Make.com Tutorial: Build a Google Maps Lead Generation System on Autopilot (2026 Guide)

A buddy of mine runs a 6-person agency in Austin. Marketing stuff, mostly local businesses. Last month he told me he'd spent — and I'm not exaggerating — 30 hours copying restaurant contacts from Google Maps into a Google Sheet. Thirty. Hours. That's four full workdays of clicking, copying, tabbing, pasting, and slowly dying inside.

I showed him how to wire Scrap.io into Make.com on a Friday afternoon. Nothing fancy, maybe 45 minutes of setup. By Monday morning, 4,200 leads were sitting in his Airtable — sorted by city, Google rating, email availability. He hadn't touched a keyboard all weekend.

That's what this make.com tutorial covers. Not theory. Not "imagine the possibilities." The actual step-by-step build for an automated prospecting system that scrapes Google Maps, filters the junk out, and feeds clean leads into your database while you're off doing something that actually requires a brain.

Oh and if you'd rather skip the whole build? We're giving away the pre-built scenario for free. Grab it, tweak it, run it. But stick around — understanding what each piece does means you can customize it without guessing.

Why Automate Google Maps Lead Generation in 2026?

The no-code automation market is headed toward $819 billion by 2030. That number sounds made up but it comes from Mordor Intelligence and frankly it tracks with what I'm seeing.

Forget the big picture for a sec though. Think about what manual prospecting actually looks like.

You open Google Maps. Type "plumber Nashville." Click a listing. Copy the name. Tab to your spreadsheet. Paste. Click back. Find the website. Hunt for an email address that may or may not exist. Copy, paste, repeat. Five hundred times.

At 90 seconds per lead — and that's being generous — you're burning 12 hours. Half of those emails will bounce. Some of the businesses closed six months ago. And your back hurts from hunching over a laptop all day. Wonderful.

Meanwhile the people who've automated this? Companies using marketing automation are seeing 53% higher conversion rates according to EmailVendorSelection's 2025 report. The Aberdeen Group pegs automation users at 3.1% higher revenue growth year-over-year. On a $10 million business that's an extra $310K. Annually. From automation alone — not from a new product launch, not from hiring five more salespeople.

And Make.com specifically? Over 3,000 enterprise clients. A community forum with 50,000+ members trading scenarios. They raised $180M at a $2.5B valuation. Not exactly a garage project anymore. (76% of marketers already use automation tools. Sales teams? Only 44%. If you're in sales and reading this, you're behind.)

WiserNotify published a stat last year that stuck with me: $5.44 back for every $1 invested in automation over three years. Where else are you getting 5x returns on a tool that costs less than your monthly coffee budget?

If you're the "make.com tutorial for beginners" type who's never touched an automation platform — don't worry. We're going piece by piece. For the bigger picture on what Google Maps automation can do beyond lead scraping, there's a separate guide on complete marketing automation with Google Maps worth bookmarking.

What You Need: Make.com + Scrap.io

Two tools. That's the entire stack.

Make.com — used to be called Integromat, for anyone who's been around a while — is a visual automation builder with 3,000+ app connectors. You drag modules onto a canvas, draw lines between them, and it runs. Like Zapier, except Make actually lets you build complex stuff without hitting weird limitations every five minutes.

Pricing is credit-based now. Core plan: $9/month billed annually (or $10.59 monthly). That buys you 10,000 credits, where each module action in your scenario eats one credit. For a lead gen workflow running once a day, that's more than enough. Check their pricing page for current numbers — they've been adjusting things since the November 2025 credit overhaul.

Scrap.io is the other half. It's a dedicated Google Maps scraping tool with 200 million businesses indexed. Not a static database that was scraped once in 2023 and forgotten about. Real-time data, pulled fresh from Google Maps and the websites connected to each listing.

What separates Scrap.io from the 15 other scrapers floating around:

• 200M businesses, 195 countries, 4,000+ Google Maps categories
• 5,000 queries per minute. It's fast.
• Pulls more than just name and phone — emails, social profiles, website tech stack, ad pixels, review breakdowns, contact forms
• Full API that plugs natively into Make.com

Together, these two replace what would normally require a virtual assistant plus a data cleaning service plus a CRM integration consultant. One finds and filters your prospects. The other orchestrates the entire pipeline.

