How to Scrape Google Maps by ZIP Code and Review Coverage

To scrape Google Maps by ZIP code, combine business keywords with a checked list of postal areas, import the results, then compare unique places and their addresses. Smaller location queries can reveal additional candidates, but they do not establish complete coverage or a strict geographic boundary.

I recommend keeping Place Id, Query and Postal Address in the output. They let you distinguish repeated businesses from newly discovered places and check whether a result belongs to the area you intended to target.

📌 Summary For Those In a Rush

Build a local-business list from checked keyword and ZIP-code searches, then review it before export. Datablist's Google Maps Scraper creates rows with place identifiers, contact fields and the originating query.

Compare unique places across searches, inspect missing and out-of-area records, and budget for returned rows. ZIP-code expansion is a search strategy; it does not promise every business in a city.

Avoid confusing more rows with full coverage

A city-wide query and several postal-area queries can return overlapping results. More imported rows may represent new businesses, repeated branches or the same place found under several keywords. Keep the identifiers before combining the files.

A business can also serve a ZIP code without having its listed address there. Define whether you want businesses physically located inside an area or businesses serving that area. Those are different qualification rules, and a location keyword alone cannot decide them. If you need separate city and country fields from a returned postal address, structure the address with Location Lookup while keeping the original for review.

I would compare three counts: returned rows, distinct place identifiers and accepted businesses after review. This makes the result useful without assigning an unsupported percentage to missing leads.

Prepare a checked location list

Use a postal-service or other authoritative geographic source for your target area. Preserve codes as text so leading zeroes survive. Confirm the city, state or region and country; a bare postal code can be ambiguous across countries.

An AI assistant can suggest an initial list, but it can omit codes, add nearby areas or confuse postal delivery areas with administrative boundaries. Check its suggestions before using them as the source of a coverage claim.

For a small illustrative New York test, you could check locations such as 10001 New York, NY and 10002 New York, NY. This is a sample input, not a complete Manhattan ZIP-code list. Keep the confirmed location list separately so you can explain which areas were searched.

Run a small Google Maps import

Create or open a collection in Datablist. Choose See all sources and select Google Maps Scraper.

Set keywords, locations and language

Enter the business terms in Categories/Keywords, such as plumber and plumbing contractor. Add one checked location per line under Locations. Choose Country and Language for the intended search.

Datablist combines each keyword with each location and country. Two keywords and two locations create four searches. Remove duplicate or irrelevant inputs before multiplying a large list of locations.

Use business terms appropriate to the market, such as idraulico for an Italian plumber search. The language setting and the keyword are separate inputs; choosing a language does not translate every keyword or guarantee all local listings will appear.

Set a per-search limit and inspect the estimate

Scraping Limit per search applies to each keyword/location combination. Start with a small limit, such as 10, while checking the query and fields. Four searches with a limit of 10 permit up to 40 returned rows; they do not promise 40 unique businesses.

The current source charges 4 credits per imported place row. If that illustrative sample returns 40 rows, its source charge is 160 credits. Actual returns may be lower. A separate enrichment can add its own cost; subscription and top-up prices are separate from this arithmetic.

An empty or zero limit is described as “no limit” in the settings, but the current source still applies a maximum of 500 results per search. It does not request every business in an area. Check the estimate and the actual output before expanding the inputs.

Keep fields needed for review

Click Continue and configure the outputs. Include Name, Place Id, Link, Query, Postal Address, Website and Phone Number when useful. Rating, review count, business status and other available fields can support your qualification rule.

Keep Query even if several rows have the same place identifier: it explains how each candidate was found. A review-count field or link to reviews is not the full review text, and an optional contact field can be empty.

Choose Run import now after checking the destination properties and estimate.

Compare overlapping results before scaling

The original walkthrough shows 560 rows from a ZIP-code-based search and 187 from a broader location search. Those screenshots show returned row counts. They do not establish the number of distinct businesses, identical query conditions or the size of the entire market.

For your comparison, keep keywords, country, language, limits and collection date consistent. Compare the set of Place Id values from the broad query with the set from the smaller areas. Inspect identifiers present only in the expanded run and check their addresses and relevance.

Before merging duplicate rows, decide how to preserve the originating queries. A chain can have several legitimate branch locations under one website domain. Do not collapse every shared-domain row into a single business automatically.

For a hypothetical 40-row sample, 26 distinct place identifiers with two out-of-area records would leave 24 accepted places. These numbers illustrate reconciliation, not a measured result from the source.

Export Google Maps results to Excel or CSV

Review missing fields, duplicates, branch identities and the chosen geographic rule. Then open Export and select Excel or CSV. Check the exported column names and row count against the reviewed collection.

For another local-business source, the Yellow Pages plumber walkthrough keeps listing URLs and addresses separate from service-area qualification. Compare branch identities before combining directory and Google Maps rows.

Frequently asked questions

Does searching every ZIP code give 100% coverage?

No. Results depend on the queries, ranking, available listings and source limits. Postal codes also do not necessarily match the administrative boundary or service area you have in mind.

Is a location query a strict ZIP-code filter?

Do not assume it is. Inspect each returned postal address and decide how to handle nearby and service-area businesses. Keep uncertain rows for review instead of labeling them as confirmed local businesses.

Can I extract email addresses or complete reviews directly?

The source's listed outputs include phone, website, rating, review count and a reviews link. They do not promise work emails or full review text. Choose a separate appropriate enrichment only after inspecting the inputs you have.

Is scraping Google Maps always permitted?

Public visibility does not establish permission to collect or reuse data. Review Google Maps' additional terms and, for API use, the applicable Maps Platform terms. Choose an authorized route for your intended use.

What should I do next?

Run a small, checked search. Keep Place Id and Query, review geographic relevance, then export the accepted rows. Increase the scope only when you can explain the additional unique places and their cost.

If the next step is identifying a person at an accepted business, use its reviewed website in the business-owner research workflow. A Maps listing identifies a business; it does not establish who owns or operates it.