Automated Google Maps Scraping for U.S. Business Data

How a U.S. Data Intelligence Firm Automated Google Maps Data Collection

We built a custom Google Maps scraping solution that allows the client - a U.S.-based data intelligence and marketing advisory firm, to independently collect publicly available business data across the U.S. The system performs targeted company searches, identifies relevant listings and URLs, and processes the data through a structured pipeline for cleaning, normalization, and delivery. This approach gave the client full control over data freshness, structure, and scalability.

Advertising Services

Data Scraping

Business process automation

60–70

business coverage achieved across targeted U.S. regions and categories

IDM is a U.S.-based data intelligence and marketing advisory firm with over 20 years of experience in developing account-based marketing strategies. The company works with large enterprises, including Fortune 500 organizations, delivering custom data solutions that support advanced analytics, precise market segmentation, and data-driven marketing decision-making.

Aiohttp

Lxml & Regex

Geopy

PostgreSQL

Loguru

THE CHALLENGE

Building a Scalable and Cost-Efficient Way to Enrich U.S. Business Data with Reliable, Up-to-Date Attributes

The client relied on third-party data providers but received incomplete business records with a very limited set of parameters. To gain more control and data depth, they decided to collect and manage the data themselves. Manual enrichment proved slow and expensive, while the business required regularly updated, detailed datasets at scale to support marketing insights,and consulting recommendations for U.S. companies.

Explore how automated Google Maps data collection can power your market intelligence

THE SOLUTION

Automated Google Maps Data Collection and Enrichment Pipeline

We built an automated Google Maps–based data collection pipeline designed to operate at national scale.

The solution performs targeted company name searches via Google Maps, identifying and collecting relevant business listings and URLs across the United States. This stage focuses on accurate discovery and coverage, deliberately excluding the parsing or storage of extended Google attributes to ensure speed, stability, and controlled data scope.

Scalable Scraping and Data Processing Architecture

The system uses an automated scraper with geo-based search, category targeting, and anti-ban mechanisms. Raw data is cleaned, deduplicated, and standardized before being stored in PostgreSQL, ensuring high data quality and consistent business attributes at scale.

Automated Delivery, Updates, and Client-Ready Data Exports

The pipeline includes automated CSV exports and scheduled monthly updates, eliminating manual effort. End-to-end testing, monitoring, and documentation ensure reliable operation, transparent results, and a cost-efficient alternative to traditional data providers.

THE RESULT

Key Results

The automated pipeline enabled the client to independently collect and refresh U.S. business data at scale, achieving 60–70% coverage of targeted businesses via Google Maps. Compared to third-party providers, the solution significantly increased data depth and freshness while eliminating manual verification costs. Monthly automated updates replaced slow, expensive enrichment workflows, allowing IDM to deliver more accurate segmentation, faster marketing insights, and higher-quality consulting recommendations using consistently up-to-date datasets

60-70%

business coverage achieved across targeted U.S. regions and categories

Automated Google Maps Data Collection for a U.S. Intelligence Firm

Steps of providing data scraping services

Step 1 of 5

Free consultation

It's a good time to get info about each other, share values and discuss your project in detail. We will advise you on a solution and try to help to understand if we are a perfect match for you.

Step 2 of 5

Discovering and feasibility analysis

One of our core values is flexibility, hence we work with either one page high level requirements or with a full pack of tech docs. At this stage, we need to ensure that we understand the full scope of the project. Receive from you or perform a set of interviews and prepare the following documents: list of features with detailed description and acceptance criteria; list of fields that need to be scraped, solution architecture. Ultimately we make a project plan which we strictly follow. We are a result-oriented company, and that is one of our core values as well.

Step 3 of 5

Solution development

At this stage, we develop the scraping engine core logic. We run multiple tests to ensure that the solution is working properly. We map the fields and run the scraping. While scraping, we keep the full raw data so the final model can be enlarged easily. Ultimately we store data in any database and run quality assurance tests.

Step 4 of 5

Data delivery

After quality assurance tests are completed, we deliver data and solutions to the client. Though we have over 15 years of expertise in data engineering, we expect client’s participation in the project. While developing and crawling data, we provide midterm results so you can always see where we are and provide us with feedback. By the way, a high-level of communication is also our core value.

Step 5 of 5

Support and continuous improvement

We understand how crucial the solutions that we code for our clients are! Our goal is to build long-term relations, so we provide guarantees and support agreements. What is more, we are always happy to assist with further developments and statistics show that for us, 97% of our clients return to us with new projects.