Setting Up the Integration

This part takes five minutes. Maybe ten if you're the type who reads every tooltip.

Step 1: Install the Scrap.io module in Make

Go to your Make.com dashboard, search "Scrap.io" in the app directory, click Install. Done. It's a native integration — no webhook hackery needed.

Step 2: Get your API key from Scrap.io

Log into your Scrap.io account. Profile → Security → API Keys → Create. Copy the key.

[IMAGE_PLACEHOLDER — screenshot of Scrap.io API key generation page]

Step 3: Connect them

Create a new scenario in Make. Add a Scrap.io module. Paste your API key when it asks. That's... it. No OAuth flow, no JSON config, no cursing at your screen.

[IMAGE_PLACEHOLDER — screenshot of Make.com workflow with Scrap.io module connected]

If you want to skip even this setup: Scrap.io publishes a free pre-built scenario that handles make.com google maps scraping end-to-end — search, enrichment, Airtable sync, pagination. Download, import, customize. Five minutes to a working pipeline.

Deep Dive: The 4 Core Scrap.io API Models

Here's where it gets interesting. Scrap.io's API exposes four distinct modules inside Make.com. Each one does something different. Mix them, chain them, use them standalone — your call.

Model 1: The Search Function

The main one. Tell it what type of business you want (say, "bakery"), where (country, state, city), and it returns results with all associated data.

Couple things that trip people up:

Results per page — your options are 1, 10, 25, or 50. Not 37. Not "all of them." Those four. It's a quirk. Live with it.

Admin1 vs admin2 vs city — because Scrap.io works across 195 countries, they use generic terms instead of "state" or "county." In the US: admin1 = state, admin2 = county. In France: admin1 = région, admin2 = département. City is city everywhere. The IDs for these come from Model 3 (we'll get there).

Now the actually important part: filters.

Seventeen filters. Minimum Google review count, email present (yes/no), website present, contact form detected, social media profiles, main category match... the output comes pre-qualified. No more exporting 10,000 rows and spending two days deleting garbage.

I ran a test last month. Restaurants in Tennessee, filtered for "has email" and rating above 3.5. Result: 2,800 leads. Every one had a working email. Try getting that from a list you bought off some shady data broker.

For the full breakdown on email extraction specifically, see our guide on how to find emails on Google Maps.

Model 2: Search Types

This one's simple. You search for a Google Maps category keyword — "restaurant," "plumber," "strip club" (no judgment) — and it returns the corresponding IDs.

Why bother? Because Google Maps has 369 types of restaurants. Searching "restaurant" gives you all of them. Searching "bakery" gives you five. You need the right ID for accurate results in Model 1. Skip this step and you'll either get way too many results or none at all.

Model 3: Search Locations

Same idea, different axis. Give it "Nashville" and a country code, and it hands back the location ID you need for your search queries.

Critical detail: if you want Nashville the city, you need to specify "city" as the entity type and use the returned ID in the city field of Model 1. I made the mistake of plugging a city ID into the admin1 field once. Zero results. Spent 20 minutes confused before I realized what I'd done.

Bonus: GeoSearch. You can define a radius around a point, or draw a polygon on the map for your search area. Handy for hyperlocal campaigns where city boundaries don't match your actual service area.

Model 4: Enrich — The Reverse Lookup

Honestly my favorite. Feed it a domain name, email, URL, or phone number. It returns the full Google Maps profile attached to that business — if one exists.

Why is this powerful? It works backwards. You've got a list of company websites from some other source — a CRM export, a LinkedIn scrape, whatever. Run those domains through Enrich and suddenly each one has Google ratings, review counts, categories, social links, contact data. Information you didn't have five minutes ago.

One caveat: big chains return tons of results. Feed McDonald's domain and you'll get hundreds of location bundles. Local plumber? One clean match. Adjust expectations accordingly.

