Best Pages Jaunes Scrapers 2026 [No-code Edition]

TL;DR

1. I tested no-code PagesJaunes scrapers across data, pricing, speed, scalability, and ease of use
2. I skipped browser extensions, visual scrapers, and API-only tools — only cloud-based no-code tools with a dedicated PagesJaunes scraper made the cut
3. lobstr.io returns 14 fields (26 with enrichment), is the only tool with email extraction, and uses parallel concurrency to push throughput when volume grows
4. Apify returns 38 fields — the most here, including the only full weekly opening hours — at a flat $1.50/1,000 with no scale discount
5. WebScraper.io returns 10 fields and is the slowest (5/min) — even though it uses parallel concurrency, it is the most expensive on this list
6. PhantomBuster is the fastest (150/min) and cheapest at scale ($0.16/1,000) but returns only 4 fields — name, address, phone, listing URL

Getting a few PagesJaunes results is easy.

Getting a clean, usable list at scale — without code or surprise costs — is the real problem.

Most scraping tools you find online are either built for developers, unreliable past a few hundred rows, or wildly overpriced once you need volume.

I tested the best no-code options so you don't have to sit through the same trial-and-error.

Here's what actually works.

But before that, let's clear the air. Is it legal?

Is it legal to scrape PagesJaunes?

Yes, it is legal.

For most business use cases — lead generation, market research, competitive analysis — you're well within those boundaries.

A few things to keep in mind:

1. Use the data internally, not for republishing listings publicly
2. Don't extract the full catalogue
3. Don't build a competing directory from the scraped data

Further reading:

How I chose these tools

From there, I narrowed the comparison down to five criteria:

1. Data
2. Affordability
3. Scalability
4. Speed
5. Ease of use

Here's what I checked for each one:

For data, I counted how many fields each tool returns, which fields are exclusive, and whether the output is clean enough to use without cleanup.

For affordability, I converted pricing into cost per 1,000 results and compared entry-level vs scale-level pricing.

For scalability, I measured both input scale and output scale.

Input scale is bulk import and how well the workflow holds up with large URL lists.

For output scale, I convert speed into a monthly ceiling using 8h/day of active runtime (≈14,400 min/month).

That estimates how many results each tool can produce in a month.

Then I noted whether the tool has concurrency controls to push throughput, or if scaling is mostly linear.

For speed, I ran timed tests and converted everything into results per minute.

For ease of use, I ran the full workflow myself — from first landing on the tool to exporting usable data.

I judged it on steps to first result, input clarity, result limiting, scheduling visibility, plus export options and integration options.

I also checked customer support: what channels exist, and what users say about response quality.

After defining the criteria, I listed every PagesJaunes scraper I could find through Google results and AI recommendations.

Then I cut the list down:

1. Browser extensions and visual scrapers were out because they're better for smaller, manual jobs.
2. API-only tools were out because they still require coding to get useful output.

So the final list only includes no-code tools that are practical for scalable PagesJaunes data collection.

Best PagesJaunes scrapers

1. Lobstr.io

Key features

1. 26 data fields
2. URL-first workflow: paste your PagesJaunes search URL directly
3. CSV bulk upload for multiple search URLs
4. Email extraction from business websites — exclusive to this tool
5. Company data: SIRET, SIREN, NAF code, creation date, company size
6. Slots to control concurrency
7. Schedule recurring scrapes
8. Cloud-based, no installation needed
9. Export to CSV or automate delivery to Google Sheets, Amazon S3, SFTP, or email
10. Integrates with Make.com and 3,000+ apps

Data

lobstr.io returns up to 26 PagesJaunes fields per result, depending on which add-on functions you enable.

At baseline, it gives you 14 core fields:

That covers the essentials: business name, address, rating, phone numbers, activity, and the listing URL.

From there, lobstr.io has two paid add-on functions you can toggle on:

1. Collect Additional Details
2. Collect Emails from Website

With both add-ons enabled, lobstr.io adds 12 more fields:

So with both add-ons on, you get 26 fields total.

Compared to the other scrapers here, a few fields are basically Lobstr-only:

Email is the standout.

Lobstr pulls it from the business's own website.

