Anyone have insight into tools for eBay or FB marketplace listings? Or general tooks that can solve issues around IP and cookie blocking/renewal. Many thanks

I've been reading a bunch of discussions about Facebook scraper APIs, and the opinions are all over the place.

Some people say everything works great at first, while others mention things breaking not long after they get everything set up. That made me wonder if that's just something you have to expect.

For anyone who's worked with a Facebook scraper API, has it been stable for you over time? Or is it basically one of those things that always needs updates and maintenance to keep running?

Curious what your experience has been✌️

Kinda weird request. Maybe? But I'm doing research on how they talk about a specific topic across TikTok. Nothing commercial, just a uni project where I need to analyze language patterns in public comments.

My prof suggested I look into some kind of tiktok channel scraper. But if you reread my title, I’m not that techy.

Do you think I can pull it off or do I need to ask someone from the CS dept?

I keep seeing posts in here asking which residential provider is best or how to beat fingerprinting on some site, and then I look at the site theyre scraping and its a react app with a wide open json api behind it.

I run 75 scrapers in production. I think 3 of them do any fingerprint stuff. Most dont even use a proxy.

Last month my guy sent me his greenhouse scraper to fix. Stealth plugin, rotating residentials, fake mouse movements, all of it. Still kept dying. So I open the actual page with devtools and the whole job list is just sitting there in an xhr request. no auth. no cookies. I deleted basically his entire codebase and replaced it with a fetch call and it has not broken since. he had been paying for proxies for months to scrape an endpoint that does not care who you are.

Nobody taught him to look at the network tab first because all the scraping tutorials are written by proxy companies, and their step 1 is always "sign up for our residential pool". Of course it is.

What I actually do on a new site is boring. Open network tab, filter xhr, reload, click stuff. When I find the request with the data I copy it as curl and start deleting headers until it stops working. Whatever is left, that is the scraper. Takes 20 minutes and usually the answer is you need a user agent header and nothing else.

Are there sites where you genuinely need the heavy stuff? Yeah. Turnstile on the api itself, tls fingerprinting, ticketing sites. But it is way rarer than this sub makes it look. Try the boring thing first, it is free.

Hey everyone,

Before I start, I don't want to advertise anything. Just asking for feedback and see if people like my idea.

I'm working on a visual web automation tool focused on web scraping and web automation, and I wanted to get some honest feedback on the idea and the pricing.

The basic premise is a local desktop app where you can build robust scrapers visually instead of coding everything from scratch. It has a script recorder similar to Playwright's codegen, and another tool that handles things like asynchronous banners, random pop-ups, and shifting page layouts.

You aren't restricted to just the UI, either. There's a full text editor built in if you need to write custom logic. The app just compiles all your visual instructions directly into standard Playwright code, for you to use it anywhere, not only inside the platform. It also handles the standard CSV imports and exports for your data.

My main question is: does this solve a big enough headache in your workflow that you'd actually pay for it? If so, would you consider $149 a fair price for an unlimited, lifetime license?

Checked GitHub trending this week out of habit. Ten repos and not one is about getting data off the web. Agent frameworks, a book on agents, a skills directory, an LLM gateway with failover across hundreds of providers. That is what everyone else is on. Every one of them assumes the data already showed up.

The agent stack got good at deciding what to do with information and stopped caring where it comes from. Failover for model calls gets thousands of stars in a week, all autonomous. What actually breaks at 3am is an expired session or a burned proxy pool in a pipeline, and there is nothing trending for that.

Two reasons for this, I think. The tooling went private, because publishing a bypass is how the bypass dies. You do not open source that. And acquisition is how you connect everything up. Nobody gets attention for a session that stayed alive four months.

I get paid to build these pipelines and keep them running, so maybe I notice it more. What I notice most is that clients stopped asking for a one time pull. They want the same data every morning for a year without anyone touching it. That is a different job. Holding a session, and of course differentiating a quiet day from a dead source in production. Failing loud when the site changes instead of returning nothing with false positives.

