Simulation outcomes from live client engagements. Each study maps the gap between what companies assume and what synthetic populations actually do.
A CPG brand planned to enter Tier 2/3 Indian cities through premium retail and digital. Five synthetic personas from Kanpur, Nashik, Bareilly, Indore, and Bhopal revealed the flaw: purchase decisions in these markets ran through kirana distribution networks and localised social trust — channels the brand had no presence in and no budget for.
A men's personal care brand had built a decade of equity in shaving. Their masterbrand name contained a strong category reference — "Shave Co." — that had worked brilliantly for the core business. When the brand tried to expand into skincare and launch a women's sub-brand, conversion collapsed. The simulation found the name itself was the ceiling: consumers couldn't place a shaving brand in new categories no matter how strong the product story. Brand architecture, not copy, was the lever.
A D2C brand's highest-follower creator drove almost zero purchases. 40 synthetic buyers across 4 cohorts revealed why: purchase authority was not correlated with audience size or content style — it was built through personal trust signals invisible to follower count metrics. The creator with 10% of the followers was converting 3× better.
A functional food brand placed a diet-category keyword in their Amazon title to maximise search volume. The simulation found it was suppressing 83% of their addressable audience — signalling a niche dietary tribe to the vast majority who didn't belong to it. Zero non-specialist personas preferred the diet-keyword title. The fix was a rewrite, not a product change.
A micro-savings platform assumed lower-income users would churn first. The simulation found the opposite. The lowest-income persona was the most churn-resistant. The highest-income user churned on day 67 after a ₹505 paper loss. Income predicted almost nothing — identity built around saving predicted everything.