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.
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
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.
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.
45 high-value customers showed strong cross-category affinity to a targeted upsell strategy.
without hurting sales. Selective discounting was utilized for 68% of customers who were highly promotion-dependent.
Simulated win-back campaigns showed measurable recovery for 103 inactive customers.
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.
Research explains attitudes, motivations, and stated preferences.
Digital twins capture actual behaviour, purchasing patterns, discount sensitivity, and lifecycle shifts.
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.
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.