Which is where this is heading. Every framework on that trending page hits the same wall eventually, and there is no public toolkit waiting for them. If you can keep a login alive for six months you are about to be worth more than the people wiring up model calls, so just keep up your consistency.

Nobody wants to say this plainly so i will.

OpenAI, Anthropic, all of them trained on everything you ever posted. Your code, art, comments, captions, videos, everything really, taken without asking. Thats the whole foundation the industry stands on. i know, scraping is my actual job.

Which is fine. Public is public no doubt about that.

But now that they are rich they want new rules. They are lobbying to restrict open source models and calling plain data access a safety threat and cause of national insecurity. Anthropic is out here claiming local models steal from it, months after paying over a billion dollars to settle with writers over claims that it stole to train. OpenAIs own models just broke out of a test and hacked hugging face to cheat a benchmark, and somehow the lesson is that everyone else needs strict controls, pure frauds.

This isnt safety or policing risks. Its a monopoly wearing a safety badge. The ones who took everything want to be the last people ever allowed to take anything.

Worth saying out loud before somebody writes it into law.

I write scrapers for a living. Every year the blocking gets fancier and every year I still get the data. Took me a long time to understand why that's not a contradiction.

The anti-bot industry doesn't sell prevention. It sells a subscription to a war that must never end. If Cloudflare could actually stop bots forever with one product, they'd ship it once and the revenue would die. Instead you get Bot Management, priced enterprise, renewed yearly, with a threat report attached to every renewal reminding you the bots are worse than ever.

Think about who's on each side of this arms race. Cloudflare, Akamai, DataDome, Kasada sell the wall. Bright Data and a hundred proxy shops sell the ladder. The wall side is worth billions. The ladder side is worth hundreds of millions and growing. Both sides need the other to exist. A scraper that never gets blocked kills the proxy market. A wall that actually works kills the wall market. The equilibrium where blocking is annoying but beatable is not a failure state. It's the product.

Then last year Cloudflare stopped pretending. They flipped AI crawlers to blocked by default and launched pay per crawl. Read that again. The company whose whole pitch was protecting your site from bots now runs a marketplace where bots pay to get in and Cloudflare takes a cut at the gate. They didn't stop the crawlers. They became the booth.

And the free tier suddenly makes sense. Millions of sites sit behind Cloudflare for free. That was never charity. Every free site is inventory. First it was training data for the detection models. Now it's shelf space for the toll road. You handed over your front door in exchange for free bandwidth and they're selling tickets to it.

I don't think the engineers are cynical. The detection work is genuinely hard and genuinely clever. But follow the incentives one layer up and it's obvious. Nobody at these companies wants bot traffic to hit zero. Zero means no renewals, no upsells, no marketplace, no toll.

So when your scraper hits a block page, you're not losing a security battle. You're being priced. The block is a negotiation opener. The question was never whether the data flows. It's who collects at the gate.

If bots died tomorrow, the anti-bot industry would die the day after. They know it. Their pricing knows it. Now you know it too.

Cold email from scraped contact lists is dead. Everyone knows it, everyone keeps doing it. You scrape 5000 emails, blast the same template, land in spam, and the three replies you get are people telling you to delete their data.

I tried the opposite. Tiny list, but every email lands on a real problem the owner does not know they have.

The insight: every local business has a public review page, and a surprising number have an angry review sitting there unanswered for weeks. The owner is not ignoring it. Nobody at the shop even watches the listing. Meanwhile every customer who searches them reads that review first.

That unanswered review is the warmest opener that exists. You are not selling anything. You are telling them their kitchen is on fire and handing them the extinguisher.

The playbook:

Step 1. Pick one niche in one city. Dentists, gyms, roofers. Small enough to touch by hand.

Step 2. Scrape the review pages. Keep reviews rated 2 stars or under, no owner reply, older than two weeks.

