We use the following mechanisms to check incoming reviews:

Automatic or algorithm-based checking mechanisms:

Word filter: We use an automated word filter to prevent reviews containing terms from our word filter list from appearing on our website in the first place. In this way, we try to avoid the publication of offensive, racist or advertising reviews at an early stage.
Hazard warnings in the word filter: The word filter list also includes hazard terms such as "allergy" or "injury". These are mainly used to alert our team to potential sources of danger.
Data protection filter in the word filter: Incoming reviews are automatically scanned and filtered for data relevant to data protection that allows conclusions to be drawn about a person's identity (real names, telephone numbers, credit card numbers, etc.).
Automated checking of metadata: All incoming reviews are automatically checked by us for anomalies with regard to the respective metadata (e.g. IP address, device ID, date, e-mail address).
Self-learning review algorithm: Our automated review mechanisms are self-learning algorithms. This allows us to constantly check previously published reviews for discrepancies and carry out further manual checks if necessary.

As soon as a review contains anomalies based on our review mechanisms, a detailed manual review of the individual cases follows. All reviews filtered out or reported in this way are checked by our team against our review guidelines and also subjected to a general plausibility check.

For the plausibility check, we take into account the customer's entire review behaviour and also look at the content and metadata (e.g. IP address, device ID, date) of the review. In doing so, we check whether the purchase and evaluation of the product are in temporal and spatial relation to each other and whether there are any contradictions in terms of content. This allows us to investigate whether the customer has actually used the product.

Example: A customer leaves a review of the product the day before the goods are delivered or claims to have been using it for a month, even though the purchase was only a week ago.
Example: A DVD is rated with the sentence: "I don't like the colour and finish of the shoe".

The content of the reviews indicates that the review may not correspond to the product being reviewed. We then endeavour to contact the authors of such conspicuous reviews in order to be able to verify the statements in their review if necessary. If the circumstances are clarified, the rating will be adjusted accordingly. If the circumstances for the rating remain too vague and unclear, the corresponding rating is filtered out. It is no longer displayed or not published at all.

All ratings filtered out in this way are not included in the overall rating shown.

There is no stricter filtering of negative reviews or favouring of positive reviews. As long as a review fulfils the above criteria, it will be published on an equal footing regardless of whether it is formulated in a favourable, critical or even derogatory manner.

Valuation guideline:

We would be delighted if you would like to rate our products. To ensure that your review can be published, please observe the following guidelines when submitting your review:

The evaluation may of course contain your opinion and, if applicable, criticism. However, any form of discrimination and insults will not be tolerated.
It is not permitted to leave adverts for other products in reviews.
We do not allow reviews from so-called product testers. They must not have received any financial compensation from third parties for the review.
Reviews must be based on your experience with the product and must be truthful. Any form of untrue claims and attempts at manipulation will not be tolerated.
We reserve the right to temporarily or permanently block user accounts and the ratings they have submitted in the event of violations of our rating guidelines.

Source: Lawyer Putte

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