There are five ways to get Google reviews into a spreadsheet, and only one of them gives you every review, with the real date on each, on a listing you don't have to own.

Google Takeout is free and it works, as long as you own the listing. Takeout exports as JSON and there's no CSV option, and it writes a separate reviews.json for every location, so a twelve-location business gets twelve files to merge. Takeout carries no review photos either.

Scrapers and free Chrome extensions produce a spreadsheet in minutes, on any listing, and they lose the dates. Google publishes "3 months ago" instead of a date, so every review in that bucket arrives stamped with the same value. That file can't be sorted by date or charted over time, which is usually the reason people wanted it.

Building it yourself runs into two hard limits. Google's Places API returns a maximum of 5 reviews per listing. The Business Profile API returns all of them, but only for profiles you already own, and Google takes up to 14 days to approve your access.

Reviewflowz exports any Google listing to CSV with the exact date on every review, including listings you don't own and never get access to. You filter on screen first, so the file arrives already narrowed, with every location in it and eighteen columns to choose from. Plans start at $45 per location per month, and a free trial exports 10-row samples.

Each of these fails at something different, and usually at something you don't notice until the file is already open. Here's what you get from each one.

Two rows decide this for most people: exact review dates, and listings you don't own. Until recently you had to pick one. Scrapers read any listing on Google Maps and lose the dates, because Google publishes "3 months ago" instead of a date. Google's own API keeps the dates and refuses any listing you're not an owner of. So you could have coverage or you could have data, and not both.

You filter your reviews on screen, pick your columns, and the file lands in your inbox as a CSV. It opens in Excel and Google Sheets and handles every language, Mandarin, Cyrillic, Greek, Arabic. This section is about Google, and the same export covers every platform you connect, so the steps are the same whether you're exporting Tripadvisor reviews or reviews from any other review site.

A Google listing gives you eighteen columns. You pick which ones you want and what order they come in, and the export only ever offers columns Google actually fills for that platform. That's why you won't see a Pros column or a Cons column on a Google export. Google doesn't have them, so we don't ship you an empty column.

Photos come out as links, one per photo, in a single cell. Videos don't, so if you're after video attached to a review, this file won't carry it.

If you use custom dimensions, each one becomes its own column too.

The export carries whatever filters you've got on screen. So you don't dump everything and clean it up afterwards, you narrow it down first and the file arrives already narrow.

The filters worth knowing about for Google:

When you start an export, you can select what columns you want to export, and order them as you need them. Your data is yours.

One export covers every listing on your account. You don't run one export per location and stitch them together in a pivot table afterwards, and you don't lose track of which row came from where, because the Review profile, Location and Product name columns all tell you.

If you want one location instead, filter to it and export that. The point is that it's your choice rather than a limit.

Say you run three restaurants and you want to know which branch gets complaints about waiting times, and which servers get named in the good reviews. On a scraped file you'd read 900 rows and tag them by hand. Here you set up a tag for waiting times, and it runs across every review you've ever had, not just the new ones. Then you let the AI read your past reviews for your team's names and nicknames, so a review that says "Marco was great" gets attributed to Marco.

Then you export. The Tags column and the Team members column are already filled in, and you can pivot on them the moment the file opens.

One thing worth knowing: the export only writes attributions that are confirmed. An AI suggestion nobody has validated yet doesn't reach the spreadsheet, so you're not exporting guesses.

You can export a listing you have no access to. A competitor, a prospect, a client who hasn't shared access with you, a business you're doing diligence on. You don't need to be an owner, you don't need a Google Business Profile connection, and you don't need to ask anyone.

You still get exact dates on it.

Exporting is on the paid plans, and the price is per location per month. There's one rate up to three locations and a lower one from four to ten. Above ten locations it's quoted rather than listed.

Takeout is Google's own data export, and it does include the reviews on a Business Profile you own. It's free, and it's the right answer if you own the listing and you want one file once.

The nesting matters if you have more than one listing. You get a folder per account, a folder per location inside it, and a separate reviews.json inside each one. So a business with twelve locations gets twelve files in twelve folders, and merging them into one sheet is on you. You'll also get a folder for every account you're attached to, including ones with no locations and no reviews in them at all.

Takeout gives you JSON, and only JSON. There's no CSV option and no Excel option, so what lands is a nested file that a spreadsheet can't open in any useful shape.

One review comes out like this.

Every one of those has to be flattened, renamed and converted before you have a row. Do it for one review and it's ten minutes of fiddling. Do it for 900 and you need a script, which is the thing you were trying to avoid. Most "JSON to CSV" converters online won't do it either, because they flatten the nesting into a mess of columns rather than the five you wanted.

Three more limits worth knowing before you spend an afternoon on it. Takeout only covers listings you own, so it's no help for a competitor or a client who hasn't given you access. It carries no review photos, because a review in that file has no photo field at all, and the images in the archive are your own business photos rather than anything a customer attached. And business owners do report incomplete review exports on Google's own support forum, so check the count in the file against the count on your listing before you trust it.

Takeout holds both, and it's easy to export the wrong one.

The reviews customers left on your business sit under Business Profile. The reviews you wrote about other businesses, as a person on Google Maps, sit under Maps. If you're building a report about your own business you want the first one. If you want a copy of your own review history, you want the second.

Scrapers are the fastest way to a file. You paste a Google Maps link, you wait, and a CSV comes out. They work on any listing, yours or not, which is genuinely useful and it's the reason people keep reaching for them.

Then you open the file and look at the date column.

Google doesn't publish a date on a review. It publishes an age, so "3 days ago", "3 weeks ago", "3 months ago", and it recomputes that phrase every time the page loads. A scraper copies down what it can see, so every review in that bucket arrives stamped with the same value. You can't sort by date, you can't chart a trend, and you can't tell whether your rating is improving or getting worse. If you're exporting reviews to analyse them, that's the whole job gone. We wrote up how to get the exact date for a Google review separately, because it comes up constantly.

The other thing to watch is how much you actually get. A scraper reads the reviews Google renders on the page, so on a listing with thousands of reviews you tend to get the first few hundred and a file that looks complete.

You can build this, but it costs more than it looks.

Google has two APIs and neither one does what you want:

Building your own scraping setup skips the approval and hands you the scrapers' problem instead, so now you're paying for proxies and maintaining parsers to produce a file with the wrong dates in it.