Use case · Retail, FMCG and BFSI

Micro-market decisions, below the census

The census tells you the district. It cannot tell you the catchment around one candidate site. SmartData fills that gap with ward-level demographics, urban market profiles, footfall and a 30M+ POI layer, so the decision sits on the street, not the district average.

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The SmartData population layer over Mumbai as a fine grid, one cell selected showing total population and its split by age and gender
Population over Mumbai on the urban grid, in the Lepton data application. One cell returns its own total and the split by age and gender.

The decision

The census stops where the decision starts

Every site, territory and branch decision comes down to one question: who actually lives, works and moves around this exact location? For FMCG, retail and BFSI analytics teams, census-level data is too coarse for micro-market decisions. It can describe a district, but the choice between two candidate sites a kilometre apart is made on the street, not the district average.

So the gap gets filled with assumptions: a rough radius, a gut sense of the neighbourhood, a number borrowed from a larger area. The decision sits on guesswork at exactly the resolution where it costs the most to be wrong.

What a micro-market actually needs

Resolution below the district

  1. 01

    Ward-level, not district-level

    City Ward demographics resolve the population beneath the census, so a catchment reads on the ward it sits in rather than the district average around it.

  2. 02

    An urban market read per town

    The Urban Market Profile carries more than 200 variables across 7,795 towns, turning a location into a profile of the market around it, not just a head count.

  3. 03

    A 100m grid in urban India

    The Footfall index resolves to a 100m grid in urban areas and a 500m grid in rural ones, so the busy corner reads differently from the quiet one a block away.

  4. 04

    What is already on the ground

    A primary-surveyed layer of 30M+ points of interest, including 1,09,000 QSR outlets with cuisine-level attributes, shows what already trades inside the catchment before you commit to it.

The mechanism

Draw the catchment, read what is inside it

The Catchment and Nearby APIs turn a candidate location into a defined trade area on the map, then read the demographics, market profile, footfall and points of interest that fall inside it.

One coordinate becomes a scored micro-market: who is around it, how busy it is, and what already competes for them, on layers built from primary field survey rather than guesswork.

The layers behind the decision

India ground truth, at micro-market resolution

These are not estimates stretched over a wide footprint. The Socioeconomic category carries the Urban Market Profile, City Ward demographics, India GDP and the Footfall index, and they sit on the same primary-surveyed foundation as the 30M+ POI layer. The decision reads on ground truth at the resolution it is actually made.

200+ variables in the Urban Market Profile, across 7,795 towns
1,663 wards in City Ward demographics, below the census
100m footfall grid in urban India, 500m in rural
30M+ points of interest, including 1,09,000 QSR outlets
The SmartData income layer over Sectors 24 to 26 in Gurugram as a grid, one cell selected showing average monthly income and the high, middle and low income group shares
Income over Sectors 24 to 26, Gurugram. Each cell carries an average monthly income and the share of high, middle and low income households inside it, which is the resolution a site decision is actually made at.

Honest about freshness

Built from survey, refreshed every year

Every layer here begins as primary field survey, not crowd-sourced or algorithmically inferred, and the portfolio is refreshed on an annual cycle. That is the right cadence for site and territory decisions, where the question is the shape of a market rather than this morning's traffic. Where you need a live read, the same APIs let you query the current state on demand.

  1. 01

    Score sites, not regions

    Two candidate locations a kilometre apart get two distinct catchments, scored on the demographics, footfall and competition that actually surround each one.

  2. 02

    Cut the cannibalisation risk

    The 30M+ POI layer shows what already trades inside a catchment, so a new branch or outlet is placed against real competition, not a blank map.

  3. 03

    One India, one method

    The same survey-built layers cover 7,795 towns the same way, so a market in one city is read on the same footing as a market in another.

Proof

India data trusted at national scale

The world's leading mapping platforms license India data from Lepton, and the same survey backbone underpins public-sector mandates with Railtel and NIC, including a 40,000+ km NOFN infrastructure survey and the enhancement of 4,08,563 sq km of map to 1:10,000. The ground truth behind a catchment decision is the ground truth behind the map.

700+ customers worldwide build on SmartData data and APIs
40,000+ km surveyed on public-sector mandates with Railtel and NIC
Get started

Score your next sites on India ground truth.

Bring a shortlist of candidate locations, and we will show you the catchment, demographics and footfall around each one on SmartData.

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