[IMAGE_PLACEHOLDER — Enrich model results in Make.com showing data returned from domain lookup]

Building the Complete Automated Prospecting System

OK. Individual modules are great. But the real magic happens when you chain them into a full automated prospecting system. Here's how the complete workflow works.

[IMAGE_PLACEHOLDER — complete Make.com workflow overview: variables + Scrap.io + Airtable + pagination]

1. Variables. Two of them. Results per page (set it to 50 for max throughput) and your Scrap.io API key. That's your initialization.

2. Scrap.io Search fires. Based on whatever criteria you've defined — business type, location, filters. Returns the first batch of results.

3. Iterate and store. Each result gets pushed into an Airtable table as a new lead record. Name, email, phone, website, review score, categories — all mapped automatically. The make.com airtable integration makes this dead simple.

[IMAGE_PLACEHOLDER — Airtable "Leads" table populated with Google Maps business data]

4. Pagination. This is where most DIY automations fall apart. Your search returns 300 results but you're pulling 50 per page. You need a cursor to grab page 2, then 3, then 4. The pre-built scenario handles this automatically: stores the cursor, updates the target status from "to do" to "in progress," keeps looping until there's no more data. Then flips to "done."

5. Queue management. The Airtable "targets" table tracks what's been scraped and what hasn't. Three statuses: to do, in progress, done. Stack up ten different searches (restaurants Nashville, bakeries Memphis, plumbers Knoxville) and the system chews through them one by one.

Once this runs? Schedule it. Daily, weekly, whatever rhythm your sales team needs. Google maps scraping automation no code — no Python, no proxies, no IP rotation headaches. Just data flowing into your pipeline on autopilot.

And it doesn't stop at lead collection. Some users bolt on email tools like Lemlist or Saleshandy, creating a closed loop: scrape → filter → enrich → validate → email → track responses. When a lead status changes in Airtable, Make triggers the next action automatically. You can even automate your email outreach entirely, or layer on AI-powered cold email personalization using ChatGPT to write custom messages from the scraped data fields.

Real-World Results: Who Uses This System?

Case studies sound nicer than "let me prove I'm not making this up." Fine. Let me prove I'm not making this up.

Globant (30,000+ employees) used Make.com to roll out automation company-wide. Their Head of Innovation didn't just run a pilot — he gave 30,000 people access to the platform. Non-technical teams building their own workflows. That's a scale bet most companies wouldn't touch. (Source: Make.com blog, March 2026.)

FranklinCovey automated internal processes with Make and saved — their words — "hundreds of thousands of dollars" while freeing hundreds of staff hours. The kind of savings that make finance people smile for the first time since college. (Source: Make.com case study, September 2025.)

The wildest one: Celonis built Make AI Agents for expense auditing. Annual auditing costs went from $50,000 down to $150. I had to read that twice. Fifty grand to a hundred and fifty bucks. (Source: Make.com case study, November 2025.)

My personal favorite though? Eduardo Cifre Sanchez built a voice-powered AI invoicing system for rural farmers in Spain — people who'd never used automation software in their lives. Made it with Make.com. Saved dozens of small businesses hours of paperwork and removed their need for dedicated accountants. Non-technical guy, building for non-technical users. That's the whole promise of no-code in one example. (Source: Make.com blog, December 2025.)

On the Scrap.io side: a SaaS company targeting restaurants scraped 12,000 contacts from Google Maps. That part took under an hour. Then they realized the hard part wasn't finding leads — it was converting Google Maps prospects into actual customers. But having 12K qualified contacts to work with is a pretty nice problem to have. (Referenced in the Scrap.io lead nurturing guide.)

And from the Scrap.io blog directly: a web design agency filtered Google Maps for businesses without websites but WITH contact forms, then ran a contact form outreach campaign. Twenty-three percent response rate. 47 new clients in three months. That's nearly 5x what they were getting through cold email alone. The difference was targeting precision — 70+ data points per lead instead of name-and-email-and-pray. (Source: Scrap.io contact form strategy article.)

Reddit's r/automation has regular threads about Make + Google Maps builds too. One user shared their Google Form → Sheets automation, then rebuilt the whole thing with Scrap.io after seeing the data quality gap. Twenty comments, detailed workflow screenshots. Real people building real stuff.

