If you’ve ever tried to get all your customer reviews in one place—across Amazon, Google, Yelp, and wherever else people are talking about you—you know what a mess it can be. Copy-pasting is a non-starter. Manual exports? Good luck keeping up. This guide is for folks who just want a straight answer: How do I actually collect and analyze reviews from multiple platforms without losing my sanity? If you’ve heard that Apify might help, you’re in the right place. Here’s how to use it, what to watch out for, and how not to overcomplicate things.
Why bother with multi-platform review collection?
A single angry customer on Yelp can torpedo your local business. A glowing Reddit thread can spike sales overnight. The point: Reviews are scattered, and the truth about your product or service is rarely tied to just one platform.
But here’s the rub: - Every platform has its own format, quirks, and (often) hidden export buttons. - They don’t want you automating this, for the most part. - Manual copy-paste doesn’t scale and gets old fast.
That’s where web scraping comes in. And that’s what Apify is built for.
What is Apify, really?
Let’s cut through the marketing. Apify is a cloud platform that helps you run web scrapers (they call them “actors”). You can use their prebuilt scrapers, tweak them, or roll your own. The upside? You don’t have to set up your own servers or fight with headless Chrome every time a website changes.
But: It’s not magic. If a site is hellbent on blocking scrapers, you’ll need patience (and sometimes, just plain luck). Also, scraping can get fiddly—expect some maintenance as platforms change layouts.
Step 1: Pick your platforms (and know the rules)
First, decide which review sites matter for you. Common choices: - Amazon: For product reviews. (Scraping Amazon is a cat-and-mouse game. Be prepared for blocks.) - Google Maps/Google Business: For local business reviews. - Yelp: Same as above, but more U.S.-centric. - TripAdvisor: Hotels, attractions, restaurants. - Trustpilot, G2, Capterra: For SaaS, software, and B2B. - Reddit, forums, niche sites: Sometimes where your fans (or haters) actually hang out.
Pro tip: Double-check the terms of service. Some sites explicitly forbid scraping. Many companies ignore this in practice, but know your risk tolerance.
Step 2: Set up your Apify account
- Head to Apify and sign up. The free tier is fine for most experiments.
- Get used to the dashboard. You’ll spend time here running “actors” (scrapers) and checking results.
- Grab your API token if you want to automate things later.
That’s about it. No credit card? No problem—just note that heavy usage or premium actors will need payment info eventually.
Step 3: Find or build the right scraper (“actor”)
Here’s where Apify shines. You don’t have to reinvent the wheel.
Using Apify Store
- Go to the “Actors” or “Store” section.
- Search for your platform, e.g., “Amazon Reviews,” “Google Maps Scraper,” or “Yelp Reviews.”
- Read the docs. Some actors are well-maintained, others are abandoned. Look for:
- Recent updates
- Number of users/runs
- Clear documentation
- Support for extracting reviews, not just basic info
What works: Most big platforms have at least one decent scraper in the Apify Store.
What doesn’t: Niche sites, custom login flows, sites with aggressive anti-bot measures. For those, you might need to tweak an open-source actor or build your own.
Building your own (if you must)
If there’s no actor for your target platform, you can: - Fork an existing open-source actor and adjust the selectors. - Use Apify’s SDK (in Node.js or Python) to write a custom scraper. This isn’t trivial, but it’s well-documented. - For browser automation, Playwright or Puppeteer are your friends.
Reality check: Unless you’re scraping a weird or tiny site, start with the Store. Building from scratch is last-resort territory.
Step 4: Configure and run your scraper
Each actor will have its own input. Usually, you’ll need: - The business/product URL or search term - Number of reviews to fetch (be realistic—thousands at once might get you blocked) - Optional filters (e.g., date ranges, ratings)
Tips for smoother runs: - Start with a small batch. Make sure the output is what you expect. - Use proxies if you’re scraping platforms like Amazon or Yelp. Apify provides proxy options, but they cost extra. - Schedule runs (daily, weekly) if you want to keep your data fresh.
What to ignore: Don’t worry about scraping every review ever written. Focus on what’s recent and relevant.
Step 5: Export and organize your reviews
Once your actor finishes, Apify will give you options to download the data: - CSV: Best for Excel, Google Sheets, or basic analysis. - JSON: Flexible, especially if you’re piping into a database or script. - API: For full automation, grab your results via API.
Pro tip: Standardize your fields across platforms. Every site calls things something different (“reviewer,” “user,” “author”), so pick your own columns and stick with them.
Step 6: Analyze (but don’t overthink it)
You’ve got the data—now what? Here’s what most people actually want to know: - What’s the average rating? - What do people complain about most? - Are there patterns by product, location, or date?
You don’t need fancy AI for this: - Excel/Google Sheets: Use filters, pivot tables, and basic text search. - For larger datasets: Python (with pandas) or R can help. - Tools like MonkeyLearn or even ChatGPT can pull out themes, but don’t trust them blindly.
Honest take: Sentiment analysis sounds cool, but in practice, keyword frequency (“slow shipping,” “friendly staff”) is usually more actionable.
What works, what doesn’t
Works well:
- Collecting reviews from most mainstream platforms (Google, Yelp, TripAdvisor, etc.)
- Setting up scheduled scrapes for ongoing monitoring
- Exporting to CSV/JSON for easy analysis
Struggles:
- Sites with heavy anti-bot protection (Amazon is notorious; you’ll get blocked if you’re too aggressive)
- Getting every single review—older reviews sometimes load dynamically or require endless scrolling
- Scraping platforms that require logins or CAPTCHAs (Reddit, some forums)
Ignore (for now):
- Trying to “analyze everything automatically” with AI. You’ll waste time tuning models for little gain.
- Overengineering dashboards before you even have clean data.
Keeping it simple: Maintenance & troubleshooting
- Actors break. Sites change layouts all the time. If your scraper stops working, check for updates or try another actor.
- Don’t hoard data. Keep what’s relevant and recent; archiving every review ever is usually pointless.
- Stay legal-ish. Scraping is a gray area. Don’t go nuts; if a site blocks you, take the hint.
- Start manual, automate later. Pull a month of reviews by hand before setting up daily scrapes.
Wrapping up: Start small, learn, iterate
You don’t need a PhD or a dev team to collect and analyze customer reviews from multiple platforms. Apify lowers the technical bar, but it’s not fire-and-forget. Pick your sites, grab a good scraper, get your data, and focus on what you actually want to know. Don’t aim for perfect—just keep it simple, and improve as you go. That’s how you actually get value from your reviews, instead of drowning in them.