Make.com Tutorial: Automate Google Maps Lead Generation Without Code (2025)

Your sales team spends 6 hours a day finding prospects on Google Maps. They copy names, phone numbers, emails into spreadsheets. Half the data is outdated. No one's happy.

What if that entire process ran on autopilot while you slept?

This guide shows you exactly how to build a no-code automation system using Make.com that finds, extracts, and organizes Google Maps leads into a database. No coding required. No developers needed. Just a few clicks and your lead pipeline fills itself.

Why No-Code Automation Changes Lead Generation

Before no-code platforms, you had three choices:

1. Manual work — hire a VA to spend 40 hours/week copy-pasting data
2. Hire developers — spend €3,000-5,000 building a custom script
3. Buy expensive software — subscribe to 4-5 tools that don't talk to each other

No-code automation flips this on its head.

Make.com is a visual workflow builder. You drag components onto a canvas, connect them, and workflows execute automatically. No Python. No APIs to debug. No waiting for code review.

Here's what this means for lead generation:

• Speed: Build a system in 2 hours instead of 2 weeks
• Cost: €9-99/month instead of €3,000 upfront
• Control: Change workflows yourself when your strategy shifts
• Scalability: Run the same workflow across 10 cities or 50 industries simultaneously

This approach works for:

• Sales teams automating prospect research
• Marketing agencies building client campaigns
• Freelancers scaling without hiring staff
• Founders validating markets before investing

The key difference: you're not learning to code. You're learning to think in workflows.

Understanding the Core Components: Make.com + Google Maps Data

Make.com connects tools together. It's the "glue" between systems.

You need two things to work:

1. A workflow engine (Make.com) — orchestrates the process
2. A data source (Google Maps) — provides the business information

Google Maps itself isn't designed for data extraction. You can't export 10,000 businesses to CSV from the UI. This is where a Google Maps data extraction tool becomes essential.

Most extraction tools fall into two categories:

Category 1: Real-Time Scrapers - Scrape Google Maps on-demand - Slower (30-60 seconds per 50 results) - Risk of hitting rate limits - Examples: Outscraper, various Python scripts

Category 2: Pre-Indexed Databases - Data already collected and organized - Much faster (instant results) - Updated monthly - Cover 37 countries with 50M+ businesses - Include additional data: reviews, technologies, SIRET matching

For Make.com automation, a pre-indexed database works better. Here's why:

• Speed: Instant API responses mean workflows complete faster
• Reliability: No timeouts or rate limiting during automation runs
• Cost efficiency: Fixed monthly credits instead of per-query charges
• Data richness: Includes reviews, business technologies, claimed status

The workflow becomes: Make.com triggers → Query data source → Extract results → Store in database.

The Four Core Operations in Google Maps Automation

Every Google Maps automation workflow uses four basic operations:

1. Search by Category & Location

Find all businesses matching specific criteria.

Example parameters: - Category: "Plumbers" - Country: France - City: Paris - Filters: Has website, Has email, Rating > 4.0

Output: 500 plumbers in Paris with websites and email addresses

This is your starting point. Every workflow begins here.

2. Search Location Metadata

Retrieve the unique ID for a specific city, region, or country.

Why this matters: Locations have IDs. You need the ID to search them. This operation looks up IDs automatically.

Example: - Input: "Nashville, Tennessee" - Output: Location ID that you use in searches

Without this, you'd manually look up IDs in documentation. This automates that step.

3. Search Business Categories

Find all available category types and their IDs.

Example: - Input: "bakery" - Output: 5 category variations (Bakery, Artisan Bakery, Pastry Shop, etc.)

This helps you target specific business types, not just broad categories.

4. Enrich Business Data

Reverse-lookup a business using a single data point.

Example inputs: - Domain name: "example-plumbing.com" - Email: "[email protected]" - Phone: "+33 1 23 45 67 89" - Google Place ID

Output: Complete business profile with all available data

This operation is powerful for verification. If you have a phone number from another source, this finds the corresponding Google Maps listing.

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Building Your First Workflow: Step-by-Step

Let's build a real workflow. This one finds all restaurants in Amsterdam and stores them in Airtable.

Step 1: Create a Make.com Account

Go to make.com and sign up (free tier available).

You get 1,000 operations/month free. One "operation" = one step in a workflow.

Our example workflow uses ~50 operations per run. Plenty of room on the free tier.

Step 2: Create Your First Scenario

In Make.com, a "scenario" is a workflow.

1. Click Create a new scenario
2. Name it: "Google Maps Restaurant Finder"
3. You'll see a blank canvas

Step 3: Add a Trigger

Every workflow starts with a trigger. This tells Make.com when to run.

Options: - Schedule: Run every day at 9am - Webhook: Run when you send data to a URL - Database trigger: Run when a record is added - Manual: Click a button to start

For lead generation, schedule is most common. Set it to run daily.

Add the trigger: 1. Click the blank canvas 2. Search for "Schedule" 3. Select "Schedule (Simple)" 4. Set it to run daily at 9:00 AM

Step 4: Set Variables

Before searching, define what you're searching for.

