I rebuilt my Google Maps lead scraping workflow without a browser

I've been messing around with Google Maps lead generation for agencies, and one thing kept bothering me.

Why are so many lead scrapers loading an entire browser just to get a business name, phone number and website?

So I built a request based version for my own workflows.

The basic process is:

Google Maps search → business details → website → contact email → dataset

No browser rendering, screenshots, scrolling, or reviews pagination.

The interesting part wasn't actually making the scraper work. It was figuring out what not to scrape.

For example, I ended up doing things like:

• Deduplicating businesses by Google Maps place ID before fetching their websites

• Skipping Facebook, Instagram, LinkedIn, etc. when they appear as a business website

• Stopping a website request as soon as a usable email is found

• Not downloading PDFs, images, or other non HTML responses

• Fetching the same domain only once when multiple businesses share it

• Streaming leads into the dataset instead of waiting for the entire run to finish

• Filtering by rating, business status, and whether the business has any contact method

That made a surprisingly big difference to how lean the workflow could be.

The output I'm interested in isn't really "Google Maps data."

It's more like:

"Find me 100 dentists in Chicago with 4+ stars that have a phone, email, or website and give me something I can actually prospect."

That distinction seems important for agencies.

You don't necessarily need more scraped data.

You need fewer useless rows.

Curious what other agency owners are doing here.

What does your lead research workflow look like right now?

Are you using Google Maps, Apollo, directories, manual research, or some combination?

And what's the biggest pain for you?

Finding the businesses, getting contact info, cleaning the list, or actually converting the leads?

I learned this the hard way.

Code is free now.

Distribution isn't.

Anyone can vibe code an app over a weekend.

Almost nobody can convince 100 strangers to care.

A few months ago I built an AI product that I genuinely thought people would love.

Technically, it worked.

The UX was good.

The AI was solid.

I kept adding features because I thought one more improvement would finally make people use it.

They didn't.

The problem wasn't the product.

The problem was that I never proved anyone actually wanted it before I started building.

That failure completely changed how I approach startups.

Now I spend far more time answering questions like:

• Are people already paying to solve this?
• Are they actively complaining about this problem?
• Can I reach them cheaply?
• Can I get 20 people interested before writing code?

Only then do I open Cursor.

Because AI has completely changed the startup game.

The bottleneck isn't engineering anymore.

It's demand.

The founders who win in 2026 won't be the ones who can build the fastest.

Everyone can build now.

The winners will be the ones who find demand before everyone else.

I'm curious...

What's something you built that nobody wanted, and what did it teach you?

I wanted to share a breakdown of a project I worked on over the last six months with a creator in the self-development niche.

Like many bloggers, he got hit hard by Google's recent updates and AI Overviews. His blog dropped from around 600k monthly visitors to roughly 50k almost overnight.

The biggest issue wasn't the content.

Visitors who reached the site were still converting into affiliate sales and paid community members. The problem was that almost all of his traffic came from Google. Once that disappeared, the business became heavily dependent on a single source.

Instead of spending months trying to recover rankings, we decided to diversify and build a second traffic channel. We chose Pinterest because it's much closer to a visual search engine than a typical social network, and long-form blog content naturally translates into pins.

Our first mistake

Our first idea seemed obvious.

We built an automation that took existing blog posts, generated Pinterest pins, and published them on a schedule.

It worked... at first.

The account picked up some impressions and clicks, but after about two months growth completely plateaued.

That's when we realized something.

The automation wasn't the problem. What we automated was.

We were simply republishing existing content in a different format.

Pinterest rewards fresh content, but more importantly, it rewards content that matches what people are currently searching for and what visual styles are performing well.

What we changed

Instead of automatically turning blog posts into pins, we rebuilt the workflow around Pinterest itself.

Every month we analyzed Pinterest autocomplete data and trending keywords in the niche.

Then we studied the top-performing pins for those searches to understand what was working. Things like layouts, typography, colors, headlines, and overall presentation.

Instead of recycling old blog graphics, every pin became a completely new creative designed around current search demand.

We also warmed up the account gradually instead of jumping straight into high-volume posting. We started with a few pins per day and slowly increased the volume over several weeks.

The results after four months

• Pinterest grew from essentially no meaningful reach to roughly 4 million monthly impressions.
• It generated around 15,000 additional visitors per month.
• Pinterest traffic converted better than both Google search traffic and the creator's newsletter.
  • Google: ~0.6%
  • Substack: ~1.3%
  • Pinterest: ~1.9%
• Monthly revenue grew from roughly $3k MRR to $5k MRR, putting the business on track for around $50k ARR.

Biggest takeaway

If your blog still depends almost entirely on Google, I'd seriously consider building a second distribution channel.

Whether that's Pinterest, YouTube, email, or something else, relying on one traffic source has become much riskier over the last couple of years.

For us, the biggest lesson wasn't that automation works.

It was that automation only amplifies a strategy that's already working.

Automating the wrong process just helps you reach the plateau faster.

Has anyone else here successfully diversified away from Google? I'd love to hear what channels have worked best for your blog.

I read 3,022 one-to-three star reviews across 15 competitor calorie tracking apps (MyFitnessPal, Yazio, Lifesum, Cal AI, Foodvisor, etc) to find what to build. instead of brainstorming, i had an llm find recurring patterns in the complaints instead of one off gripes.

here's what actually showed up, ranked by volume:

1. subscription and billing dark patterns (500+ reviews touch this, by far the biggest category). charged the second they finish onboarding, refunds refused, cancel button hidden somewhere in settings menus.
2. gamification fatigue (86+ reviews, concentrated in the biggest apps). mascots, streaks, forced pop ups before every meal log. one reviewer said she pays for the app and still gets buried in reminders. this one surprised me, i expected ai accuracy complaints to dominate and they didn't.
3. ai photo and calorie accuracy (263 reviews). confidently wrong numbers, can't handle mixed plates or home cooked meals. real, but smaller than the other two.

nobody in this space is building the boring version. no mascot, no streak guilt, honest billing, just fast accurate logging. that's the actual gap.

cost a few dollars in scraping plus an afternoon with claude to find this. Cheaper than weeks of guessing.

Curious what methods you all use to validate before building. also wondering if the billing dark patterns and gamification fatigue combo shows up in other app categories too, or if that's specific to health and fitness apps.

I feel like smartphones have become objectively better every year, but we've quietly lost a lot of genuinely useful features along the way.

For me it's:

• Headphone jack
• Notification LED
• SD card slot
• IR blaster
• Physical fingerprint scanner on the back
• Charger in the box
• Smaller flagship phones

Meanwhile we've gained... AI wallpapers, 5 cameras lens working together to zoom to moon craters and, circle-to-search.

I'm curious:

If manufacturers could bring back ONE feature tomorrow, what would you choose?

Mine would honestly be the notification LED. It was such a simple thing that made checking my phone so much easier.

What's yours?