LARGE-SCALE DATA ACQUISITION
Ability to scrape, sort, and verify structured business data at city level — across multiple categories simultaneously.
Enabling Scalable Hyperlocal Merchant Discovery Across a Pan-India Ecosystem
Leading Hyperlocal Commerce Platform India
Data Intelligence , Customer Acquisition
Leading Hyperlocal Commerce Platform India
On-Demand Delivery & Merchant Ecosystem
CRM Tech & Data Scraping Partner
70+ cities across India
THE SITUATION
A leading Indian on-demand convenience platform was expanding its hyperlocal delivery ecosystem by onboarding thousands of local merchants — grocery stores, meat shops, pharmacies, apparel retailers, and pet stores — across India. The manual onboarding process was slow, inaccurate, and impossible to scale. The client needed a data-first partner to build a verified, city-level merchant intelligence engine that their sales teams could act on immediately.
WHAT INTIN DID
1
APPROACH
Strategic Problem Segmentation & Approach Design
- Analysed the operational burden of manual merchant onboarding and redesigned the approach
- Broke the challenge into automated, category-level data acquisition workstreams that could run in parallel across geographies
2
SCRAPING
Precision Data Scraping at Scale
- Deployed specialised data scraping capabilities across multiple merchant categories — covering food, personal care, household services, and retail segments
- Operated at street and locality level across a defined radius per city
3
DELIVERY
Data Verification & Intelligent Structuring
- Delivered verified merchant listings with contact details, WhatsApp, location data, and business identifiers
- Sorted by business size and potential so the client's teams could prioritise high-value merchant outreach from day one
4
ROLLOUT
Phased Rollout — Pilot to Pan-India
- Began with a controlled pilot across select cities to validate data quality and accuracy before scaling
- Scaled the full methodology to a Pan-India rollout, delivering large, verified datasets per city within rapid turnaround windows
RESULTS DELIVERED
70+
Cities covered in the Pan-India rollout
15,000+
Verified merchants identified per city
10+
Business categories mapped & structured
4–6 days
Average dataset turnaround per city
CAPABILITIES THIS ENGAGEMENT DEMONSTRATES
CATEGORY INTELLIGENCE
Deep mapping of local merchant ecosystems across diverse business segments to support hyperlocal expansion.
VERIFIED DATA DELIVERY
Structured datasets with contact verification and business profiling — ready for immediate CRM and outreach use.
PHASED, SCALABLE EXECUTION
Pilot-to-rollout delivery model that validates quality before scaling, reducing risk across large geographic programs.
MERCHANT NETWORK ENABLEMENT
Converting fragmented public data into a structured merchant intelligence asset — a permanent foundation for ecosystem expansion.
SPEED & TURNAROUND
Fast, multi-stream data processing that replaces slow manual audits with a scalable, repeatable acquisition engine.
Pilot Validated
Controlled pilot across select cities validated data quality and accuracy
✓ DeliveredPan-India Rollout
Full methodology scaled to 70+ Indian cities
✓ Delivered10+ Categories Mapped
Food, personal care, household services, retail, and more structured per city
✓ DeliveredCRM-Ready Datasets
All records delivered structured for immediate sales team activation
✓ Delivered""INTIN converted fragmented, unstructured public data into a verified, revenue-sorted merchant intelligence asset — giving the client a scalable foundation for hyperlocal expansion that no manual process could replicate.""
CHALLENGES IDENTIFIED
MANUAL ONBOARDING AT SCALE
The existing manual merchant onboarding process was slow, inaccurate, and impossible to scale across 70+ cities.
DATA FRAGMENTATION
Merchant information was scattered across public directories with no structured, verified, or prioritised format.
SPEED OF EXECUTION
The platform's expansion timeline demanded rapid, high-volume data delivery with no margin for quality errors.