Detecting and Reporting Fake Reviews: Protection Against Fraudulent Ratings
Fake reviews are fraudulent ratings (either purchased positive reviews for your own business or negative fake reviews from competitors) that violate Google guidelines as well as EU and Austrian competition law, and distort local rankings and customer trust.
Key Takeaways
- Typical fake patterns: new accounts without profile picture, only one review, generic text and review clusters on a single day
- In 2024, Google blocked or removed more than 240 million policy-violating reviews and uses AI systems for this purpose
- Reporting in Google Maps via the three dots and “Report review”, in the Business Profile via “Report”, each with a reason
- The EU Omnibus Directive and the Digital Services Act tighten platform obligations
- Businesses that post or commission fake reviews violate the UWG (injunctions, damages); for widespread cross-border violations, EU law sets a maximum fine of at least 4% of annual turnover
- In Austria, injunctive relief claims exist for defamatory false statements of fact; evidence preservation is the first step
- Best protection is an organic review profile: actively solicit genuine reviews, never buy them, respond to all
Fake reviews are a double problem for local businesses. They distort customer trust and influence local Google rankings. Those who can recognize fake reviews, report them correctly and assess them legally protect both reputation and visibility. This article shows the typical patterns, the concrete reporting process and the legal situation in Austria and the EU.
Why fake reviews are relevant for local businesses
Reviews are a central factor in purchasing decisions. According to a US study by BrightLocal, 75% of consumers always or regularly read online reviews, and Google remains the most-used platform with 81% for reading reviews (1,141 respondents). When these signals are manipulated, the decision-making basis for the entire industry suffers.
The problem is measurable and also present in Austria. In an Austrian survey, 19.8% of participants suspected that more than half of all online reviews are fake or purchased. This mistrust has direct consequences for business. According to the Austrian E-Commerce Trust Mark, every second person (51%) researches the provider and looks for customer reviews, and 61% abandon the purchase if an offer seems dubious.
At the supervisory level, the EU has also sharply addressed the issue. In a coordinated review of 223 large websites (published in January 2022), national consumer protection authorities, coordinated by the European Commission, concluded that at least 55% of the reviewed sites potentially violated EU law. For 144 of the 223 sites, the authorities could not confirm that the operators were doing enough to ensure that reviews are authentic.
How to recognize fake reviews: typical characteristics
Fake reviews often follow recognizable patterns. Individual anomalies are not proof, but the combination of multiple signals significantly increases the probability.
- Generic language: Interchangeable phrases without specific reference to the product, person or situation. Details that only genuine customers would know are missing.
- Review clusters on one day: Multiple similar reviews within a short time indicate a coordinated campaign, not organic feedback.
- Missing profile photos: New accounts without pictures, without further activity and with only a single review are a classic warning sign.
- Extreme star patterns: An accumulation of pure 1- or 5-star reviews without nuance appears unnatural, as genuine feedback is usually more differentiated.
- Mass reviews: Profiles that review dozens of businesses across different industries and regions in a short time are rarely authentic.
Checking fake Google reviews specifically
If suspicious, it's worth looking at the reviewer profile. Click on the name and check the review history. Four points are informative:
- Reviewer profile: How old is the account, is there a complete profile and real activity over a longer period?
- Review history: Does the profile review inconsistently, for example rating competing businesses positively and yours negatively?
- Location plausibility: Do the reviewed locations fit geographically, or does a profile review across multiple countries?
- Unrealistic review numbers: Hundreds of reviews in a few days or a sudden spike indicate manipulation.
Reporting fake reviews: step by step
The reporting process differs by platform but follows similar logic.
Google Business Profile and Google Maps. In Google Maps, click the three dots next to the review and select “Report review”. In your own Business Profile, open “Read reviews” and select “Report” next to the review. Choose the reason that fits, such as spam. Google then reviews the report. If it is rejected, you can file a one-time appeal in the Reviews Management Tool, ideally with additional justification and evidence.
Other platforms. On Trustpilot, Amazon or industry portals, there are comparable reporting functions directly on the review. Document each report with date, screenshot and justification so you have complete documentation for repeated or legally relevant cases.
Important: Factually negative but true reviews are protected by freedom of expression and will not be removed. A report is only promising if there is a genuine policy violation.
Legal situation in Austria and the EU
Fake reviews are not a trivial offense. The EU Omnibus Directive has tightened consumer protection. Since then, it has been an unfair commercial practice to submit fake reviews or commission others to do so, and to claim that reviews come from genuine customers without taking reasonable steps to verify their origin. In Austria, these bans are listed in the annex of the Federal Act against Unfair Competition (UWG) (items 23b and 23c). Businesses that provide access to consumer reviews must also explain whether and how they ensure that the reviews come from consumers who actually used or purchased the product. Leaving this information out can count as a misleading omission (Section 2(4) and (6b) UWG).