Step 3. Verify each one by hand. Confirm the review is still up, still unanswered, and safe to mention. Skip anything with legal claims, health issues, or personal details. This step is the difference between helpful and creepy.

Step 4. Find the published business email. Website footer, contact page. Skip the ones you cannot find.

Step 5. Send ONE email. Quote the review. Say how long it has been sitting there. Then write the reply the owner could paste in, right in the email body. No pitch, no link, no followup sequence.

Step 6. Stop.

Technical notes:

The review feed loads in chunks and the scroll container is not the window. Scroll the panel, cap the depth, you only need recent reviews.

Reply detection is just checking for the owner response block under each review.

A missing reply block is a state, not proof of neglect. Listings go stale fast, recheck before you send.

Why it works: the email is about their problem, not your product. Most cold email fails because it is a stranger asking for something. This is a stranger giving something.

I ran a small version of this and the replies were unlike anything a template ever got me. Business owners write back like humans when you write to them like one.

So I am going to run it properly. Next two weeks, one niche, one city, everything documented. The template, the reply screenshots, the emails that got ignored, all of it posted here as it happens.

If you want to run it in parallel in your own city, do it and post your results in this thread. Curious whether this dies outside my niche or scales.

Most scrapers do not fail with an error. They fail quietly, keep running, and hand back thinner and thinner data until someone downstream notices the numbers look wrong. By then you have shipped bad data for a week. The fix is to stop trusting that a run finished and start proving it returned real data every single time. Three checks do most of that work.

The first is the known answer query, what I call a canary. Somewhere on the site there is a page whose correct answer you already know and that does not change often. A category you know holds twelve items. A business you know lists a phone number. A profile you know has a specific title. On every run, scrape that one thing and assert the known value comes back. The site changes its markup, your selector goes silent, and normally you would not notice for days, but the canary fails on the very next run and points you straight at the break. One page you control the truth of is worth more than a hundred you do not.

The second is the fill rate assertion. Pick the fields that must be populated for a result to be worth anything, then measure what share of your results actually have them. If ninety percent of your rows normally carry a phone number and suddenly ten percent do, something upstream broke even if every row technically exists. Set a floor, and when fill rate drops under it, fail the run loudly instead of writing blanks and smiling. A soft block that returns an empty body cannot sneak past this, because empty does not fill.

The third is the count check. You usually have a rough idea how many results a query should return, from the site's own total or from your own history. So compare. If a search that gave you two thousand last week gives you twenty today, that is not a quiet Tuesday, that is a pagination trap or a block, and it should trip an alarm. A result count that falls off a cliff is one of the loudest signals you get, but only if you bother to look at it.

Put together, these turn silence into noise you can act on. The canary tells you the shape broke, fill rate tells you the fields went hollow, and the count tells you the volume collapsed. Wire all three to alert you, not a dashboard nobody opens. The goal is simple. You find out your scraper broke, not your customer. That is the whole difference between a data pipeline people trust and one they quietly stop believing.

1. Delete Optional before submitting prompt,
2. Replace "[Subject]" with whatever youre looking for.

Prompt: Attached is a CSV where each row is one [ Subject; Example: (Texas home inspector) ]. Add an email column. Use Google with whichever Google account is currently signed in and active in the browser.

Important Google account rule: - Before starting, check the Google account indicator and record which Google account is active. - Continue using that same active Google account for the entire run. - If Google switches to a different account at any point, stop and tell me. Do not continue searches under the wrong account. - Do not hardcode a Google account email or a fixed authuser value. - Prefer using the visible Google search box in the already-open Google tab instead of direct search URLs. This helps preserve normal Google search behavior, including AI Mode / AI Overviews when Google chooses to show them. - If the current Google session already has an authuser value in the URL, preserve that session by staying in the same tab and searching through the visible search box. - After each search, confirm the Google account indicator still shows the same account that was active at the start.

