Synthetic data sounds futuristic, but you don’t need a moonshot project to see value. You can start small, in places where it relieves real-world pain points for experimenters. Here are 3 low-effort pilots I’ve seen make an immediate difference:

1️⃣ Pretest A/B Variants Before Launch
Most A/B tests are built on hope—that your headline, creative, or flow might resonate. Synthetic audiences let you run a “dress rehearsal” before exposing real customers. You won’t get perfect predictions, but you will spot weak variants, save time, and increase the odds your live test has winners in the mix.

2️⃣ Reduce Customer Fatigue
Overexposure is a silent killer of experiments. When the same customers get hit with too many tests, they tune out—or worse, churn. Synthetic audiences help simulate exposure patterns so you can adjust frequency caps or balance groups before you burn goodwill. Think of it as quality control for customer experience.

3️⃣ Fill Sparse Segments Without Distortion
Ever had a test stall because one segment was too small? Synthetic augmentation can expand those rare or underrepresented groups, giving you directional insights faster. You still validate with real data, but synthetic fills the dead zones so your experiments don’t drag on endlessly.✨ The takeaway: You don’t need to overhaul your whole experimentation program. Start by slotting synthetic audiences into the cracks where real data falls short—pretests, fatigue control, sparse segments. Small moves here can unlock big momentum.