t change your strategy. That’s a low-value test — even if it’s statistically elegant.
So, before greenlighting a test, ask:
- What’s the expected value of the decision this test informs?
- Is the uncertainty I’m resolving blocking a major budget move?
- Will the result materially change how I allocate spend?
If the answer is no, don’t run the test. Spend the time elsewhere.
3. choose your experiment type based on constraints — not idealism
There’s a hierarchy of tests, and each comes with trade-offs:
- Individual-level RCTs: best signal, highest cost, limited to digital
- Geo holdouts: great for cross-channel tests, works for TV/podcast, lower precision
- Go-dark / before-after: fast, dirty, sometimes enough
Most marketers try to force everything into one method. But the best teams choose the method based on what the decision requires, not what the textbook says.
For example:
You think TikTok is underperforming. Rather than wait for the perfect individual-level test (which might not even be feasible), you go dark in three markets for four weeks. If sales stay flat? You just saved a considerable amount of your budget. If they drop? You’ve validated the channel and can scale confidently.
And always blend your learnings. No test lives in isolation. The strongest systems use MMM to weave together experimental results, digital attribution, and marketer intuition into one incrementality system.
final word: don’t wait for perfect signal
The sharpest marketers don’t chase perfect answers. They run high-impact tests, update their beliefs, and act. They think in bets. They learn fast. And they don’t waste cycles proving what they already know.
If your team is prioritizing tests by how clean the results will be — not by how much they’ll move your next decision — you’re playing the wrong game.
Use uncertainty as a guide. Use MMM to surface where learning matters. And design every test to inform your next budget move — not just to get a p-value.