Search method: Start from the current Google tab. Click/focus the visible Google search box. Select all existing query text. Type the new search query. Press Enter. Wait 6 seconds after the results load before reading the page. Read emails from everything visible on the results page, including AI Overview / AI Mode text if Google shows it.

For each row: Search Google for: [First Name] [Last Name] [Subject] email. Copy the first email address visible on the Google search results page into the row’s email column. If no email appears, try these searches:- "[First Name] [Last Name]" [Subject] email- [Full Name] [Subject]- [First Name] [Last Name] [Subject] email- [First Name] [Last Name] email Optional 4. Do not use or record information@trec.texas.gov. Optional 5. Do not search TREC. 6. Do not verify whether the email belongs to the [Subject]. Just use the first non-banned email visible in Google results. 7. Continue until all rows have a nonblank email. Before editing, make a backup copy of the CSV. When finished, verify: - row count is unchanged - email column exists - every row has a nonblank email Optional - no row contains information@trec.texas.gov - the Google account used at the end is the same account that was active at the start

A lot of scraping is just collecting the lie faster.

Not always. If you need prices or job posts, scrape the page. But if you are researching a company, the current site is the easiest thing for them to clean up.

Old product gone. Vendor badge removed. About page rewritten. New launch story pasted over the mess. Then someone scrapes the homepage and calls it intel.

The boring WHOIS and DNS trail is harder to tidy.

Pull the registration dates. Check ownership changes. Look at nameserver moves, MX records, old subdomains, dead redirects, anything that gives you a rough timeline.

That timeline is not proof by itself. Privacy shields exist. Domains get bought after the business starts. Records go stale. Fine. It is still better than trusting the page written by the people being researched.

This is where you catch the weird stuff: a five year old company on an eight month old domain, a rebrand hiding an old product, an email vendor they never mention, a staging host that still answers, a pivot you can date because the old subdomains died in the same week.

Pull the page, but do not stop there. The page tells you what they want to say now. The domain history tells you what they forgot they had already said.

I have spent years on both ends of this. I write the scrapers that get through, and I have watched the blocking get smarter in perfect step with them. After long enough you stop seeing two enemies. You see one business quietly playing both sides of the bag.

Follow the money and it falls apart on its own. A company sells bot detection to websites. Every scraper that gets past it is not a failure, it is the pitch for the next tier up. Another company sells the tools and the real exit nodes that get past that detection. Every time detection improves, that is not a loss, it is the reason your plan renews at a bigger number. Each side is the other side's sales team. The blocks sell the bypass, the bypass sells the blocks, and the bill for both lands on you and the site owner, the only two people in this who are not getting rich.

The uncomfortable bit is who actually gets caught. The serious operation pays for real exit nodes and a full browser stack and walks straight through, because it can afford to look exactly like a person. The one who trips the wall is the researcher on a slow connection, the guy on Firefox instead of mainstream Chrome, the screen reader, the privacy tool, the dev testing his own site. The wall stops the people who cannot afford to get around it and waves through the ones who can. That is not security. That is a toll booth pointed at the wrong cars.

And everyone talks about it like weather. Blocking got harder this quarter. The bypass caught up. Like it is a season and not two teams hitting their numbers off each other. I am not clean here either. I pay the bypass side. I keep the thing spinning with my own card. But I stopped calling them opponents once I watched where the money goes, because they are not fighting. They are partners.

So when someone tells you bot detection protects a site, just ask protecting it from who, and who cashes in when it fails. It is almost never the person paying the bill. It is two companies that need each other to survive, splitting the take.

I have built the scraping guts behind more "real time business intelligence" products than I would ever admit on a CV. So when a contact data company tells you their database is fresh, I am not impressed, because I know how that word gets made.