It's the only tool on this list that returns an email contact without a separate enrichment step.

Affordability

lobstr.io runs on a monthly subscription model.

Plans start at $20/month and scale up to $500/month, each offering a fixed number of usage credits.

The base pricing is simple:

1. FREE plan available
2. STARTER plan → $2.00 per 1,000 results
3. TEAM plan → $0.50 per 1,000 results

But there is one important detail. lobstr.io has two optional enrichment toggles: Collect Additional Details and Collect Emails from Website.

If you turn both on, the cost goes up because you're getting more data per result.

With enrichment enabled:

1. STARTER plan → $6.00 per 1,000 results
2. TEAM plan → $1.50 per 1,000 results

Scalability

lobstr.io handles large input and you can push throughput with Slots when you need results faster.

On the input side, you can upload PagesJaunes search URLs in bulk via CSV.

That's the cleanest way to run multiple cities, categories, or filters without babysitting the setup.

On the output side, the base speed is 164 results/min — about 2.36M results/month under heavy active use (164 × 14,400 minutes).

Each Slot adds another scraper running in parallel (up to 20 per run), so you're not stuck at 7/min when volume grows.

You can trade more concurrency for dramatically higher throughput.

So in practice, CSV input makes big runs easy to start, and Slots make big runs finish faster.

That also makes scaling more stable.

With concurrency, a larger job doesn't mean an exponentially longer wait — you add more Slots and keep runtime under control.

Ease of use

lobstr.io keeps the workflow simple and practical.

The setup is URL-first, so you can paste a PagesJaunes search URL and start from the search you already built on the site.

You can also upload a CSV if you want to process multiple search URLs in bulk.

Limiting the scrape is straightforward.

You can cap max unique results, and set max pages (meaning how many PagesJaunes search result pages Lobstr is allowed to crawl).

The key toggles are easy to find and configure, so you're not digging through menus before your first run.

Scheduling is built into the main workflow.

It's mainly for monitoring: catching new listings and changes to existing ones over time.

You can run manually or set recurring runs by minutes, hours, days, weeks, or months.

Getting data out is also clean: export to CSV, or send results directly to Google Sheets, Amazon S3, SFTP, or email.

If you want automation, the Make.com integration plugs into 3,000+ apps without extra setup work.

Speed

lobstr.io's speed depends on which add-ons you have enabled.

That works out to roughly 164 results per minute — the fastest result in this test.

That drops to roughly 7 results per minute — because the tool is fetching each business website to extract the email.

The speed trade-off is direct: you get email contacts, but each result costs more time.

However, speed is adjustable.

You can increase Slots to run more work in parallel and raise throughput when you need it.

Customer support

lobstr.io offers support through a live chat pop-up on the website.

That makes it easy to ask for help without leaving the platform or digging through docs first.

Support is also one of the things users consistently praise.

The team is known for quick replies, technical answers, and actually helping when something breaks.

Best for

lobstr.io is best for teams building outreach lists that need email contacts alongside directory data.

It's the fastest base scraper in this test, and Slots let you push throughput further when volume grows.

The trade-off is data delivery: export is CSV only, and turning on email enrichment drops speed from 164/min to 7/min — plan your runs accordingly.

2. Apify

For the comparison, I picked the PagesJaunes actor with the most users.

It's the simplest way to avoid picking a dead actor.

Key features

1. 38 unique data dimensions — most fields of any tool here
2. Exclusive: full weekly opening hours, verified business status, legal business name
3. Bulk URL input via Bulk edit
4. Cost-per-run limit (not row limit)
5. Schedule recurring scrapes (separate tab)
6. Cloud-based, no installation needed
7. Export to CSV, JSON, XML, Excel, or HTML
8. Integrates natively with Make, Zapier, and n8n

Data

Apify returns the widest schema here.

It gives you 38 unique data fields, though the raw column count is higher because some fields repeat across multiple columns.

Phone numbers, images, external links, and weekly opening hours are all expanded in the export.

The standout field nobody else has is opening_hours.

Apify returns the full weekly schedule — Monday through Sunday — with time slots.

If you are building a field sales route or need to know business hours, this is the only tool that gives you that.

raison_social is also worth noting.

