A leading supermarket chain uncover $274K+ in revenue opportunities in 14 days
Client Profile
The Challenge
The client manages one of the largest and most influential supermarket chains in Saudi Arabia, operating hundreds of stores and serving millions of customers monthly across grocery, FMCG, household items, and perishables.
A business of this scale generates massive volume across transactions, customer journeys, promotions, and product interactions. However, extracting actionable insights from this data can be slow, expensive, and fragmented across teams and systems
The leadership team wanted to:
- Build a modern customer-intelligence foundation grounded in actual shopper behaviour, not opinion-based surveys.
- Get rapid, data-backed answers to segmentation, pricing, and promotion questions that currently take weeks or require external research.
- Identify high-value customers and churn risks
Our Solution
DoppelIQ partnered with the client to build a next-generation customer intelligence engine powered by AI-based digital twins.
We started with their transaction-level data, validated all incoming datasets, mapped 40+ customer attributes, and reconciled behavioural inconsistencies to ensure model accuracy.
This data was converted into living, dynamic twins (simulations) that capture motivations, triggers, price elasticity, brand affinity, and lifestyle patterns.
Each customer twin simulates:
The Results
Simulations That Revealed Hidden Revenue
Once behavioral digital twins were created, the team began testing real business decisions inside the simulation layer before executing them in the market. DoppelIQ’s conversational interface enabled the client to query for qualitative as well as quantitative insights.
Instead of guessing which campaigns would work, they asked questions like:
- If we reduce discounts on Fresh and Almarai products, which customers will still buy and which will drop off?
- What will happen to revenue if we limit offers to once per month for heavy deal-seekers?
- If we target online-only shoppers with Fresh Produce bundles, how much can AOV grow?
- Which VIP customers are likely to churn even though their past spend is high?
DoppelIQ ran iterative simulations across hundreds of customer twins and surfaced high-confidence opportunities.
VIP Expansion
45 high-value customers showed strong cross-category affinity to a targeted upsell strategy.
Discount Optimization
without hurting sales.Selective discounting was utilized for 68% of customers who were highly promotion-dependent.
Retention Recovery
Simulated win-back campaigns showed measurable recovery for 103 inactive customers.
Total opportunity identified in the first 14 days:
Conclusion
The client’s existing research foundation is strong - survey‑driven segments and consumer studies provide valuable context on why customers behave a certain way. DoppelIQ does not replace this.
Instead, it complements and enhances it by grounding those insights in real, revealed behavioural data. Think of digital twins as the behavioural engine that sits underneath traditional research. Research explains attitudes, motivations, and stated preferences. Digital twins capture actual behaviour, purchasing patterns, discount sensitivity, and lifecycle shifts.
DoppelIQ transforms this raw transaction data into a living simulation of the customer base. This leads to more reliable segmentation, sharper campaigns, and a customer intelligence engine that strengthens every decision-making.