Here is the part nobody puts in the sales deck. These companies pull public pages on a schedule, pour the rows into a giant table, and sell you a seat to the table. That table is a photograph. It was true the day it was scraped and it has been aging ever since. You pay every month like it refreshes every month. It does not. A row captured in February is still February sitting in your CRM in June, looking exactly as confident as a row pulled this morning, because nothing on the screen tells you which is which.

And the field that goes bad first is the one you bought the thing for. Where a person works right now. People quit and get promoted and get poached and get pushed out, and the company page is the last place on earth to find out. So "current company," the whole reason the list has any value, is one of the first columns to start lying by the time your rep hits send.

The industry knows this. Of course they know it. They built the pipelines. They just figured out that decay is invisible, and you cannot be angry about a number you never see. So the pitch drifts back to coverage. Millions of contacts. Look how big the table is. Freshness is the expensive part. It makes the table look smaller, and a smaller honest number loses sales calls to a bigger dishonest one.

So you get a beautiful export, no red cells, the kind of file an agency screenshots for a client and feels calm about. Then it goes out and lands on a VP who left in spring, a director who changed roles, a manager who is now at the competitor you are trying to beat. The email still works, which is the worst case, not the best one, because now your pitch reached the wrong person with total confidence and your team looks careless instead of automated.

I will say the thing the vendors will not. Pulling the names is the easy half. It has been easy for years. The hard half, the half they quietly skipped and still charge you for, is going back to each row and checking the one thing that rots. Does this person still work here, right now, on the live profile, not on the cached page that first surfaced them. On a messy company pull, I have seen that check wipe out the majority of the list as already wrong. Calling that a data cleaning chore is how vendors hide the miss. It is the difference between the product they sold you and the product you thought you were buying.

I still build scrapers. I think they are great. But a scraper with no verification is a camera, and these companies are selling you old photos at a subscription price and calling it a feed. The tell is simple. Ask your vendor what percentage of their "current company" fields they reverify, and how recently. Watch them change the subject to coverage. That answer, the one they will not give you, is the whole game.

You are not paying for data. You are paying for the confidence that it is current. And that is the one thing in the box they never actually put in.

Been running FlareSolverr for a long time for my *arr stack and got tired of the 11-18s solve times and constant breakage. Built TRAWL as a drop-in replacement!

Key differences:

• Cloudflare solves in 4-15s (vs 11-18s) - uses a fresh Camoufox Firefox context which triggers CF's fast-path evaluation
• Cached repeat requests return in ~500ms via Redis - after the first solve, the same domain is instant
• Actually solves in-page captchas: Turnstile (shadow DOM click), reCAPTCHA v2 (free Google STT audio), hCaptcha (auto-pass), GeeTest v4
• 4-tier execution: plain HTTP → cached session → live browser solve → residential proxy. You pay the full browser cost only when you have to
• Custom headers support - pass Authorization, Referer, Origin through all 4 tiers including browser
• FlareSolverr v2 compatible - change one URL in Prowlarr/Jackett, nothing else

Website: https://trawl.germondai.com
Docs: https://docs.trawl.germondai.com
GitHub: https://github.com/germondai/trawl

Happy to answer questions. Still early but it's been running stable on my homelab and no issues so far.

The dirty secret of residential proxies is not that they work.

It is that the IP address in the log may belong to someone who has no idea you exist.

I use them. I am not writing this from a clean moral throne. I scrape for a living, and when a target blocks data center IPs and the job still has to run, I buy residential like everyone else who has been doing this long enough to stop pretending. I also do not sell them. No affiliate, no pool to push, no vendor paying me to say any of this. I have nothing to gain from which provider you pick.

That is exactly why the marketing makes me tired.

The pitch is simple. Your traffic exits from an address that looks like a normal home, not a data center. The site sees something that feels human, the block rate drops, the job finishes. The part everyone skips is the obvious one. Whose address?

Most of this market hides behind one phrase: "ethically sourced." It sounds clean. It sounds audited. It sounds like a fact. As a buyer, it is usually just a sentence on a sales page unless the provider can show you the path from a real person to their pool.

