Key Takeaway
You can buy scraped Google review data, but the hard part is living with what you build on top of it. The scraper sells you a file once, while you own the lawsuit and the bad rating that follow.
This FAQ walks through the real questions founders ask before they ship an app powered by reviewed data. Read it before you wire money to a vendor.
Can I just buy the data and build the app?
Technically, yes. A vendor in Ukraine or anywhere else will happily sell you a dump of reviews tied to place IDs.
Legally, the vendor gets paid once, but you carry the exposure for as long as your app is live. It starts the moment you publish a rating derived from that data.
That scraper lawsuit win does not protect your app
You are thinking of the hiQ Labs case against LinkedIn. According to public reports, a court ruled that scraping public data does not break the federal hacking law.
That ruling is narrow. It said scraping public pages is not a criminal act under one specific statute.
It did not bless reselling the data. It did not touch copyright or database rights.
What does the vendor’s own terms clause actually mean?
That line about not using the data against Google’s business interest is a pass-through warning that shifts the risk to you.
If your app competes with Google Maps by showing a rival rating, you are squarely in that zone. According to Google’s published terms, copying review content to build a competing experience is forbidden.
The vendor knows this. That is why the clause exists.
Can I post filtered ratings as a product?
This is the most dangerous part of the idea. When you let users hide service reviews or filter to one group of customers, you publish a new factual claim and take ownership of it.
A restaurant with a genuine 4.6 can argue your filtered 3.1 is false and harms its business. That is a defamation and false advertising conversation and it is expensive.
What technical traps live inside review data?
Reviews are messy. The same person posts duplicates and bots flood new listings.
Two problems bite hardest. Fake reviews push scores up. Old reviews punish a kitchen that fixed its service two years ago.
You need a de-duplication step and a time-decay rule before any score is trustworthy. Without them your app ships noise with a star rating on it.
Reviewer identity adds another layer. A reviewer in Seoul sends a different signal than a local. Location is central to the filtered product, so you cannot skip it.
What does a cleaner model look like?
Build on data you are allowed to use. Two paths work better than a raw scraped dump.
First, license the official Places API. It costs money and caps what you can store, but the provenance is clean.
Second, collect your own first-party reviews inside the app. You own those outright.
If you do show outside ratings, link back to the source and label it clearly. Attribution reduces legal risk.
How do I judge a data vendor before paying?
Ask four questions. How was the data collected? How often is it refreshed? What happens when a target site changes its markup? Will they put an indemnity clause in the contract?
Most vendors answer the first two. Few answer the last one in writing.
An indemnity clause means the vendor covers your legal costs if the data turns out tainted. If they refuse to sign one, treat that as your answer.
What you should do before writing any code
Write down the exact claim your app will make. If it publishes a rating, name who owns that number and who defends it.
Get a short legal read before launch. Two hours with a lawyer who knows data law costs less than one cease-and-desist letter.
Then pick your data source to match the claim. Use the official API for public ratings and first-party reviews for your own score.
One thing decides this whole project. Can you defend every number you show? If you cannot, fix the data source before you ship.