Free tool

Free Review Sentiment Analysis Tool

Paste your reviews or survey responses — one per line — and AI classifies each as positive, neutral, or negative, surfaces the recurring themes, and tells you the one thing to act on. Free, no signup.

Reviews being sorted into a positive, neutral, and negative sentiment bar

The tool

What is sentiment analysis of reviews?

Sentiment analysis reads a piece of text — a review, a survey answer, a comment — and determines the feeling behind it: positive, negative, neutral, or mixed. Done across a batch of feedback, it turns a pile of individual opinions into a measurable picture: what share of customers are happy, what share are frustrated, and crucially, what specific things keep coming up on each side.

The reason it matters is volume. Reading ten reviews is easy; reading two hundred and keeping an accurate mental tally is not — and human readers reliably overweight the most recent or most dramatic comment. An analyzer counts every response equally, which is how you notice that "slow service" appears in a third of your negative feedback while the one furious review you can't stop thinking about is actually an outlier.

This tool runs that analysis on whatever you paste: Google reviews, survey responses, feedback form submissions, support comments. Each line is classified individually, the totals are aggregated into a breakdown, and the recurring themes are pulled out on both the positive and negative side — with one concrete suggested action at the end.

Quick start

How to analyze your reviews' sentiment

  1. 01

    Collect your feedback

    Copy reviews from your Google Business Profile, survey responses from your last send, or feedback form submissions — anywhere customers wrote to you in their own words.

  2. 02

    Paste one response per line

    Up to 20 at a time. Keep each response on its own line so the analyzer classifies them individually.

  3. 03

    Read the breakdown

    You get a positive/neutral/negative split, each response tagged with its sentiment and a short reason, and the recurring themes on both sides.

  4. 04

    Act on the one thing

    The analysis ends with a single suggested action based on your negative themes — because the point of sentiment analysis isn't the chart, it's the fix.

Reading results

How to actually use a sentiment breakdown

Trend beats snapshot

One batch tells you where you stand today. Running the same analysis monthly tells you whether the fixes you made actually moved anything — the number that matters is the direction.

Themes beat scores

A 70% positive rate is nice to know; "the negative 30% is almost entirely about wait times" is something you can fix on Monday. Always read the themes before the percentages.

Neutral is information

A pile of neutral responses usually means the experience was forgettable or the question was vague — both worth knowing. Don't ignore the middle of the distribution.

Small samples lie

Three reviews can swing wildly. Treat batches under ten as anecdotes, not data — and collect more feedback before drawing conclusions.

Beyond the batch

From one-off analysis to always-on sentiment tracking

A manual batch like this is perfect for a monthly check or a one-time audit. The limitation is that it's a snapshot you have to remember to take — and the feedback keeps arriving whether you paste it anywhere or not.

That's the job FeedbackRobot automates: every review and survey response you receive is analyzed the moment it arrives, themes are tracked over time instead of per-batch, and negative sentiment triggers an actual workflow — an alert, a ticket, an owner — instead of a chart entry. Our guide to automated sentiment analysis covers how that works in practice, and the review sentiment automation deploys it in minutes.

Frequently asked questions

Is this sentiment analysis tool really free?

Yes — paste up to 20 reviews or survey responses per batch, as many batches as you like, no signup and no credit card. It's a genuinely useful free tool; the paid product is for when you want the same analysis running automatically on every piece of feedback you receive.

What kind of text can I analyze?

Anything customers wrote in their own words: Google, Yelp, or TripAdvisor reviews, survey responses, feedback form submissions, support ticket comments, social media mentions. Paste each one on its own line and it's classified individually.

How accurate is AI sentiment analysis?

Modern language models handle the hard cases traditional keyword tools failed on — sarcasm, mixed feedback ("great food, terrible parking"), and context ("cold beer" is good, "cold food" is not). No automated analysis is perfect, which is why each classification comes with a short reason so you can sanity-check any tag that looks off.

What's the difference between sentiment analysis and a star rating?

A star rating is the customer's own one-number summary; sentiment analysis reads what they actually wrote. The text routinely contains signal the stars miss — a 4-star review whose text describes a serious problem, or specific praise worth repeating in your marketing. Analyzing both gives you the full picture.

Can I analyze survey responses, not just reviews?

Yes — open-ended survey answers are ideal input. Sentiment analysis is exactly how you make hundreds of free-text responses readable: classify each one, then read the themes instead of every individual answer.

How do I run sentiment analysis automatically on all my reviews?

That's FeedbackRobot's core job: it connects to your review platforms and surveys, analyzes every response as it arrives, tracks themes over time, and routes negative feedback to your team for resolution. The free analyzer here is the manual version of that pipeline.

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