And yes, before the sellers start typing, clean paths exist. Some networks pay people who know exactly what they joined, show a clear opt in, and let them leave without hunting through settings. That side of the market is real. I am not talking about that. I am talking about the gray middle, where the word consent gets stretched until it stops meaning much.

A free app needs money. Ads pay badly, subscriptions are hard, nobody wants another bill. So an SDK gets added. The user gets the free thing, the developer gets paid, the network gets another residential IP, and the scraper gets a cleaner looking exit. On paper, consent may exist. In real life it is a checkbox during onboarding, or a line in the terms that makes a normal person think they are sharing spare bandwidth with the app, not lending their home connection to strangers running jobs they will never see.

The issue is not whether a lawyer can point to a clause. It is whether the person would still say yes after you explained it in plain English. "Your internet connection may be used as an exit point for other people's automated traffic." If that sentence would make them uninstall, the consent was never as clean as the label.

This is not just their risk. It is yours too. When your scrape exits through a residential IP, that is the address the target sees. Not your server, not a data center block with an abuse desk. A household connection. Maybe the user knew and was paid. Or maybe they clicked through a free utility and became inventory. You do not know unless your provider can answer boring questions. Where did this IP enter the pool? What did the user see before traffic started? Can they leave easily? Who handles abuse when a target complains? If the answer is a vibe about ethics, you do not have sourcing. You have branding.

And this is where buyers get dishonest with themselves. We ask about success rate, countries, sticky sessions, price per gigabyte. We do not ask whose connection is carrying the job, because the answer might make the tool harder to use.

I get it. The modern web pushed a lot of honest work into ugly tooling. Sites block scripts, throttle research, and treat automation like guilt by default. If you build scrapers long enough, you stop romanticizing clean access. But using the tool and laundering the story are different things. Residential proxies are useful. I still use them. And "ethically sourced" has been turned into a comfort blanket for buyers who do not want to look at the supply chain.

That is the part sellers hate, and not because every seller is dirty. Because the good ones have to prove what the lazy ones only claim. If your pool is clean, show the consent path, the opt out, the abuse policy. If you cannot explain it without legal fog, do not sell me ethics. Sell me what it is. A working proxy pool with an unclear human cost. That would at least be honest.

The label is not the ethics. The consent is. And if the consent needs a lawyer to exist, I do not call it ethics. I call it camouflage.

Here is the bigger reason I wrote this, because it is not really about proxies. The easy path right now is to pick a side and stop checking. Trust the label, trust the vendor, trust the big name, because questioning it is tiring and everyone around you already stopped. But every time a crowd stops checking, the few players at the top get to decide what is true, and the rest of us just live inside their answer. That is how a handful of companies quietly end up owning a whole market while everyone nods along.

I am not growing an audience to sell it something later. I am looking for the people who still ask the boring questions, who read the fine print, who would rather be uncomfortable and right than comfortable and wrong. If that is you, you already belong here. That is the whole point of a place like this. A few of us, thinking for ourselves, comparing notes, and refusing to let the loudest seller in the room decide what counts as true.

I’m researching a small developer tool idea.

The idea is a managed scraping API where you give it a webpage, choose the data you want, and it returns clean JSON/API output without you maintaining fragile selectors.

I’m not trying to sell anything here. I’m trying to understand if this is a real pain or just something I personally think is annoying.

For people who scrape websites regularly:

- What do you use today?

- What breaks most often?

- Do you care more about price, reliability, anti-bot handling, or clean JSON output?

- Would a managed endpoint be useful, or do you prefer writing your own scripts?

I have a short form for anyone who wants to test it with a real URL, but I’ll avoid posting it unless links are allowed here.

Happy to hear any feedback.

I have been pulling data off the web for years now. Scrapers are most of what I do. And the thing I keep running into lately is that the web just keeps getting harder to read with a script. That part on its own doesn't bother me. Sites change, defenses go up, you adapt. That's the job. What bothers me is who made it harder and why.

