That's Why We Rejected 23% of the Reviews at OMR Reviews

User reviews are crucial for the business model at OMR Reviews. As a platform for software and tools, we rely on users reporting on the use of programs and their own experiences.

However, not every comment lands on our website unfiltered. That would be quite unprofessional and no longer objective. But which reviews are rejected by our team and why? Questions upon questions. Now our colleague Christin gives the answers to create more transparency on our platform.

Why are most reviews rejected?

Over the past few years, about 23% of all individual reviews have been rejected. Nevertheless, more than 50,000 reviews are now online. The basic rule is: If Christin has doubts about the neutrality or truth of a critique, of a user or the data given, the user will be contacted by mail. There are very few cases where we do not offer the opportunity for subsequent correction.

Depending on how much you want to narrow it down, there are four common and four rare reasons why we reject reviews:

The top reason: Doubts about actual use

By far the most common reason for rejecting reviews is serious doubt that the user has actually used the tool. Many indications such as incorrect factual information, confusions or a wrong statement of the professional position suggest this case of "Fake Tool Use". Screenshots to Christin can minimize skepticism at this point.

Reason #2: Comments not helpful enough

Each review should be helpful for our target group. To this end, at least one question with at least three bullet points or sentences must be answered. If a comment does not add value, it is considered too content-free.

Third most common reason: Fraud or lack of authenticity

The third reason for rejection is the most obvious: the person commenting either does not exist at all or copies identical texts from other review portals. Disposable email addresses or duplicate persons also fall into this fraud category. So if Christin can't quite believe that this person exists, she also doubts the authenticity of the review.

Reason #4: Texts written by artificial intelligence

Another common proof of an invalid review has only been relevant for some time: texts that are obviously written by artificial intelligence do not show any personal (human) experience values and are too generically formulated. Such texts include those from ChatGPT or machine-translated copies from other languages.

Are there any other occasions to sort out reviews?

Apart from these four common reasons, our colleague Christin notes four other (rare) justifications for an invalid review.

Person data is incomplete or incorrect

Anyone who writes a review must provide name, company email and occupation. If these data are incomplete or incorrect, the review can no longer be credible. A quick research on LinkedIn and the like or proof that the data given are really correct often helps here.

Lack of neutrality due to bias

Imagine you work for a digital company that has its own tool on the market. Can you then still give a neutral and unhindered honest review? Most likely you have to or want to write a somewhat embellished "self-review" due to bias or fear of consequences. This is not entirely neutral and helpful.

Review was copied or used more than once

Of course, the criticism must be tailored to the respective tool. It is not permitted to send the same text for several programs. Otherwise, the info is – exactly – not useful enough. Similarly unhelpful are discriminatory or insulting reviews. That's self-explanatory.

Private use of the tools

Since OMR Reviews is a B2B platform, we reject reviews from private use. Tools are to be evaluated from a company and business perspective. This is important because expectations of certain programs may be satisfactory for individuals, but not really good for multiple users.

Pay attention to these points so that your review goes online

These are eight reasons why we sort out a review. Christin checks all reviews for their truth content and their neutrality, even the anonymized ones. And a subsequent change is also checked again. She goes to all this trouble just to make the content as helpful and objective as possible.

Thanks to Christin, OMR Reviews offers over 50,000 valid and helpful reviews on online tools. To get your review approved by her, pay close attention to these things and you really don't have to worry about a rejection:

• Provide your real personal data.
• Don't review a tool that you work on yourself or for which you work yourself.
• Only review tools that you actually use professionally or have used.
• Write a factual and meaningful text (suitable for the software) without the help of AI and with the necessary three bullet points.
• Don't copy your own or someone else's review from OMR Reviews or another review platform.

Now tell us directly which tool makes your work easier and write a review.