Demystifying “Synthetic Control” — A New Series!

Over the last couple of weeks, I've heard recurring questions from at least 4 customers and 3 investors about the fundamentals of Synthetic Control. This curiosity tells me it's time to address these head-on.

Over the coming weeks, I'll be addressing these questions here on LinkedIn and on Adrsta AI's website, diving into both the fundamentals and real-world applications

But what if a perfect match isn’t achievable? Traditional SCM methods falter when there's no exact pre-campaign alignment between your test and synthetic markets. This is where Augmented Synthetic Controls (ASCM) step in.

• How do advertisers trust Synthetic Control results?
• What's the difference between Synthetic Control vs. Synthetic Data vs. Synthetic Persona?
• Why do you call Synthetic Control the 'Swiss Army Knife' of measurement?
•  Isn't Synthetic Control essentially Geo-Lift?
• Are you saying holdouts aren't needed for incrementality measurement?

Let me start with the trust question — because trust is everything in measurement.

Question #1 of N — How do advertisers trust Synthetic Control results?

• Gold Standard Foundation — Synthetic Control (whether geo, people, or product-based) is an incrementality method rooted in Randomized Control Trial principles — the gold standard of measurement. When your methodology is fundamentally sound, trust follows.
• Visual Transparency — Our platform provides granular time series visualization that plots the behavior of test markets against synthetic control markets across your KPIs. You can literally see how well the control mirrors the test during training and validation periods.
• Statistical Rigor — We compute key statistical metrics including SMD (Standardized Mean Deviation) and ATT (Average Treatment Effect) that quantify the similarity between test and synthetic control markets. Numbers don't lie!
• 4. Multi-Level Validation — Our platform delivers both macro results across all markets AND granular insights for each centroid market, complete with statistical significance scores that clients can cross-reference with their first-party data.

The beauty of Synthetic Control isn't just in its sophistication — it's in its transparency. Every assumption, every comparison, every result can be interrogated and validated.

What questions do you have about measurement methodologies? Drop them below — your question might be the next post in this series.