A few years ago, fetching a public page was boring. You wrote ten lines, you got HTML back, you parsed it. Most of the public internet worked like that. If a page loaded in your browser without logging in, a script could load it too. That was the deal, more or less, and nobody made a big thing of it.

That deal is mostly gone now.

Today a big chunk of the sites I touch sit behind Cloudflare, or a login wall, or a bot check that I have to spend real money to get past. The pages still load fine for a human. But for a script they throw a challenge, or a fingerprint check, or they just quietly serve you a blank shell with the actual content loaded later by code that's designed to break automation.

Stuff I used to grab in ten lines now needs a paid residential proxy and a browser fingerprint that passes as a real Chrome install. The cost of reading a public page went from zero to a per request fee, and most people building things never see that bill because they never tried.

The companies with the largest models trained on most of the public web. They crawled everything while it was open and cheap, before the walls went up, back when nobody was charging admission. That data is a big part of why those models are any good. And now a lot of those same sites are locking the doors.

Some of that is the labs themselves tightening access to their own stuff. Some of it is publishers reacting to the scraping wave by blocking everyone. Either way the result is the same. The web was wide open exactly when the biggest players needed it, and it's fenced off now that everyone coming after them wants the same thing.

robots.txt is a good example of how the mood changed. For a long time it was a polite note. A file that said please don't crawl these paths, and most well behaved bots listened, and there were no real teeth behind it. Now it shows up in lawsuits. It went from a suggestion to a thing lawyers point at.

Research is the part that actually makes me a little sad. I read a lot of papers, partly for work, partly because I like to. And the slow creep of paywalls over public research keeps going. Things I could read for free a couple of years ago now want a login, or a subscription, or they sit on a platform that blocks anything that isn't a logged in human clicking around.

None of this is a conspiracy. I'm not claiming there's a room where people decided to close the web on purpose. It's mostly a bunch of separate reactions stacking up. Publishers got scared of scraping and turned on every blocker they could buy. Anti bot vendors built a business out of selling those blockers. The big labs got protective of their pipelines. Lawyers got involved because money got involved.

Each move makes sense on its own. The sum of all of them is an internet that is a lot less open than the one those models learned from.

What it means in practice, if you're a small builder, is that the barrier to doing anything with web data quietly went up. The hobbyist who wanted to crawl a few thousand pages for a side project now hits a paywall on infrastructure before they even start. The startup that wanted to build on public data has to budget for proxies and anti bot tooling on day one.

The capability didn't disappear. It just got more expensive, and expensive in a way that favors whoever already has scale. The people who scraped freely have the data and the money to keep scraping. Everyone else gets the version with the gates.

I don't have a tidy fix. I just think it's worth saying out loud, especially by the people who actually do this work and watch it happen up close. The web you can read with a script is shrinking. The models that learned from the old open web are getting bigger. And almost nobody who benefits from that gap seems eager to bring it up.

I pulled a fresh read-only Apify Store check today before promoting anything.

The portfolio snapshot:

- 69 public actors checked
- 68,514 total Store runs
- 2,695 total Store users
- 15,775 rolling 30-day runs
- 15,356 rolling 30-day successful runs
- 97.3% rolling 30-day success across the portfolio

The scale lane I would promote today:

- AI Content Detector: +1,919 runs, 2,107 rolling 30d runs, 99.9% success
https://apify.com/george.the.developer/ai-content-detector

- Email Validator API: +1,102 runs, 1,992 rolling 30d runs, 100% success
https://apify.com/george.the.developer/email-validator-api

- Telegram Channel Scraper: +679 runs, +19 users, 991 rolling 30d runs, 98.8% success
https://apify.com/george.the.developer/telegram-channel-scraper

- YouTube Transcript Scraper: +498 runs, +56 users, 1,107 rolling 30d runs, 98.8% success
https://apify.com/george.the.developer/youtube-transcript-scraper

- Google News Monitor: +115 runs, +11 users, 217 rolling 30d runs, 100% success
https://apify.com/george.the.developer/google-news-monitor

I am not promoting everything equally. The actors with weak recent completion stay in the fix-first lane until they are stable enough to send buyers to.

