Google Local Pack API: How to Collect Local Business Results

When users search for local services on Google, they often see a group of business listings near the top of the search results page.

This section is commonly called the Google Local Pack.

For searches like “dentist near me,” “coffee shop in Austin,” “emergency plumber Chicago,” or “best Italian restaurant Brooklyn,” the Local Pack may show business names, ratings, review counts, addresses, websites, phone numbers, opening hours, and map-related links.

For users, it is a quick way to choose a local business.

For SEO teams, agencies, lead generation teams, market researchers, and AI products, it is a source of structured local business data.

That is where a Google Local Pack API becomes useful.

A Google Local Pack API helps collect local business results from Google Search and return them as structured data that can be stored, analyzed, compared, and used in applications.

A practical workflow looks like this:

Local keyword
↓
Target location
↓
Google Local Pack result collection
↓
Structured local business results
↓
Local SEO, competitor tracking, lead generation, market research, and AI workflows

This guide explains what a Google Local Pack API is, what data it can return, how to collect local business results, and how TalorData can support this workflow.

What Is the Google Local Pack?

The Google Local Pack is a local business result section that may appear in Google Search when the query has local intent.

A Local Pack usually includes several business listings and a map-style layout.

Common Local Pack searches include:

• dentist near me
• coffee shop in Austin
• plumber Chicago
• hotel near Central Park
• best sushi restaurant in Seattle
• car repair shop near me
• law firm in Dallas

A Local Pack result may show:

The Local Pack is important because it often appears above traditional organic results.

For local businesses, appearing in the Local Pack can be more valuable than ranking lower in organic results. Lovely, another reminder that “ranking number one” is not always as simple as humans wish it were.

What Is a Google Local Pack API?

A Google Local Pack API is an API workflow that collects Google Local Pack results and returns them in a structured format.

It is usually used to answer questions like:

• Which businesses appear for this local keyword?
• Which business ranks first in this city?
• Which competitors appear in the Local Pack?
• How many reviews does each business have?
• Which businesses have websites?
• Which businesses appear across multiple locations?
• How did Local Pack rankings change over time?

A simplified API request may look like this:

{
  "engine": "google",
  "q": "dentist near me",
  "location": "Austin, Texas, United States",
  "language": "en",
  "device": "mobile"
}

A simplified Local Pack result may look like this:

{
  "position": 1,
  "business_name": "Example Dental Clinic",
  "category": "Dentist",
  "rating": 4.8,
  "review_count": 326,
  "address": "123 Main Street, Austin, TX",
  "phone": "+1 512-000-0000",
  "website": "https://www.exampledental.com",
  "hours": "Open until 6 PM",
  "result_type": "local_pack"
}

Instead of manually searching Google and copying business listings one by one, teams can collect Local Pack results programmatically.

Google Local Pack API vs Google Maps API vs Places API

These terms are often confused, so it is worth separating them.

A Google Local Pack API focuses on what users see in Google Search for a local query.

That makes it useful for local visibility analysis, because it captures the competitive search result page, not just a single business record.

The simple distinction is:

Places API helps you work with place data.
Google Local Pack API helps you monitor local search visibility.

Tiny difference. Massive reporting consequences.

Why Collect Google Local Pack Results?

Local Pack data is useful because it shows the businesses Google displays for local intent searches.

Common use cases include:

Local Pack data helps answer questions such as:

• Who ranks for “dentist near me” in Austin?
• Which restaurants dominate Brooklyn local results?
• Which plumbers appear across multiple neighborhoods?
• Which local businesses have high ratings but no website?
• Which competitors gained visibility this month?
• Which locations are crowded with similar businesses?

Without structured data, teams usually rely on manual searches and screenshots. The ancient ritual of “I checked it myself” continues to haunt civilization.

What Data Can a Google Local Pack API Return?

A good Local Pack API should return both search context and business result data.

Search Context Fields

Local Business Result Fields

If you want to monitor changes, always store the collection time. Without timestamps, you do not have monitoring. You have loose observations wearing a fake mustache.

Step 1: Choose Local Keywords

Start with local keywords that match the business category or service you want to analyze.