For a broader look at extraction methods — Python, Chrome extensions, SaaS tools — the complete Google Maps scraping guide has five approaches compared side by side.

Make.com vs Other Automation Tools (2026)

"Why Make and not Zapier or n8n or whatever?"

Legit question. Here's where they actually differ — not marketing fluff, real trade-offs.

Feature	Make.com	Zapier	n8n	Power Automate
Entry paid plan	~$9/mo (10K credits)	$19.99/mo	Free (self-hosted) / ~$20 cloud	$15/user/mo
Scrap.io module	✅ Native, full API	❌ Webhook workaround	❌ HTTP module only	❌ Nothing
Visual builder	✅ Best in class	✅ Simple, limited	✅ Solid but technical	❌ Clunky
App integrations	3,000+	8,000+	400+ (extensible)	1,000+ (Microsoft-centric)
AI agents	✅ Native (2025+)	✅ Basic	✅ Custom nodes	✅ Copilot
Learning curve	Moderate	Easy	Steep	Steep
Best for	Complex multi-step workflows	Simple A→B automations	Developers who self-host	Microsoft-only orgs

Zapier is easier. Nobody denies that. But add branching logic, iterators, error handlers? Zapier starts choking. Make was designed for that level of complexity from day one.

n8n is open-source and self-hostable. Excellent if you're a developer who wants total control. No native Scrap.io module though — you'll build HTTP requests manually. Which, fine, but why bother when Make gives you drag-and-drop?

Power Automate only makes sense if your company breathes Microsoft. For automated lead generation google maps workflows? Non-starter.

Here's what sealed it for me: since November 2025, even Core plan users on Make can plug in their own OpenAI or Anthropic API keys. Build scenarios that don't just scrape — they analyze leads, categorize them, generate personalized emails. The google maps data extraction automation game has completely shifted. This isn't 2023 anymore.

For make.com automation workflow examples beyond lead gen, the Make community forum is a goldmine. Fifty thousand members sharing scenarios for everything from invoice processing to social scheduling to full prospecting pipelines.

Cost Breakdown: Running This Automation

Let's do the actual math. No hand-waving.

Component	Plan	Monthly Cost
Make.com Core (annual)	10,000 credits/month	~$9/mo
Scrap.io Professional	20,000 credits/month	$99/mo
Airtable Free	1,000 records/base	$0
Total		~$108/mo

20,000 leads for $108. That's $0.0054 per lead. Half a penny.

For perspective: WordStream benchmarks put B2B lead costs at $100-$400 per lead through traditional channels. A VA manually scraping Google Maps does maybe 30 leads per hour at $15-25/hour — that's 50 to 83 cents each. Intent data platforms like ZoomInfo run $150-$500/month and give you a tiny fraction of the volume.

Half a penny vs. fifty cents. I don't have a clever analogy. The gap is just absurd.

Starting out? Scrap.io's free trial comes with 100 leads and full API access. Enough to build the workflow, test it end to end, and see actual data before committing.

Compliance & Legal Considerations

Not the sexiest section but skip it at your own risk.

Scrap.io pulls only publicly available data — the same stuff anyone sees when they browse Google Maps manually. Business names, addresses, phone numbers, websites, emails displayed on those websites. Scrap.io just does it faster and at scale.

For cold outreach using that data: CAN-SPAM in the US requires clear identification, honest subject lines, a working unsubscribe link, and your physical business address. GDPR in Europe allows B2B cold email under "legitimate interest" as long as you offer easy opt-out and can justify why you're contacting that specific business.

Two things before you blast your freshly scraped list. First: verify those emails. Even one campaign with a 5%+ bounce rate can wreck your sender reputation. Second: consider contact form outreach as an alternative channel — near 100% read rates because the message lands in the owner's inbox directly, not in a spam folder.

Deeper dive on legality: we wrote a full article on whether scraping Google Maps is legal. Short version: publicly accessible business data, yes. Personal data, no. Stay on the right side and you're fine.

Once compliance is handled, the data you've got gives you outreach ammunition most competitors simply don't have. You know their review count. Their rating. Whether they run Facebook ads. Whether their site uses WordPress or Shopify. Use that. Personalization based on real data beats generic "Dear Business Owner" every single time.