The sanctions are substantial. For widespread cross-border violations that national consumer protection authorities pursue in a coordinated EU action, the Omnibus Directive (EU) 2019/2161 requires the maximum fine to be at least 4% of the company's annual turnover in the member states concerned. The EU review from 2021/22 mentioned above shows how widespread the problem was even before the new rules took effect on May 28, 2022. Transparency was a core problem: 104 of the 223 websites did not explain how reviews are collected and processed, and only 84 provided this information on the review page itself.
The EU Digital Services Act (DSA) further tightens obligations by requiring platforms to implement reporting and transparency mechanisms.
Review fraud, sabotage and extortion
Fake reviews occur in several variants. Purchased positive reviews are intended to enhance one's own profile. Negative fake reviews by competitors aim to deliberately damage a business and downgrade it in local rankings. A particularly aggressive form is extortion: perpetrators threaten a flood of negative reviews unless money is paid. Such extortion attempts should be documented immediately and reported to both the platform and, if necessary, law enforcement authorities.
Impact on local SEO and local ranking
Reviews are a ranking signal in local search and the Map Pack. Manipulated reviews distort this signal in both directions. Purchased positive reviews can temporarily boost rankings but are exposed when discovered and cost trust as well as visibility. Negative fake reviews artificially depress the average rating and can reduce clicks and calls. In both cases, data quality suffers, which both Google and potential customers rely on.
How platforms combat fake reviews automatically
Detection is increasingly AI-supported and runs at large scale. According to its own statements, Google uses machine learning algorithms and a model trained with the help of Gemini that flags suspicious profile edits. In 2024, Google blocked or removed more than 240 million policy-violating reviews, the majority before they even became visible. Additionally, more than 12 million fake business profiles were removed or blocked and over 900,000 accounts were subject to posting restrictions. Amazon and Trustpilot also operate their own detection systems that analyze patterns, account behavior and networks.
Best practices: prevention for local businesses
The most effective protection is a healthy, organic review profile. Those who continuously collect genuine feedback make individual fake reviews relatively insignificant.
- Actively solicit genuine reviews: Ask satisfied customers promptly and personally for a review, for example via a short link after purchase or appointment.
- Never buy reviews: Purchased reviews violate policies and law and endanger the entire profile.
- Respond to all reviews: Professional, factual responses to both positive and negative feedback strengthen trust and signal engagement.
- Establish monitoring: Regularly observe the review profile to detect anomalies such as sudden clusters early.
- Response to fake reviews: Respond factually, report the violation and avoid public escalation.
Legal steps for affected parties
For defamatory fake reviews with false statements of fact, injunctive relief claims exist in Austria and Germany. The first step is evidence preservation: screenshots with date, URL and profile information, ideally documented in a court-proof manner. Subsequently, a legal warning with cease-and-desist demand can be issued. A lawyer specialized in media or competition law can directly request the platform to delete and initiate court proceedings if necessary. Important is the distinction between protected opinion and false statement of fact, as only the latter is legally actionable.
Tools, AI detectors and their limitations
There are tools and AI detectors that flag suspicious reviews based on language patterns, account data and timing. They provide initial indications and accelerate monitoring. However, their limitations are clear: they generate false alarms, do not reliably detect cleverly formulated fakes and cannot replace human review. Automated assessments should therefore serve as indicators, not proof. The final classification of whether a review is reported or legally pursued remains a manual, context-based decision.
Conclusion
Good review management combines three levels: continuously soliciting genuine reviews, systematic monitoring and a clear process for reporting and legal response. Those who establish this routine reduce the impact of individual fake reviews and strengthen both local ranking and customer trust in the long term.
Data & Statistics
More than 240 million reviews violating guidelines blocked or removed in 2024
Google (The Keyword / Google Maps Blog) (2024)More than 12 million fake business profiles removed or blocked, over 900,000 accounts with posting restrictions (2024)
Google (The Keyword / Google Maps Blog) (2024)At least 55% of 223 examined websites potentially violated EU law (EU sweep, published January 2022)
European Commission, Press Release IP/22/394 (2022)104 of 223 websites did not explain how reviews are collected and processed, only 84 did so on the review page itself
European Commission, Press Release IP/22/394 (2022)19.8% of respondents suspect that more than half of online reviews are fake or purchased
Statista / Marketagent (Austria survey) (2018)61% do not purchase when doubting the credibility, 51% research the provider and look for customer reviews
Austrian E-Commerce Trust Mark (meinungsraum.at) (2018)75% of consumers always or regularly read online reviews, Google is the most used platform with 81%
BrightLocal Local Consumer Review Survey 2024 (2024)EU Omnibus Directive: maximum fine of at least 4% of annual turnover for widespread cross-border violations
Directive (EU) 2019/2161 (Omnibus), EUR-Lex (2019)Opens the chat with a prepared prompt.
Frequently asked questions
How do I recognize if a Google review is fake?
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Are fake reviews illegal in Austria?
Can I take legal action against defamatory fake reviews?
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