Useful keyword types include:

Service Keywords

• dentist near me
• emergency plumber
• roof repair company
• moving company near me

Category Keywords

• coffee shop
• Italian restaurant
• fitness center
• pet grooming

Location-Specific Keywords

• dentist in Austin
• coffee shop in Brooklyn
• plumber in Chicago
• hotel near Central Park

Commercial Local Keywords

• best dentist in Austin
• top-rated restaurant in Seattle
• affordable moving company Dallas
• best car repair shop near me

A simple keyword list may look like this:

dentist near me
dentist in Austin
best dentist in Austin
emergency dentist Austin
dental clinic Austin

Group keywords by category and intent.

Start focused. A clean keyword set is more useful than a giant keyword dump pretending to be strategic.

Step 2: Choose Target Locations

Local Pack results depend heavily on location.

The same keyword can show different businesses in different cities, neighborhoods, ZIP codes, or coordinate points.

Common location levels include:

For broad market research, city-level tracking may be enough.

For serious local SEO, coordinate-level tracking is often more useful because rankings can change across neighborhoods.

Example location setup:

The more local the search intent, the more precise your location settings should be.

Step 3: Collect Local Pack Results

Once you have keywords and locations, collect Google Local Pack results.

Example request:

{
  "engine": "google",
  "q": "coffee shop",
  "location": "Austin, Texas, United States",
  "language": "en",
  "device": "mobile"
}

Simplified response:

{
  "query": "coffee shop",
  "location": "Austin, Texas, United States",
  "local_pack_results": [
    {
      "position": 1,
      "business_name": "Example Coffee House",
      "category": "Coffee shop",
      "rating": 4.7,
      "review_count": 812,
      "address": "456 Market Street, Austin, TX",
      "phone": "+1 512-111-1111",
      "website": "https://www.examplecoffee.com",
      "hours": "Open until 8 PM"
    },
    {
      "position": 2,
      "business_name": "Downtown Brew",
      "category": "Coffee shop",
      "rating": 4.5,
      "review_count": 519,
      "address": "789 Congress Ave, Austin, TX",
      "phone": "+1 512-222-2222",
      "website": "https://www.downtownbrew.example",
      "hours": "Open until 7 PM"
    }
  ]
}

Collect the full Local Pack result set, not only the first business.

The full result set allows you to compare competitors, ratings, websites, review counts, and ranking changes.

Step 4: Store Results as Snapshots

Local Pack results change over time.

A business may move from position 5 to position 2. A competitor may disappear. A new business may enter the Local Pack. Ratings and review counts may change.

To monitor this, store snapshots.

A useful table structure includes:

Snapshots allow you to compare:

• Today vs yesterday
• This week vs last week
• This month vs last month
• City A vs city B
• Neighborhood A vs neighborhood B
• Mobile vs desktop
• Business A vs business B

Without snapshots, you only know what is visible now. With snapshots, you can measure change.

Step 5: Normalize and Deduplicate Businesses

Local business data can contain variations.

The same business may appear as:

Example Coffee House
Example Coffee House Austin
Example Coffee House - Downtown

These may refer to the same business.

Useful normalization steps include:

This step is not glamorous. It is also where usable data is born. Naturally, the important part is the boring part. Humanity remains on brand.

Step 6: Analyze Local Pack Rankings

Once your data is clean, you can analyze local rankings.

Useful metrics include:

Example ranking comparison:

This helps local SEO teams understand who is gaining and losing visibility.

Step 7: Analyze Ratings, Reviews, and Trust Signals

Local Pack results often include ratings and review counts.

These fields can help compare business trust signals.

Useful analysis includes:

Example insights:

• A business with 4.9 stars and 35 reviews may have strong satisfaction but low review volume.
• A business with 4.4 stars and 2,000 reviews may have stronger market presence.
• A competitor with lower ratings but better ranking may have stronger proximity, relevance, website signals, or category fit.

Ratings do not explain everything, but ignoring them is equally foolish. Naturally, humans do both.

Step 8: Analyze Website and Contact Coverage

Local Pack results can also reveal whether businesses have websites and phone numbers.

