Our Services - Top 25 High-Impact Plays
Consulting frameworks + Data Science models we offer to help you grow customers, sales and margin. Explore our curated service portfolio - Built on retail & shopper data.
Know every shopper. Earn every visit.
5 servicesConfident pricing. Clean promo P&L.
5 servicesThe right products, in the right place.
4 servicesSpend less. Sell more. Prove it.
3 servicesForecast better. Stock smarter.
3 servicesStrategy, partnership and what's next.
5 servicesKnow every shopper. Earn every visit. — 5 services
Behavioural and needstate segmentation built on basket, visit and engagement signals.
Probabilistic CLV models that predict 12-36 month value using frequency, recency, basket and engagement features.
Early-warning models flag at-risk shoppers 4-12 weeks before lapse, paired with tested win-back journeys.
End-to-end loyalty design covering value proposition, tiering, earn-burn economics, partner ecosystem.
ML-ranked offer engine that selects the right product, discount and channel for each shopper.
Confident pricing. Clean promo P&L. — 5 services
SKU-level own and cross elasticities estimated from transaction data, including substitution and halo effects.
Baseline-vs-uplift decomposition of every promotion to separate incremental sales from cannibalisation.
Dynamic markdown engine that times depth and breadth of discounts against sell-through curves and residual value.
Web-scraped, normalized competitor price feeds joined to internal SKU and KVI maps.
Strategic price architecture built around key-value items, key-value categories and price-role tiers.
Forecast better. Stock smarter. — 3 services
Hierarchical ML forecasts at SKU-store-day level, blending trend, seasonality, weather, events and promotional calendars.
Service-level-aware safety stock and reorder logic that balances availability, waste and cost.
Behavioural and demographic clustering of stores to drive differentiated range, price, space and service propositions.
Strategy, partnership and what's next. — 5 services
End-to-end category strategy: role, drivers, shopper missions, range, price, promo and space.
Data-led JBP frameworks with shared KPIs, agreed scorecards, and analytics packs.
Basket-level decomposition into trip missions (top-up, big shop, food-now, treat) with cross-mission migration.
Build of a retail media proposition: audience platform, onsite ad placements, measurement and supplier self-service.
Natural-language copilot over trading, customer and supplier data so a buyer can ask what changed in my category.