Scrap.io API Models — Quick Reference

Model	Input	Output	Best Use Case
Search	Category + Location + Filters	Businesses with full data	Main prospecting by type and geography
Search Types	Keyword (e.g. "bakery")	Matching category IDs	Discover exact IDs before running Search
Search Locations	Country + entity type + term	Location IDs	Get city/state/county IDs for search queries
Enrich	Domain, URL, email, or phone	Full Google Maps profile	Reverse lookup — enrich existing databases

Frequently Asked Questions

How to automate Google Maps lead generation?

Connect Scrap.io to Make.com via the native module. Build a scenario: search by category and location, apply filters, push results into Airtable or your CRM. Scrap.io handles extraction, Make handles orchestration. Schedule it and walk away. The API documentation covers every parameter.

Is Make.com better than Zapier for lead generation?

For Google Maps specifically? Yeah. Native Scrap.io module, half the price (~$9 vs $20), and a builder that handles branching, iteration, and error paths without falling apart. Zapier is fine for simple stuff. Complex multi-step workflows? Make wins.

Is Make.com worth learning in 2026?

With 3,000+ integrations, native AI agents, and 50,000+ community members — hard to argue against it. The free tier gives you 1,000 credits to test (no credit card). Make Academy has free courses if you want structured learning. Their Help Center covers the rest.

Do I need coding skills to use Make.com?

Nope. Everything is drag-and-drop visual. If you can use a spreadsheet, you can build Make workflows. That's the entire point of no-code lead generation — removing the developer bottleneck.

How many leads can you generate per hour?

Scrap.io processes 5,000 queries per minute. With Make handling the pipeline, several thousand leads per hour is realistic. Exact numbers depend on filters, page depth, and data fields. A typical scenario pulling 50 results per page with 5 filters runs through about 3,000-5,000 leads in an hour.

How much does this automation cost per lead?

About half a cent ($0.005). Make Core (~$9/month) + Scrap.io Pro ($99/month) = roughly 20,000 leads for $108. Traditional B2B services charge $100-$400 per lead. VA scraping costs $0.50-$0.83 each. The math is brutal.

How to use the Scrap.io API with Make.com?

Install the Scrap.io module in Make's app directory. Generate an API key in your Scrap.io account (Profile → Security → API Keys). Paste it into the connection prompt. Done. All four API models show up as native modules. Full reference at apidoc.scrap.io.

What tools automate Google Maps prospecting?

Scrap.io for extraction (200M businesses, 195 countries). Make.com for automation logic. Airtable for the database. For outreach after scraping: Lemlist or Saleshandy work well, especially with AI-driven email personalization. Some teams also feed leads into HubSpot or Pipedrive.

Can I use Make.com with Airtable for lead management?

Recommended setup, actually. Make has native Airtable modules — create, read, update, search. The free Scrap.io scenario uses Airtable for both the scraping queue (targets table) and lead storage (leads table). You can trigger follow-up actions when fields change: status update → Slack ping → email sequence → CRM entry.

Where can I learn Make.com basics?

Make Academy for structured courses. Make Help Center for docs. For this specific use case, this tutorial plus the free Scrap.io scenario gets you 90% there. Community forum handles the other 10%.

Is Google Maps scraping legal?

Yes — when you stick to publicly available business data. Scrap.io pulls only information businesses choose to display on their Maps profiles and websites. Same data any human could see by browsing. Courts in the US and EU have broadly upheld this. For outreach, follow CAN-SPAM and GDPR. Full breakdown in our dedicated legal article.

Your Move

Two paths. Keep clicking through Google Maps listings until your wrist gives out. Or spend an afternoon building a system that does it while you sleep.

The free scenario exists. The API docs exist. Half a cent per lead vs. a hundred dollars. Not much to debate.

Freelancer, sales team, agency — doesn't matter. Pick one business category. One city. Run the search. Watch the leads land. Then scale. You can layer on automated email outreach next, or build a full marketing automation pipeline. The foundation you build today handles all of it.