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Dataforest

enhanced

Automated Google Maps Data Collection Platform

MNDA

Enterprise/Corporation
Company Type
LA, United States
Location
Project work
Engagement Model
6 - 10 people
Team Size
6 - 9 Months
Duration
$50K - $100K
Budget

About

We built a custom Google Maps scraping solution for a U.S.-based data intelligence and marketing advisory firm, enabling independent collection of publicly available business data across the U.S. The system performs targeted searches, captures relevant listings and URLs, and processes data through a structured pipeline for cleaning and normalization, giving the client full control over freshness, structure, and scalability.

Challenge, approach, and impact

Scalable, Cost-Efficient U.S. Business Data Enrichment

The client depended on third-party providers delivering incomplete U.S. business records with limited attributes. Manual enrichment was slow and expensive, while the business required regularly updated, detailed datasets at national scale to support marketing intelligence and consulting insights. They needed a scalable, automated way to collect and manage reliable business data independently.

How we built

Data Analytics and Visualization

Testimonials

Anonymous

Verified Testimonial

At DATAFOREST, we designed and implemented a scalable Google Maps data collection pipeline that gave the client full control over U.S. business data enrichment. By automating scraping, cleaning, deduplication, and monthly updates, we replaced costly third-party providers with a reliable, self-updating intelligence system delivering up to 70% market coverage.

Team structure

Client team

Client

Product Owner

The client stakeholders were working closely with the team at Dataforest

Agency team

Data Engineer

Production

Product Manager

Production

Business Analytics

Production

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