Useful checks include:

• Does the business have a website?
• Does the business show a phone number?
• Is the website an official domain?
• Is the business using a third-party profile instead of its own website?
• Do multiple branches share the same website?
• Is the website outdated or missing HTTPS?

This helps with:

Raw contact data should be verified before outreach. “Found it online” is not a compliance strategy, though many have bravely tried.

Step 9: Compare Local Pack Results Across Locations

Local Pack rankings can vary dramatically by location.

A business may rank well downtown but disappear in another neighborhood.

Useful comparison questions include:

• Which businesses dominate each city?
• Which businesses appear across multiple neighborhoods?
• Which locations have the strongest competition?
• Which areas have many low-rated businesses?
• Which areas have high demand but fewer visible providers?
• Which chains appear everywhere?
• Which independent businesses rank locally?

Example comparison:

This is useful for local SEO, store expansion, franchise planning, and competitive market analysis.

Step 10: Use Local Pack Data for Reports and Alerts

Local Pack data becomes more useful when turned into reports and alerts.

Useful report sections include:

Useful alerts include:

Example Coffee House dropped from position 2 to position 6 for “coffee shop” in Downtown Austin.
A new competitor entered the Local Pack for “dentist near me” in Austin.
A competitor gained 120 new reviews this month.
Your business disappeared from Local Pack results in South Austin.

Good alerts should be useful, not noisy. Nobody needs a system that screams every time a ranking sneezes.

Step 11: Use Local Pack Data for AI Workflows

AI agents and RAG systems can use Local Pack data as fresh local search context.

Useful AI workflows include:

A safe AI workflow looks like this:

Collect Local Pack results.
Normalize business data.
Filter relevant businesses.
Verify important fields.
Select source URLs.
Use verified data in AI or RAG workflows.

Local Pack data should be treated as search context, not final truth. Business information can change. Verify important details before using them in sales, reports, or decisions.

How TalorData Helps Collect Google Local Pack Results

TalorData can act as the structured SERP data layer for collecting Google Local Pack results.

Instead of manually searching Google and copying local business listings, teams can use TalorData to collect structured results by keyword, country, language, location, and device.Try 1000 API Requests Now>>

A practical TalorData workflow looks like this:

Local keywords
↓
Target locations
↓
TalorData SERP API
↓
Structured Local Pack results
↓
Database, dashboard, CRM, AI agent, or SEO report

TalorData supports workflows such as:

The value is repeatability. Teams can collect comparable Local Pack data over time, store snapshots, and measure local visibility changes instead of relying on manual searches and screenshots.

Final Thoughts

A Google Local Pack API helps teams collect local business results from Google Search in a structured and repeatable way.

It can support local SEO, competitor monitoring, lead generation, market research, agency reporting, store expansion, AI agents, and RAG workflows.

The basic process is simple:

Choose local keywords.
Choose target locations.
Collect Local Pack results.
Extract business fields.
Store snapshots.
Clean and normalize the data.
Analyze rankings, reviews, websites, competitors, and locations.
Build reports, alerts, lead lists, dashboards, or AI workflows.

Google Local Pack results show which businesses users can find.

Structured Local Pack data shows how that visibility changes, which competitors are winning, and where local opportunities exist.

FAQ

What is a Google Local Pack API?

A Google Local Pack API collects local business results from Google Search and returns structured data such as business names, rankings, ratings, reviews, addresses, websites, phone numbers, categories, and opening hours.

What is the Google Local Pack?

The Google Local Pack is a local business result section that may appear in Google Search when a query has local intent, such as “dentist near me” or “coffee shop in Austin.”

What can I use Local Pack data for?

Common use cases include local SEO tracking, competitor monitoring, lead generation, market research, agency reporting, store expansion, and AI workflows.

What fields should I collect from Local Pack results?

Start with keyword, location, country, language, device, timestamp, position, business name, category, rating, review count, address, phone number, website, map link, and result type.

Is Local Pack data useful for AI agents?

Yes. Local Pack data can help AI agents compare businesses, summarize local markets, select source URLs, and support local SEO or lead generation workflows.