In retail, knowing what happened yesterday is easy. Knowing what will happen tomorrow — and acting on it today — is where market leaders are made.
That’s the promise of our AI Simulator: a core intelligence layer in the V9 analytics platform that models millions of shopper journeys, predicts outcomes, and guides store-level decisions at enterprise scale.
From Data to Foresight
Most analytics tools stop at reporting. They tell you how many people visited, how long they stayed, or how many purchased.
The AI Simulator goes further — it asks “What if?” and answers with evidence, not guesswork.
Just as ChatGPT is powered by a language model, the AI Simulator is powered by a spatial-temporal graph neural network (STGNN) — an AI that understands relationships:
- Between shopper demographics and buying patterns
- Between movement paths and dwell zones
- Between campaign triggers and customer response
- Between store layout and product engagement
It learns from millions of real shopper journeys, enriched with context like weather, seasonality, promotions, and even local events.
Two Powerful Modes
1. Single-Scenario Simulation
Test a specific “what-if” before committing resources:
- What if we move the promotional stand to the front?
- What if a new mall entrance changes traffic flow?
- What if we increase lunchtime staffing by 20%?
2. Monte Carlo Simulation
Run hundreds of variations to reveal probable trends and statistical confidence:
- Expected customer mix (e.g., 40% solo shoppers vs. 15% couples)
- Likely engagement hotspots
- Sales conversion forecasts
From Prediction to Prescription
The AI Simulator doesn’t just predict — it activates decisions across your organisation:
- Store managers get alerts for staffing and merchandising
- Marketing teams see which campaigns are most likely to succeed
- Operations can optimise floor layouts before spending a dollar on changes
Example: The system predicts 720 customers in the next 3 hours, with 40% likely to browse hype fashion and 15% likely to purchase co-branded tees.
Your staff and merchandising teams adjust before shoppers arrive.
Within the V9 platform, teams can:
- Create campaigns from built-in templates tailored to retail scenarios
- Define demographics, floor plans, promotions, and run counts
- Simulate millions of possible journeys under chosen conditions
- See results as heatmaps, pathmaps, dwell forecasts, and product-level metrics
Role-based access ensures each stakeholder sees only what’s relevant to their scope — from executives to store managers.
Why This Matters for the C-Suite
- De-risk major decisions – Test campaigns, layouts, and staffing virtually before committing resources
- Shorten time-to-impact – Move from idea to validated strategy in days, not months
- Maximise ROI – Direct budgets to the highest-yield actions with statistical confidence
- Scale insights globally – Apply learnings from one store to an entire estate in a click
The Competitive Edge
Retail leaders don’t wait for reports to tell them what happened. They shape what will happen next. The AI Simulator is not about replacing human decision-making — it’s about augmenting it with foresight.
By turning raw data into predictions, and predictions into prescriptions, the AI Simulator ensures you act with clarity, speed, and confidence — store by store, day by day.
See it in action in our next webinar and discover how predictive retail analytics can move your business from reactive to proactive — and from good to category-leading.
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