BranchVoice
Demo

Fake Review Detector: Separate Reviews That Aren't Genuine

Shows how likely the review is not a genuine customer experience and the warning signals behind it. It tries not to flag short but sincere reviews.

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Examples

Result

The result will appear here.

Results are AI estimates and may contain errors. Your text is not stored; the result for the same text is cached briefly.

Labels

The model scores the probability of each label below for every text. You can extend the label set for your needs or use it with labels made entirely for you.

Promotional
Advertising, promo codes, links or self-promotion.
Off-topic
Content unrelated to a product, service or experience.
Bot-like
Template phrases and repetition; looks generated.
Competitor attack
Exaggerated attack without detail that pushes another brand.
Incentivised
A review written for payment, a gift or a discount.
Overly generic
So generic it could describe any business.

Where is it used?

Examples of how teams use this model in their daily work.

  • 01

    Platform disputes

    Flag unfair or fake-looking reviews with reasons and prepare removal requests for Google and marketplaces.

  • 02

    Clean analytics data

    Remove ads, spam and bot reviews from your reports and measure the real voice of the customer.

  • 03

    Detecting competitor attacks

    Notice waves of negative reviews with no concrete detail arriving in a short time.

  • 04

    Incentivised review checks

    Separate reviews written for a gift or discount to stay within platform rules.

Use this model in your own system

Change the labels, add new ones for your industry, or connect the model to your CRM, contact centre or e-commerce stack through our API. For API access and custom models, write to us at [email protected].

Write to us

Frequently asked questions

Is this tool free?
Yes. You can analyse a number of texts a day without signing in; heavy use gets a short cool-down.
Which languages does it support?
It understands multilingual text, Turkish and English first; results are shown in your interface language.
Is my text stored?
No. The text is only processed for the analysis; the result is cached briefly so repeated requests return quickly.
Can I analyse in bulk?
The BranchVoice platform collects your reviews from their sources automatically and classifies them with these models in bulk; request a demo to try it.

Other tools

All tools

Want to analyse thousands of reviews automatically?

BranchVoice collects reviews from Google Maps, complaint sites, social media, app stores and marketplaces every day, classifies them with these models and turns them into alerts, reports and dashboards.

Request a demo