| Tool | Apify scrapers for Instagram and Facebook |
|---|---|
| Pricing | Paid per use (check official site for current pricing) |
| Category | Data collection and social listening |
| Monetization difficulty | Medium |
In short4 min read
- The scrapers cover Instagram profiles, posts, Reels, comments, and Facebook page posts and comments.
- They are paid per use, priced low enough for small experiments.
- The builder pipes the data into n8n and Python for sentiment and theme analysis.
- Their ideas: focused reports for a few hundred euros, or free samples in outreach.
Social listening has long been a service that big brands buy through enterprise platforms. A social intelligence analyst on r/SideProject is testing a smaller version: collect public posts and comments with low-cost scrapers, analyze them in an automated workflow, and sell focused reports to agencies and brands.
If you already know your way around n8n or Python and want a data-driven service to offer, this breakdown covers what the builder made, how they use it, where the money could come from, and the hard part they openly admit they have not solved yet.
In this article
The gap: enterprise tools, small projects
The builder says they have worked in social intelligence for years, often with tools like Talkwalker. For smaller projects, though, the cost can be hard to justify. Sometimes they only need posts and comments about a specific topic so they can run their own analysis.
In their words, getting that data into their own workflow was often more frustrating than the analysis itself. Because they were already into web scraping, they started building their own tools to close that gap.
What the scrapers collect
The tools are published on Apify, a platform for running web scrapers, as the builder’s own projects. They are paid per use, and the builder says they kept prices as low as possible so the tools are useful for small experiments, even before you have a paying client. They did not list exact prices, so check the official Apify listings for current rates.
| Platform | Data covered |
|---|---|
| Profiles | |
| Posts and Reels | |
| Comments | |
| Page posts | |
| Comments |
How this compares with other ways to get the data
The table below is our own comparison of the three common routes, based on the trade-offs the builder describes. It is not a pricing comparison.
| Approach | Best for | Trade-off |
|---|---|---|
| Enterprise listening platform | Ongoing brand monitoring at scale | Cost is hard to justify for small, one-off projects |
| Pay-per-use scrapers | Focused projects and experiments | You build the analysis yourself |
| Manual copy and paste | A handful of posts | Doesn’t scale past a quick check |
Inside the workflow
The builder runs the scrapers inside n8n and Python workflows. Those workflows collect comments, analyze sentiment and recurring themes, and feed into social listening reports. They review the results themselves before using them.
Their example: following a public controversy across Instagram and Facebook, collecting reactions, and seeing what people keep bringing up as the story develops. That kind of question is a natural fit for a short report. A brand or agency wants to know what people are saying and why, and they want it this week, not after a long platform onboarding.
The manual review step is worth keeping. Automated sentiment scoring can misread sarcasm, slang, or mixed opinions, and a client report built on bad labels is worse than no report.
Where the money could come from
The builder shares two ideas. Treat them as plans, not proven results; they did not report any client revenue.
1. Focused reports for agencies and brands
One idea is to offer a focused report to an agency or brand for a few hundred euros. Focused is the key word. Instead of competing with ongoing monitoring platforms, the report answers one question, such as how people reacted to a campaign or a public controversy.
2. Free samples as an outreach hook
The other idea is to send a small sample analysis when reaching out, so there is something relevant to talk about. A cold message that opens with a few real findings about the prospect’s own topic is far easier to answer than a generic service pitch.
3. A variation to consider
This one is our suggestion, not the builder’s. Once you have run a few one-off reports, a recurring version for the same client, such as a short monthly summary on a topic they track, can turn single projects into steadier work. Validate demand with one-off reports first.
The honest bottleneck: finding clients
The builder is candid: finding clients is a whole other problem. The tools and workflow exist, but the sales side is still open.
That is the right thing to plan for. Technical skill gets you a good report; it does not get you a buyer. Before building more automation, it is worth spending time on who needs these reports most often. Agencies running social campaigns, PR teams handling a sensitive topic, and brands launching something new are reasonable places to start, but you will need to test which group responds.
Risk check before you sell this service
This checklist is our own framework for anyone offering data-based reports to clients.
- Platform terms. Read the terms of each platform and the scraper listing, and collect only public data.
- Privacy. Report on themes and trends rather than individual commenters, and avoid storing personal details you don’t need.
- Accuracy. Spot-check automated sentiment and theme labels by hand, as the builder does.
- Cost control. Pay-per-use pricing is cheap for small runs, but set limits before scraping large volumes.
- Scope creep. Define the question, the date range, and the platforms in writing before you start.
Results will depend on your analysis skills, your niche, and how consistently you reach out to prospects.
How to do it
- [ ] Pick one niche where public Instagram or Facebook reactions matter, such as local brands or campaign agencies.
- [ ] Open the Apify listings for the Instagram and Facebook scrapers and check current per-use pricing.
- [ ] Run a small test scrape on one public topic to see the data format.
- [ ] Build a simple n8n or Python workflow that groups comments by sentiment and recurring theme.
- [ ] Review the output by hand and write a one-page sample report.
- [ ] Send that sample, tailored to their topic, to a short list of agencies or brands.
- [ ] Offer a focused paid report scoped to one question and one date range.
- [ ] Track which prospects reply so you learn who actually buys this work.
Want to test a social listening service this week?
Choose one public topic your ideal client cares about and run a small scrape on it today. Turn the results into a one-page sample with the top three recurring themes. That sample becomes your first outreach message.
Source: I work in social intelligence and started building my own scraping tools
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