Commercial analytics and eye-tracking diagnostics for a fuel-retail gastro network
Multi-site fuel station network operating an in-house food & beverage (“gastro”) business — hot beverages, pastry, fresh items, and made-to-order or packaged sandwiches — across several station clusters nationwide.
Confidential case study — anonymized. Full details available under NDA upon request.
Internal commercial records combined with field visits to own and competitor stations, plus eye-tracking of customers and staff.
SKU-level sales/margin/Pareto analysis, supplier concentration review, and eye-tracking attention mapping benchmarked against a competitor.
Scored product portfolio, costed planograms, promo calendar, buying KPI framework, and operational manual — piloted at select stations.
| Objective Finding | Measured Value |
|---|---|
| Share of sales held by the higher-margin, on-site-production station cluster (2023 vs. 2025) | 56% → 54%, with the pre-packaged-sandwich cluster rising from 37% to 39% |
| SKUs with marginal contribution to fast-food category sales/margin in the production cluster | ≈ 70% of SKUs each contributed under 15% of combined category sales and margin |
| Sales concentration in the pre-packaged-sandwich cluster | 22 SKUs (36% of items) generated 94% of category sales |
| Pastry category SKU concentration | Top 5 products generated over 62% of total pastry sales; half of SKUs generated 99% |
| Customer visual-attention scores at pilot stations (eye-tracking, 15 sessions) | ≈ 29%–48% range, pointing to unclear product structure and layout |
| New product scoring for the seasonal/permanent portfolio (weighted scoring model) | Majority of tested products scored 86–100%; lowest-performing item scored 71% |
| Recommendation | Rationale / Expected Impact |
|---|---|
| Portfolio rationalization: retain top-performing SKUs, consolidate marginal-contribution items | Removes the ≈70% of low-contribution SKUs while protecting concentrated sales/margin |
| Supplier consolidation for top-selling categories | Targets the fragmented supplier structure limiting purchasing leverage |
| Standardized, fully costed planograms (chilled & ambient), piloted at select stations | Replaces station-by-station “working by feel” with one repeatable standard |
| New seasonal/permanent portfolio, selected via a weighted scoring model | Built from measured SKU-level sales and margin data, not opinion |
| In-store layout changes based on eye-tracking findings | Targets zones measured at only 29–48% customer attention |
| Quarterly promo calendar tied to defined commercial objectives | Replaces ad hoc promotions with a plan mapped to measured gaps |
| Buying-team KPI framework (weighted, 4 indicators) | Provides the performance-measurement system that did not exist before |
The difference from a standard category-management project was combining two lenses on the same problem that are usually kept separate: back-office commercial data (SKU-level sales, margin, and supplier analysis) and front-of-house behavioral data (eye-tracking of customers and staff, benchmarked against a competitor). Portfolio decisions were not based on which products management assumed were performing, but on measured sales and margin concentration — and every recommendation delivered was traceable back to a specific, quantified finding from the discovery phase.