DoppelIQ Enterprise for RetailStop guessing what
shoppers will do next
Build AI twins of your customers from transaction, loyalty, and behavioral data. Simulate ads, messaging, promotions, campaigns, and store decisions to reduce risk, uncover revenue opportunities, and improve customer retention.
Who It's ForBuilt for retail teams who
make decisions on data
DoppelIQ Enterprise is used across four key functions in grocery, hypermarket, and FMCG retail, wherever customer intelligence drives commercial decisions.
Marketing & CRM
Campaign & Growth Teams
Test messages, offers, and creatives on your actual customer twins before going live. Know which version wins before you spend.
- →Ad creative and messaging A/B testing
- →Promotion resonance by segment
- →VIP loyalty and upsell campaigns
- →Win-back campaign simulation
Insights & Analytics
Consumer Intelligence Teams
Replace slow, fragmented reporting with always-on behavioural intelligence. Stop waiting weeks for segment analysis.
- →Automated customer segmentation
- →At-risk flagging
- →Quantitative + qualitative twin surveys
- →Category affinity and penetration maps
Category & Merchandising
Buying & Category Teams
Understand how your highest-value customers shop across 100+ categories. Make range and NPD decisions grounded in real behaviour.
- →New concept and product testing
- →Cross-category expansion modelling
- →Private label vs. brand affinity
- →Seasonal and occasion planning
The ProcessFrom transaction data
to retail intelligence
Four steps from your raw data to decisions you can trust. No surveys, no waiting weeks for reports.
Ingest Your Data
Connect your POS, loyalty, and CRM exports. DoppelIQ validates, cleans, and maps 44+ behavioural attributes per customer, automatically reconciling inconsistencies.
Build Digital Twins
Each customer becomes a living simulation: price sensitivity, brand affinities, discount habits, purchase triggers, and lifecycle stage, all encoded into a dynamic AI model.
Run Simulations
Ask anything in natural language: "Which message converts our Deal Hunter segment?", "If we remove blanket discounts for these 143 customers, what's the margin impact?" Results in minutes.
Act with Precision
Execute campaigns with segment-level confidence. VIP upsells, A/B-tested creatives, at-risk win-backs - each grounded in real behavioural prediction, not averages.
Use CasesThe retail decisions
DoppelIQ makes easier
Explore by function. Each use case maps to a real question your team is already trying to answer.
Test your ad creative before you run it
Run your campaign copy, offer language, or creative concepts against your actual customer twins. Know which resonates before briefing your media agency.
Simulate A/B tests before spending on media
Simulate variants on your customer twin population and predict the winning version across segments. Reduce wasted test-and-learn spend.
Validate new concepts and formats before launch
Test a new private label, loyalty tier, or category entry against your customer twins. Get predicted adoption rates by segment before committing investment.
Find the message that lands for every segment
pillars(value, convenience, quality, or occasion) resonate with each cluster.
Replace guesswork with behaviour-based clusters
DoppelIQ's ML pipeline groups customers purely by how they actually shop, as natural clusters emerge from transaction data alone. No survey bias, no manual tagging.
Maximise VIP customer lifetime value
Simulate cross-category expansion paths for your highest-value customers, with tailored offer timing and sequence to deepen loyalty without over-incentivising.
Stop discounting customers who don't need it
Identify the 30%+ of your base that buys at full price anyway. Avoid blanket promo campaigns that train everyone to wait for a deal — and recover the margin quietly.
Win back at-risk customers before they're gone
Simulate at-risk customers and deploy precisely targeted win-back messages at exactly the right moment..
Understand private label switching potential
Identify which customer segments have the highest propensity to switch to own-brand — and simulate the offer or positioning that accelerates the conversion.
What You NeedWhat data does
DoppelIQ use?
Transaction Data
The core input. Date, SKU, quantity, price paid, discount applied, store ID. DoppelIQ has processed data going back to 2016 — the more history, the richer the twins.
Promotion & Discount History
Which offers each customer received and redeemed. Enables accurate promo-dependency scoring and discount sensitivity modelling.
CRM Demographics (Optional)
Age range, Nationality, location - if available. Enriches twin fidelity but not required. Behaviour data alone is sufficient to build powerful, predictive twins.
Loyalty Programme Data (Optional)
Customer IDs, points balance, redemption history, tier. Connects transactions to a single customer across visits and channels.
50 + behavioural attributes mapped per customer which surfaces automatically from your data
+ more attributes surfaced automatically from your data
Real-World ProofHow a $3.38B supermarket chain
found $274K in 14 days
A leading hypermarket chain in Jeddah, operating hundreds of stores and serving millions of customers, used DoppelIQ to go from fragmented transaction data to a complete customer intelligence engine, uncovering revenue and margin opportunities they didn't know existed.
Industry
Hypermarket / FMCG
HQ
Jeddah, Saudi Arabia
Revenue
$3.38B (2024)
14-Day Results Summary
Achieved using DoppelIQ Enterprise with transaction data only
Your Data, ProtectedEnterprise-grade security for
sensitive retail data
Your customer transaction data is commercially sensitive. DoppelIQ Enterprise is built with security-first architecture from the ground up.
Data Stays Yours
Your transaction and customer data is never used to train shared models. It is used solely to build twins for your organisation. fully isolated by design.
Encryption at Rest & in Transit
All data is encrypted end-to-end, in storage and during transfer. Enterprise deployments support private cloud and on-premise configurations on request.
No Personal Data Required
DoppelIQ builds behavioural twins from anonymised transaction patterns. Names, contact details, and payment data are never required and should not be included.
Role-Based Access Controls
Control exactly who accesses which insights, admin, analyst, and viewer roles with full audit logging to meet enterprise governance requirements.
Data Validation on Ingestion
Every dataset is validated, cleaned, and reconciled for behavioural inconsistencies before twin construction begins, ensuring model accuracy from day one.
Getting StartedUp and running
in four weeks
DoppelIQ Enterprise onboarding is lean and fast.
Discovery Call
Walk us through your data setup, key business questions, and what decisions you want to improve. We scope the engagement and confirm data readiness in an hour.
→ 60-minute call
Data Ingestion & Twin Building
Share a secure export of transaction and loyalty data. DoppelIQ validates, maps attributes, and constructs digital twins for every customer profile in your dataset.
→ 2 weeks
First Insights & Simulation Session
Your team joins live collaborative sessions to fine tune twins, run your first simulations, stress test results and receive a Revenue Opportunity Report with prioritised actions.
→ Day 15–31
DoppelIQ Enterprise for RetailReady to simulate
before you spend?
Book a 30-minute demo and see how DoppelIQ builds digital twins from your data, and what revenue opportunities your customer base is hiding.