Clarity Across Every Catchment
Kogenta Connect for Retail.
The Challenge: Competing for Footfall in a Changing Landscape
Retailers today operate in one of the most dynamic and competitive environments in history. Shifting consumer habits, online competition, and evolving high streets make it harder than ever to decide where to open, close, or optimise stores.
The challenges are familiar:
- Unclear catchment boundaries and overlapping trade areas between sites
- Limited visibility into how people move between competing retail zones
- Difficulty measuring local spending power and leakage
- Fragmented datasets across property, marketing, and sales systems
- Reactive decision-making driven by historical sales, not predictive insight
Without accurate, current, and comparable data on people and place, even the best retail strategy can fall short.
The Solution: Kogenta Connect for Retail.
Kogenta Connect provides retailers, landlords, and retail analysts with a single, high-fidelity data foundation to understand how people live, move, and spend across every location.
Built on the Kogenta Grid — a consistent hexagonal spatial framework — it layers mobility, demographics, expenditure, and contextual data to deliver precise, privacy-safe retail intelligence.
Whether you’re planning new stores, analysing competitor locations, or optimising marketing investment, Kogenta Connect gives you the clarity you need to act with confidence.
Key Data Layers for Retail Insight.
Busyness Layer
A rich, AI-driven view of how busy different areas are – hour by hour, day by day, hex by hex. By fusing multiple independent signal sources into a unified model, this layer infers real-world human activity with exceptional accuracy and consistency. No single dataset dominates the output, ensuring robust, balanced insights that can be confidently compared across locations.
Forecasted Busyness Layer
A forward-looking model that predicts human activity at an hourly level across every H3 cell on the grid. Using advanced AI to learn behavioural patterns, fill data gaps, and synthesise historical trends, this layer enables planners and analysts to see not just what is happening – but what is likely to happen next.
Origin–Destination Flow Layer
Understand actual population movement into, around, and between retail areas — defining true catchments and overlaps. An AI-enhanced, multi-modal model of movement between origins and destinations. Built on multi-modal network structures and trained on validated transport data, this layer delivers high-fidelity OD flows that reflect the real dynamics of how people travel—across modes, times, and regions.
Places Layer
Map competitor locations, complementary retailers, and destination drivers like transport, restaurants, or entertainment venues. Catalogues commercial, civic and transport locations — shops, venues, schools, stations, and more — linking people movement to the points of interest in a location.
Demographics Layer
Profiles populations across age, household type, income, education and occupation — giving context to who resides in an area. Combined with Movement data, a powerful picture emerges of the demographics of the people travelling into, through and out of an area.
Expenditure Layer
Quantify local spending power and category-level expenditure to identify strong and weak trading zones. Maps household and consumer spending across multiple categories — from groceries and entertainment to travel and luxury goods — providing deep insight into local purchasing power. When combined with Movement data a powerful view of the expenditure habits of the people travelling into, through and out of an area emerges.
1st Party Data Layer
Your Client provided data can be included and harmonized with all other data layers. Typically, this includes data such as customer data, purchase frequency, store locations, store visit data, sales figure, POS data, etc. This data can be matched or modelled with other Kogenta Connect data layers.
Survey Layer
Add local attitudinal insights — measuring satisfaction, preference, or brand awareness in key catchments. Blends large-scale survey responses and opt-in data with behavioural signals, adding qualitative understanding to quantitative data. Sourced from reputable market research partners or directly by our own survey engine.
The Business Benefits.
Accurate Catchments — Understand exactly who each store serves- Competitor Comparisons — Quantify overlap, leakage, and opportunity zones
- Optimised Store Networks — Open, close, or relocate with confidence
- Data-Driven Growth — Forecast demand using real behaviour and spend data
- Privacy-Safe Insight — Fully aggregated, GDPR-compliant datasets
- Comparable Across Markets — Same methodology across Europe, North America, Asia and Australia