Create two variables:

Variable 1: Results per page - Name: results_per_page - Value: 50

This means each search returns 50 results. (Allowed values: 1, 10, 25, or 50)

Variable 2: Target location - Name: target_city - Value: Amsterdam

How to add variables in Make.com: 1. Click the gear icon (settings) 2. Go to Variables 3. Click Add 4. Enter name and default value

Variables let you reuse the same workflow for different cities. Change one variable, run the workflow, done.

Step 5: Search for Locations

Now you need the ID for Amsterdam.

Add a new module: 1. Click the + icon after your trigger 2. Search for your data provider (we'll use IBLead as example) 3. Select Search Locations

Configure the module:

Field	Value
Country Code	NL (ISO code for Netherlands)
Entity Type	city
Search Term	{{target_city}} (this uses your variable)

What happens: Make.com queries the API, returns the location ID for Amsterdam.

Output example:

Location ID: 2747373
Text: Amsterdam, North Holland, Netherlands

Store this ID in a variable for the next step.

Step 6: Search Restaurants

Now search for restaurants in Amsterdam.

Add another module: 1. Click + to add a new step 2. Select Search (from your data provider)

Configure the search:

Field	Value
Category	restaurant
Country Code	NL
City ID	{{location_id}} (from previous step)
Results Per Page	{{results_per_page}} (your variable)
Filters	Check: "Has website", "Has email"

This filters to restaurants that have both website and email. No dead contacts.

Output: 50 restaurant records with: - Name - Address - Phone - Email - Website - Google rating - Number of reviews - Google Place ID

Step 7: Store Results in Airtable

Now you have 50 restaurants. Store them in a database.

Add an Airtable module: 1. Click + to add a new step 2. Search for "Airtable" 3. Select Create Record

First, authenticate: 1. Click "Add" next to Connection 2. Log in to your Airtable account 3. Authorize Make.com

Configure the module:

Field	Value
Base	Select your Airtable base
Table	Restaurants (or create new)
Name	{{name}}
Email	{{email}}
Phone	{{phone}}
Website	{{website}}
Rating	{{rating}}
Review Count	{{review_count}}

The {{}} syntax pulls data from the previous step.

Critical step: You need to iterate through all 50 results.

In Make.com, add an Iterator module between Search and Airtable:

1. After Search, click +
2. Search for "Iterator"
3. Select Iterator
4. Set Array to: {{search_results}}

The Iterator loops through each result, one at a time. Airtable then creates 50 records (one per iteration).

Step 8: Handle Pagination

What if there are 500 restaurants in Amsterdam, but you only got 50?

Google Maps searches return a "next cursor" — a pointer to the next page of results.

Add pagination logic:

1. After the Airtable step, add a Conditional module
2. Set condition: "If next_cursor exists"
3. If true: Loop back to the Search step, use the next cursor
4. If false: Workflow ends

This automatically fetches all pages until no more results exist.

Step 9: Test the Workflow

Before running live, test it.

1. Click Run once (bottom left)
2. Watch each step execute
3. Check Airtable — do 50 restaurants appear?

If successful, you'll see:

✓ Trigger executed
✓ Location search: 1 bundle returned
✓ Restaurant search: 50 bundles returned
✓ Iterator: 50 iterations
✓ Airtable: 50 records created

If something fails, Make.com shows exactly where. Click the failed module to see the error.

Step 10: Activate the Workflow

Once tested:

1. Click the On/Off toggle (top left)
2. Set it to On
3. Workflow now runs on schedule (daily at 9am)

Every day, your Airtable table gets 50 new restaurants from Amsterdam. No manual work.

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Advanced Workflow Patterns

Pattern 1: Multi-City Search

Search 10 cities simultaneously.

Setup: 1. Create a table with 10 city names 2. Trigger: "When a new record is added" 3. Loop through each city 4. Run the search workflow for each

Result: Automated prospecting across entire regions.

Pattern 2: Smart Filtering

Search for businesses with specific characteristics.

Example: Find struggling restaurants

Filter by: - Rating < 3.5 stars - Fewer than 20 reviews - No website

These are restaurants struggling with online presence. Perfect for a web design agency to target.

Workflow: 1. Search all restaurants 2. Apply filters in the Search module 3. Only results matching criteria are stored

Pattern 3: Data Enrichment

You have a list of business names. Find their Google Maps data.

Workflow: 1. Trigger: CSV upload with business names 2. For each name, use the Enrich operation 3. Returns full Google Maps profile 4. Store in database

This is powerful for verifying existing data or finding missing contact info.

Pattern 4: Automated Outreach

Find leads, then send emails automatically.

Workflow: 1. Search restaurants 2. Store in database 3. Send personalized email to each 4. Track opens and clicks

Integrations: - Lemlist - Instantly - Mailchimp - HubSpot

Make.com connects to all of them.

Pattern 5: Lead Scoring

Find leads, then rank them by quality.

Score by: - Rating (higher = better) - Review count (more = established) - Website presence (yes/no) - Business age (older = more stable)

Workflow: 1. Search businesses 2. Calculate score for each 3. Only store leads with score > 70 4. Send high-quality leads to sales team

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Common Mistakes & How to Fix Them

Mistake 1: Using Wrong Location IDs

Problem: You search "New York" but get 0 results.

