Consumer & Brand
Hyperlocal Intelligence
Pin-code level neighborhood data — demand, store density and local pricing for the blocks where decisions actually happen.
// resolved down to pin-code catchments
| pincode | area | demand_idx | stores | avg_price |
|---|---|---|---|---|
| 560038 | Indiranagar | High | 42 | ₹312 |
| 560095 | Koramangala | High | 51 | ₹298 |
| 560066 | Whitefield | Medium | 37 | ₹305 |
Overview
What is hyperlocal intelligence?
Hyperlocal intelligence is food and grocery market data resolved to the neighborhood or pin-code level — demand, store and dark-store density, and local pricing. It zooms past city averages to the catchments where customers actually order and stores actually compete.
City-level dashboards smooth away the differences that decide outcomes. Demand, competition and willing-to-pay can swing sharply between two pin-codes a few kilometers apart. For expansion, hyperlocal marketing and dark-store planning teams, that block-level truth is the difference between a store that thrives and one that struggles. Hyperlocal intelligence surfaces demand profiles, store density and price variance by catchment, so site selection, targeting and network design rest on where people are, what they buy, and what they pay — not on a market-wide guess. It is built from live data across 15 markets and resolved to the catchments you care about.
Capabilities
Zoom in to the block
National dashboards hide local truth. We surface it.
Pin-code rollups
Demand and supply aggregated to pin-code catchments.
Neighborhood demand
What sells where, block by block.
Store density
Outlet and dark-store concentration by area.
Local pricing
Price variation across neighborhoods, not just cities.
Demand indexing
A comparable demand score per catchment.
Catchment mapping
Define and compare custom delivery catchments.
What's included
Every hyperlocal feed ships with
Standard fields and outputs. Anything here can be extended, trimmed or customized to your scope.
Methodology
How does hyperlocal intelligence work?
From scattered signals to block-level clarity, in four steps.
1 · Define catchments
You choose the cities, pin-codes or custom catchments.
2 · Aggregate signals
Demand, supply and pricing are rolled up per area.
3 · Index & compare
Each catchment gets comparable demand and density scores.
4 · Deliver
Profiles arrive as CSV, JSON or API.
Who it's for
Get answers like
Real questions our hyperlocal feed answers for teams across the food economy.
"Where should the next store go?"
Demand and density by pin-code.
"Which areas convert?"
Neighborhood demand profiles.
"What catchment to serve?"
Catchment-level demand maps.
Why FoodDataScrape
Why teams choose us for this
- Resolved to pin-code catchments, not city averages
- Demand, density and pricing in one profile
- Comparable demand index across catchments
- Free proof-of-concept on your target areas
Delivery & integration
How is the data delivered?
Formats
CSV, JSON or direct API — pick what plugs into your stack. Custom schemas on request.
Refresh cadence
One-time pull, daily, weekly or real-time feeds, scoped to how fast your decisions move.
Integration
Drop into BI tools, data warehouses or apps. Webhooks and scheduled exports supported.
Questions
Frequently asked questions
Down to pin-code catchments, with demand, density and pricing rolled up per area.
Yes — demand and competitor density by pin-code support site selection.
Often yes — we surface local price variance that city-level views miss.
Yes — define your own catchments and we will aggregate to them.
All 15 markets we cover, with custom regions on request.
As CSV, JSON or API on your cadence.
Get block-level clarity
Name the cities or pin-codes. We'll return a free sample hyperlocal profile.