It is the legal registered name, which can differ from the trading name. lobstr.io and PhantomBuster only return the display name.

Here are the fields exclusive to Apify:

Apify has no email extraction. If outreach beyond phone is part of your workflow, you will need to enrich the data separately.

Affordability

Apify uses a pay-per-result pricing model.

For this actor, the pricing is simple:

1. Free plan: $5/month platform credit
2. Pay-per-result: $1.50 per 1,000 results

One thing to note: the cost does not drop as you scale.

So whether you scrape 1,000 results or 100,000 results, the per-result rate stays the same.

Scalability

Apify can handle large inputs, but scaling is mostly linear.

On the input side, there's no CSV import in the main setup. Instead, you paste PagesJaunes profile URLs using Bulk edit.

In my test, I added 10,000+ profile URLs, and Apify handled the input without issues.

On the output side, my baseline test ran at 57 results/min, which is about 821k results/month under heavy active use (57 × 14,400 minutes).

What you don't get is a Slots-like concurrency dial to push throughput on demand.

So scaling is mostly linear: more results usually means longer runs, not "turn it up and finish sooner."

So in practice, Bulk edit makes big runs easy to start, and Apify's speed makes them doable.

But you don't get the same "add concurrency" escape hatch.

That makes scaling less stable at volume. As the job grows, so does the wait — there's no lever to compress that window.

Ease of use

Apify keeps the interface simple, and most of the setup is straightforward.

The workflow is URL-first. You can paste a PagesJaunes search URL and run the actor without rebuilding the search inside Apify.

You can also paste specific PagesJaunes profile URLs if you already know exactly which businesses you want.

Limiting the scrape is the one part that feels unintuitive. There's no clear "max results/URL" setting in the main setup.

Instead, you cap the run using a maximum cost per run, which works, but it's less natural than setting a simple row limit.

Scheduling exists, but it's not part of the main setup flow.

It lives in a separate area, so it's easy to miss on a first run.

Export is where Apify feels strongest. Once the run is done, you can download results in multiple formats, including JSON, CSV, XML, Excel, and HTML.

Integration-wise, Apify plays nicely with automation tools like Make, Zapier, and n8n, so getting the data into another workflow is usually painless.

Speed

Apify is not slow, but it is not the fastest either.

In my test, it collected 1,000 PagesJaunes results in 17 minutes and 28 seconds.

That works out to roughly 57 results per minute, or almost 1 result per second.

Customer support

Apify gives support through live chat, a ticketing system, and a Discord community.

The live chat is better for basic platform questions.

That is where you can report bugs, ask actor-specific questions, and get responses tied to the scraper itself.

For this PagesJaunes actor, the response time looks strong.

Best for

Apify is best for people who prioritize maximum data coverage and want a fast way to pull rich directory records.

It handles large runs reliably, but you don't get a simple "go faster" dial — scaling is mostly about letting longer jobs finish.

Pricing stays linear as volume grows, so it's predictable — just not the kind that gets friendlier over time.

3. WebScraper.io

Key features

1. 10 data fields
2. Bulk Start URL Import via Text or CSV (up to 20,000 URLs)
3. Replace or Append URL list options
4. Scheduling: daily, interval, or custom cron expression
5. Parser: built-in post-processing (regex, strip HTML, virtual columns, and more)
6. Data quality control: automated run checks with email or Cloud notifications
7. Cloud-based option available
8. Concurrency control via parallel tasks
9. Export to CSV, JSON, or XLSX
10. Automated delivery to Dropbox, Google Sheets, Google Drive, Google Cloud Storage, Amazon S3, Azure Blob Storage

Data

WebScraper.io returns 10 data fields per listing.

The address comes as one unstructured string.

There is no separate city, zip code, or street field.

If you need to filter or sort by location after the scrape, you will need to parse the address yourself.

Affordability

WebScraper.io runs on a monthly subscription model.

There's a free 7-day trial, so you can test it before committing.

WebScraper.io pricing is based on URL credits, where 1 credit = 1 page loaded by the cloud scraper (not "1 business result").

That means the real cost depends on how many pages your scrape needs to crawl to get the rows you want.