Cause: You used city name instead of city ID.

Fix: Always run the "Search Locations" step first. Use the returned ID.

Prevention: Store location IDs in a lookup table. Reuse them.

Mistake 2: Forgetting the Iterator

Problem: Only 1 record appears in Airtable instead of 50.

Cause: You didn't add an Iterator module.

Fix: Add Iterator between Search and Create Record.

How it works: - Without Iterator: Airtable creates 1 record with all 50 results crammed in - With Iterator: Airtable creates 50 separate records

Mistake 3: No Pagination

Problem: Workflow stops after 50 results.

Cause: You didn't handle the "next cursor."

Fix: Add conditional logic to loop while next_cursor exists.

Mistake 4: Running Without Testing

Problem: Workflow runs 1,000 times, creates duplicates, wastes credits.

Cause: Didn't test before activating.

Fix: Always click "Run once" first. Verify output. Then activate schedule.

Mistake 5: Incorrect Filter Syntax

Problem: Filters don't work. You get all results, not filtered ones.

Cause: Filter syntax varies by data provider.

Fix: Check API documentation. Test filters in "Run once" mode.

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Understanding Credits & Costs

Make.com charges per operation. A search operation = 1 operation.

Example workflow cost:

Step	Operations
Trigger	0 (free)
Search locations	1
Search restaurants	1
Iterator (50x)	0 (included in search)
Create Airtable record (50x)	50
Conditional check	1
Total per run	53

Monthly cost:

If workflow runs daily (30 days): - 53 operations × 30 days = 1,590 operations - Make.com free tier: 1,000 operations/month - Overage: 590 operations

Free tier covers most small workflows. Paid plans start at €9/month (10,000 operations).

Optimization tip: Batch operations. Instead of creating 50 Airtable records in one workflow, create 500 records per run. Same operations, more leads.

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Integrating Google Maps Data: Where IBLead Fits

The workflow above works, but it depends on which data source you use.

Not all Google Maps data providers are equal.

What You Need From a Data Source

1. Speed: API returns results in <2 seconds
2. Coverage: 50M+ businesses across multiple countries
3. Freshness: Data updated monthly (not yearly)
4. Features: Filters for ratings, reviews, website presence
5. Enrichment: Additional data like reviews, technologies, business details
6. Pricing: Affordable credits that don't disappear monthly

Comparing Data Sources

Option A: Real-Time Scrapers - Scrape Google Maps on-demand - Slower (30-60 seconds per request) - Risk of rate limits - Pricing: €0.10-0.50 per result

Option B: Pre-Indexed Databases - Data already collected - Instant results (<1 second) - No rate limits - Pricing: €44-250/month for 10,000-100,000 credits

For Make.com automation, Option B is superior. Here's why:

Speed matters: If your workflow waits 60 seconds per search, a daily automation across 10 cities takes 10 minutes. With instant results, it takes 30 seconds.

Reliability matters: Rate limits break workflows. Pre-indexed databases don't have this problem.

Cost clarity matters: Fixed monthly pricing vs. per-query charges. Easier to budget.

What IBLead Includes

IBLead is a pre-indexed database of 50M+ businesses across 37 countries.

Data included per business: - Name, address, phone, email - Website - Google rating & review count - Google reviews (text, author, date) — unique to IBLead - Business technologies detected (160+) — unique to IBLead - SIRET/SIREN (France only) — unique to IBLead - Claimed status, photos, hours

Pricing structure:

Plan	Credits/Month	Price
Free	5,000	€0
Starter	10,000	€44
Pro	20,000	€89
Business	40,000	€179
Enterprise	100,000	€449

Each credit = 1 business exported.

Key advantage: All features included from Starter onwards. No feature gates. No €199 "Agency" plan required to access basic filters.

Building a Workflow With IBLead

The Make.com workflow above works with IBLead. Here's what changes:

Step 1-2: Same (trigger, variables)

Step 3-4: Same (search locations, search businesses)

Step 5: When you search, results include: - Google reviews (IBLead exclusive) - Detected technologies (IBLead exclusive) - Claimed status

Example use case: Find all restaurants using WordPress for their website.

Search parameters:
- Category: Restaurant
- City: Paris
- Filter: Technology = "WordPress"

Returns 45 restaurants. Target them with web design services.

Another example: Find businesses with bad reviews.

Search parameters:
- Category: Plumber
- City: London
- Filter: Rating < 3.5
- Filter: Review count > 10

Returns struggling plumbers. Target them with reputation management.

These use cases are only possible because IBLead includes review data and technology detection.

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Real-World Workflow Examples

Example 1: Agency Lead Generation

Goal: Find all marketing agencies in 5 European cities, export to HubSpot.

Workflow: 1. Trigger: Daily at 8am 2. Loop through 5 cities (Paris, London, Berlin, Amsterdam, Barcelona) 3. Search for "Marketing Agency" 4. Filter: Has website, Rating > 4.0 5. Store in HubSpot

Result: 500+ qualified agencies per month, automatically fed to sales team.

Make.com operations: ~100/month (well under free tier)