Every review. With the owner's reply.
For each Google Maps listing, outsend extracts every published review (author, rating, date, text, attached photos) and explicitly flags reviews with no owner reply. Instant online reputation signal for your prospects, clients, or competitors.
You want to understand the voice of customers at a restaurant, a shop, a hotel — for competitive benchmarking, online reputation auditing, or sector research. Google Maps hosts thousands of public, dated, signed reviews, but offers no native export. Reading 200 reviews manually takes hours; turning them into analysable data takes a full day.
outsend's Google Maps review scraper extracts all this public data for the listings you provide — with one essential signal: the owner's reply is explicitly identified. You immediately see, per listing, the response rate, negative reviews left unanswered, and can cross-reference this with your sales or advisory strategy.
9 structured fields per review
For every review retrieved, here's what you'll find in your CSV — ready to use in Excel, Sheets, or your BI tool.
author_name
Name publicly displayed by the review author.
"Marc D."rating
Review rating out of 5 stars.
5publish_date
Relative and absolute publication date ("3 months ago" + 2026-02-12).
2026-02-12text
Full review content, untruncated.
"Flawless service…"photo_count
Number of photos attached by the author to their review.
3language
Detected language code of the review (fr, en, es, de…).
enowner_reply
Owner reply text if present. Empty otherwise.
"Thank you Marc…"days_without_reply
For unanswered reviews: number of days elapsed since publication.
47sentiment opt.
Derived sentiment score (positive/neutral/negative) if module enabled.
positive · 0.78An owner's silence is a signal
Most review scrapers give you raw text. outsend explicitly flags reviews without a reply and counts the days elapsed since publication. You get a directly actionable online reputation signal: "this business ignores its critics" or "this owner is engaged and looks after their customers."
Combined with cluster scoring (4★+ with reply, 2★- without reply), you turn raw reviews into a strategic indicator.
The scraper in 3 steps
You can scrape up to 100 listings in a single batch operation.
Identify the listing
Direct Google Maps URL, or name + geographic area (automatic lookup). You can pass a list of 100 listings as a batch, or chain directly from a previous Google Maps scrape.
Extract all reviews
From most recent to oldest, with no cap. For each review: author, rating, date, full text, attached photos if any, language, and the owner's reply if it exists.
Analyse or export
CSV / XLSX / JSON ready for Sheets, Excel, or your BI tool. Optional: automatic sentiment scoring (positive / neutral / negative) on each review for clustering.
Four typical user profiles
Restaurant owner benchmarking
Extract reviews from your 15 direct competitors to identify recurring complaints (wait times, cleanliness, quality) and find your differentiation angles backed by real market feedback.
E-reputation agency
Monitor customer voice across your 50 restaurant and retail clients, flagging negative reviews without a reply for rapid intervention. Weekly report with an open review counter.
Medical / healthcare practice
Analyse your own reviews to identify positive patterns (to highlight) and negative ones (to fix internally). Without paying a reputation platform $100/month.
Marketing student / researcher
Build a customer review dataset for your thesis or sector study, with sentiment analysis and cross-region benchmarking. Public source, no budget required.
Vs Outscraper, Trustfolio, manual scraping
| Capability | outsend | Outscraper | Trustfolio | Manual |
|---|---|---|---|---|
| All reviews (not just 10) | ✓ | ✓ | own reviews only | possible, slow |
| Owner reply explicitly flagged | ✓ | raw only | not the focus | visible |
| Days without reply | ✓ | needs coding | no | needs counting |
| Auto sentiment (option) | ✓ | paid add-on | ✓ | needs coding |
| Attached photos flagged | ✓ | ✓ | no | visible |
| Pipelinable with Maps scrape | ✓ native | via API | no | no |
| Entry price | Alpha €0 | ~$0.003/review | ~€100/mo | €0 (time cost) |
Compliance — public professional reviews
Google Maps reviews are voluntarily published by their authors on a public platform, in a professional context (rating a business or establishment). Extracting them falls under legitimate interest for web harvesting under GDPR. outsend collects no private data (email, personal phone number) — only what is publicly visible to any Google Maps visitor.
Analyse your reviews (or your competitors')
Every Google Maps review with the owner's reply explicitly flagged. Free alpha on application — no per-review cost like Outscraper.
Request free alpha access →Frequently asked questions
Can you scrape all reviews or only the first 10?
All of them. outsend scrolls through the complete review history of a listing, from newest to oldest, with no imposed cap. For very dense listings (restaurants with 2,000+ reviews), allow a few minutes for the scrape.
How does owner reply detection work?
Google Maps clearly marks owner replies with a specific label ("Owner's response") and distinct typography. outsend reads this marker, extracts the reply text and date, and calculates the delay relative to the original review's publication date.
How many listings can be processed in a batch?
Up to 100 listings in a single batch. Beyond that, it's better to chain multiple batches or use a pipeline that combines a Maps scrape → reviews automatically. No global cap on total reviews retrieved in alpha.
Is the sentiment option free?
Yes, in alpha. Sentiment scoring is computed by our internal model on each review's text and adds three columns: sentiment_label (positive / neutral / negative), sentiment_score (0–1), and sentiment_keywords (salient keywords).
What export formats are available?
CSV (configurable delimiter), XLSX (with separate sheets per listing in batch mode), JSON (nested structure: listing → reviews → reply). You choose at export time.
Does the scraper retrieve photos attached to reviews?
Not the image files directly (to keep bandwidth usage light), but their public URLs are returned in a dedicated column. You can download them in a second step if needed.
What about Google Maps ToS risk?
outsend reads public Google Maps pages as a browser would, without authentication or session cookies, at a respectful pace that avoids overloading their servers. The GDPR legitimate interest framework recognises the harvesting of public data under appropriate conditions — which applies to public professional reviews.