That makes costs harder to predict upfront.

In my PagesJaunes run, it loaded 520 pages and returned 472 records (1.1 pages per record).

So 1,000 records took roughly 1,100 URL credits in this setup.

Using the plan limits shown here, that works out to an effective cost of roughly:

1. Project: $10.60 per 1,000 records (based on my run)
2. Professional: $5.30 per 1,000 records (based on my run)

In practice, you'll pay more than you expect if you assume pages = records.

I thought it would be cheaper until I did the math.

Note: On the Scale plan, you're paying for parallel running jobs, so cost is driven more by throughput needs than URL credits.

Ease of use

WebScraper.io is URL-first, but the workflow feels more technical than the others.

You start by pasting a PagesJaunes URL, and the platform matches it to the right prebuilt scraper.

Once you click Import & Run, it goes straight into scraping.

The problem is you can't really limit the run upfront. There's no clear max records setting, and there isn't an obvious max pages cap either.

Since the platform bills by pages loaded, that missing "stop after X pages" control makes big runs harder to manage confidently.

The setup feels quick, but the dashboard is where things get busy.

The workflow is spread across a lot of tabs: Scrape, Schedule, Parser, Data quality control, Edit, Bulk Start URL Import, Tags.

The Parser is useful if you're running recurring scrapes and want cleaner exports automatically.

For one-off exports, it can feel like extra setup — especially once regex and virtual columns show up.

Data quality control is great for catching broken runs in automated workflows, but it adds another layer to learn.

Scheduling is available, but it's not part of the main setup flow.

It lives in a separate area, so it's easy to miss on a first run.

Once the scraping job is finished, WebScraper.io lets you download the results as CSV, JSON, or XLSX.

Automated data export is available too.

WebScraper.io can send scraped data automatically to Dropbox, Google Sheets, Google Drive, Google Cloud Storage, Amazon S3, and Azure Blob Storage.

Bottom line: WebScraper.io is more configuration-heavy than beginner-friendly.

Scalability

WebScraper.io can handle bulk inputs properly.

You can upload multiple PagesJaunes start URLs using Bulk Start URL Import.

It supports Text or CSV files, with each start URL added on a new line.

The start URL limit is 20,000 URLs, which is strong for larger scraping projects.

You can also choose whether to Replace the existing URL list or Append new URLs to it.

On the output side, my speed test came out to about 5 results/min.

That's roughly 72,000 results/month under heavy active use (5 × 14,400 minutes).

WebScraper.io supports concurrency via Parallel tasks, which cap how many scraping jobs you can run at the same time.

On the Scale plan, you're paying for parallel running jobs, and WebScraper even estimates monthly URL capacity based on the driver (Full JS vs Fast).

The concurrency support is what keeps WebScraper.io stable at scale.

Larger input lists don't mean proportionally longer waits — you add parallel tasks to hold runtime down.

Speed

WebScraper.io is the slowest tool in this test.

In my test, it collected 472 PagesJaunes results in 1 hour, 30 minutes, and 3 seconds.

That works out to roughly 5 results per minute.

But for larger PagesJaunes scraping projects, the speed becomes a bottleneck quickly.

Customer support

WebScraper.io gives you a few support options.

You can use AI Answers for quick questions, search the help docs, or contact support by email.

In my test, the AI assistant was useful for simple product questions.

For example, it helped explain where integration settings live and how the Replace and Append options work for bulk URL imports.

That makes the support experience helpful for basic workflow questions.

But there is not much third-party review data to lean on.

I checked G2 and Capterra: WebScraper.io had 0 reviews on G2, and I could not find it listed on Capterra.

Best for

WebScraper.io is best for teams who need bulk scraping at scale and can justify higher costs to get it done.

It supports parallel job throughput and large input lists, but it's expensive, especially once you look at the cost per record.

Speed is also a constraint, so it's a better fit for scheduled, ongoing pulls than "I need a big export today."

4. PhantomBuster

It allows you to extract data and automate actions across over 15 platforms, without writing any code.

