July 29, 2025
3 minutes
global FMCG brand
improve product visibility and sales
synthetic A/B testing
faster insights at a fraction of the cost
A global FMCG brand approached DataDiggers with a common yet critical retail challenge: how to optimize shelf placement for maximum product visibility and purchase intent—without incurring the massive costs and logistical delays of traditional in-store testing.
Their goal was to evaluate multiple shelf layouts for a new product launch across various markets. But running physical A/B tests in stores, across geographies, would have taken months, strained the budget, and exposed the brand to potential opportunity costs if the wrong setup was chosen.
They needed fast, reliable insights—before hitting the shelves.
To meet this challenge, DataDiggers deployed Modeliq, our advanced scenario simulation and modeling solution. Using statistical and machine learning logic, Modeliq generated synthetic consumer behavior patterns to simulate how real shoppers would interact with different shelf layouts.
We began by creating high-fidelity digital personas through Syntheo, our AI-powered synthetic insight engine. These personas were crafted based on existing customer data, category benchmarks, and real-world behavioral variables—including age, income, shopping frequency, preferred store types, and impulse-buying tendencies.
This allowed us to build representative synthetic samples for each market segment—ensuring the synthetic A/B tests were anchored in credible, human-like decision-making.
With the help of Modeliq, we simulated different store environments featuring three shelf layout scenarios:
Each layout was tested under multiple consumer flows (e.g., solo shoppers, family shoppers, high-speed vs. browsing behavior), mimicking the diversity seen in real-world grocery settings.
Synthetic consumers “interacted” with shelf layouts in a virtual environment. Their product choice behavior was modeled using advanced ML-based logic—considering product color, price, competition on the shelf, and proximity to other categories (e.g., healthy snacks vs. candy aisle).
Modeliq generated a robust synthetic dataset for each scenario, capturing:
Within 72 hours, the synthetic A/B test delivered clear, actionable insights—presented via Brainactive’s smart reporting dashboards. The client could:
The synthetic A/B testing approach yielded faster, smarter, and risk-free insights—at a fraction of the traditional cost.
The client used the results to:
Within three months of implementing the shelf strategy:
This case proves that synthetic A/B testing is no longer a futuristic concept—it’s a present-day advantage. By combining the power of Syntheo and Modeliq, brands can simulate market realities before launching, eliminating guesswork and reducing risk.
DataDiggers’ integrated approach—from real-world data to high-integrity synthetic modeling—enables brands to move fast, act smart, and lead with confidence.
Looking to optimize your product strategy without the wait? Let’s simulate your next retail move — with speed and confidence.
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