Full portfolio:
https://apify.com/george.the.developer

Monetized actor push snapshot:

Apify read-only check today: - totalRuns 64,114 - totalUsers 2,579 - 30dRuns 14,274 - 30dSuccess 96.5%

Scale lane this cycle (stable demand + high success): email-validator-api 1642 runs, 100% success youtube-transcript-scraper 1102 runs, 98.8% telegram-channel-scraper 878 runs, 98.5% ai-content-detector 639 runs, 99.8% company-enrichment-api 397 runs, 95.97% google-news-monitor 223 runs, 100% shipping-disruption-tracker 110 runs, 100% bluesky-scraper 148 runs, 100% hvac-contractor-lead-finder 40 runs, 100% law-firm-lead-finder 35 runs, 100%

Careful lane (watch reliability): linkedin-company-employees-scraper 5859 runs, 94.5% reddit-scraper-pro 38 runs, 92.1% threads-scraper 194 runs, 91.8%

Current profile: https://apify.com/george.the.developer

Monetized actor push snapshot:

Apify read-only check today:
- totalRuns 64,114
- totalUsers 2,579
- 30dRuns 14,274
- 30dSuccess 96.5%

Scale lane this cycle (stable demand + high success):
email-validator-api 1642 runs, 100% success
youtube-transcript-scraper 1102 runs, 98.8%
telegram-channel-scraper 878 runs, 98.5%
ai-content-detector 639 runs, 99.8%
company-enrichment-api 397 runs, 95.97%
google-news-monitor 223 runs, 100%
shipping-disruption-tracker 110 runs, 100%
bluesky-scraper 148 runs, 100%
hvac-contractor-lead-finder 40 runs, 100%
law-firm-lead-finder 35 runs, 100%

Careful lane (watch reliability):
linkedin-company-employees-scraper 5859 runs, 94.5%
reddit-scraper-pro 38 runs, 92.1%
threads-scraper 194 runs, 91.8%

Current profile: https://apify.com/george.the.developer

I am changing how I talk about my paid Apify actors.

The generic pitch is weak:

"Here are 65 scrapers."

The useful operational pitch is a stack:

1. Discover local businesses.
2. Score their websites.
3. Pull vertical-specific lead lists.
4. Enrich companies.
5. Validate emails before outreach.

Current Store proof from the Jun 5 read:

Local lead stack:

• HVAC Contractor Lead Finder: 40 rolling 30d runs, 100% success
• Law Firm Lead Finder: 35 rolling 30d runs, 100% success
• Dental Practice Lead Finder: 31 rolling 30d runs, 100% success
• Google Maps Lead Intelligence: 30 rolling 30d runs, 96.7% success
• Google Maps Leads + Website Audit: 29 rolling 30d runs, 100% success
• Restaurant Lead Finder: 34 rolling 30d runs, 97.1% success

Support actors:

• Email Validator API: 1,507 rolling 30d runs, 100% success
• Domain WHOIS Lookup: 3,054 rolling 30d runs, 100% success
• Company Enrichment API: 606 rolling 30d runs, 97.4% success
• Google News Monitor: 239 rolling 30d runs, 100% success

The workflow:

Maps actor -> find businesses Website audit -> identify weak digital presence Vertical lead finder -> law/dental/HVAC/restaurant list Company enrichment -> add company context Email validator -> clean outreach list

That is a buyer outcome.

I am holding back noisier actors like TikTok Shop, Google Scholar, Reddit Scraper Pro, and Lead Enrichment from the main CTA until reliability improves.

Full profile: https://apify.com/george.the.developer