Key features

1. 4 data fields: name, address, phone, listing URL
2. Google Sheet or CSV file bulk input
3. Control results per search
4. Maximum execution time cap to manage credit usage
5. Auto-retry on failure
6. Schedule recurring scrapes
7. Cloud-based, no installation needed
8. Export to CSV
9. Slack and webhook run notifications

Data

PhantomBuster returns 4 fields per listing.

That is the bare minimum.

You get the business name, address, phone number, and PagesJaunes URL.

But that is pretty much it.

No rating. No activity category. No description. No zip code. No image.

The address also comes as one unstructured string, instead of separate street, city, and postal code fields.

So the tradeoff is simple.

PhantomBuster is good if you only need a fast name-and-phone list.

But if you need richer business context, the schema is too thin.

Affordability

PhantomBuster runs on a monthly subscription, but pricing is based on execution time.

The free plan gives you 30 minutes of execution time, which is enough to test a small PagesJaunes scrape.

Based on my test speed of 100 results in 40 seconds, here's the rough cost:

1. FREE plan: 30 minutes/month execution time
2. $69/month → $0.38 per 1,000 results
3. $439/month → $0.16 per 1,000 results

On paper, that makes PhantomBuster affordable at scale.

But this estimate is based on a light dataset, so the real value depends on whether those few fields are enough for your workflow.

Scalability

PhantomBuster scales on input, but it doesn't really scale on throughput.

On the input side, you can load multiple PagesJaunes search URLs via Google Sheets or CSV.

That makes multi-city or multi-category runs easy to queue.

The limiting factor is execution time.

PhantomBuster doesn't give you a way to increase throughput with parallel workers, so scaling is basically: run more, wait more, pay more minutes.

That makes it unstable at scale. As volume grows, so does wait time — and there's no way to bring it back down.

Ease of use

PhantomBuster keeps the workflow simple and URL-first.

You can paste a single PagesJaunes search URL, or use a Google Sheet or CSV file with multiple search URLs.

Limiting the scrape is clear. You can set how many results to pull per search, and control how many searches the tool processes per launch.

Scheduling is built in, so it works for recurring directory pulls without extra setup.

Maximum execution time per launch helps you avoid accidentally burning through your monthly minutes.

Exports are straightforward (CSV), and you can send run updates via Slack or webhooks if you're wiring it into a workflow.

Speed

PhantomBuster is fast. Really fast.

In my test, it collected 100 PagesJaunes results in 40 seconds.

That works out to roughly 2.5 results per second, or 150 results per minute.

For a no-code scraper, that is a strong result.

However, part of that speed comes from a lighter dataset.

PhantomBuster collects fewer data points compared to tools that pull richer business details.

So the speed is impressive, but it should be judged with the data depth in mind.

Customer support

PhantomBuster offers support through an AI assistant and a request form.

You can use the chatbot for quick questions, or submit a support request by email if you need help from the team.

I did not run into an issue during my own test, so I did not need to contact support directly.

But user reviews raise a concern.

In G2 reviews, some users mention poor customer support, long response times, and vague documentation.

Best for

PhantomBuster is best for fast, high-volume call lists where you don't need much beyond basic fields.

It's the quickest way to pull a lot of rows, and pricing can stay attractive when you're operating at scale.

The trade-off is data depth: if you need richer directory fields, you'll end up pairing it with another tool anyway.

FAQ

What is the best PagesJaunes scraper for email outreach?

lobstr.io is the best fit if email outreach matters.

It is the only tool on this list that extracts email contacts from business websites without a separate enrichment step.

What should beginners look for in a PagesJaunes scraper?

Beginners should prioritize URL-first input, simple result limits, CSV export, and support.

If you are new to scraping, avoid tools that require API setup, proxy management, or custom code just to get a basic business list.

Which tool should I choose if I only need names and phone numbers?

PhantomBuster makes the most sense if you only need a fast name-and-phone list.

It was the fastest option in the test, but the data is very thin.

Can no-code PagesJaunes scrapers replace a custom scraper?

For most business use cases, yes.

If your goal is to collect leads, compare local businesses, or export clean CSV data, no-code tools remove that work.

You don't need to maintain scripts, retries, or scraping infrastructure.

A custom scraper only makes sense if you need full control over the scraping logic or highly specific fields.

Conclusion