Staying Ahead of Fake Product Reviews

In the competitive world of internet trade, not every merchant is fair. Some post fake positive reviews for their products to lure shoppers. Other people post bogus negative reviews of competitors’ products to dissuade potential customers.

Both are cases of product review fraud. It is unethical to rivals and, also, to shoppers who rely heavily on the reviews.

If a retailer doesn’t stop the fraud, shoppers could eliminate trust in the testimonials and stop purchasing from the website.

Product Review Fraud

There are various kinds of product review fraud. Below are a few common ones.

  • Individuals and small groups. This sort of fraud involves a couple of men and women who write fake reviews, either promoting their own products or criticizing competitors’. Because this is a small group, it is easier to recognize the patterns across different reviews and mark them as possible fakes. Retailers should block the fraudsters, after a first warning or with no warning.
  • Larger groups. This entails an organized group of people who write fake reviews, sometimes tens of thousands each day. For fake positive reviews, the groups are often paid a part of the increased earnings or with discounted or free products. The teams may also post countless bogus negative testimonials to reduce competitors’ sales. Coordinated fraud across bigger teams is tricky to catch as the routines are tough to trace. Additionally, the team can be comprised of revolving temporary employees with different writing styles. Sometimes the team is produced by merchants, who amuse clients to leave a positive review in exchange for a discounted or free item.
  • Automated robots. Dishonest merchants are proven to make bots that post reviews that were automated. The bots set up bogus consumer accounts and go through a list of goods to leave fake reviews. They can use review templates or a limited, predetermined language. Fraud from automated robots can cause much damage in a brief amount of time. But it’s generally easy to grab with the ideal technology, to identify patterns. The bot owner knows that its fake testimonials be detected quickly. Therefore the strategy is usually to gain from increased earnings for a couple of days prior to the fake reviews are eliminated and earnings return to normal.
  • False negative. Many sites enable users to label a review for a fake. This usually contributes to the inspection being taken offline before somebody can confirm its validity. The false negative fraud involves tagging competitions’ legitimate positive reviews as fakes to activate their removal. It usually takes some time for a competitor to confirm a branded review, which may reduce sales in the meantime. Merchants can gradually remove this sort of fraud, as once confirmed a review can’t be flagged as imitation.

Identify and Protect Against

Third-party providers can help identify fake product reviews. One such supplier is Fakespot, which can examine a product page and, based on routine analysis, determine possible fake reviews and the users that post them. These services aren’t foolproof. But they are a viable option, particularly for smaller merchants.

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Fakespot is a good example of a service that finds potential fake reviews.

A better choice is for the site owner to stop such testimonials by having a rigorous verification procedure. Reviews must only be published after they are assessed and approved. Again, pattern analysis software can frequently identify fake reviews. Blocking IP addresses of the writers of fake reviews may also help.

Graph data evaluation is another avoidance procedure. It can navigate the path by a review to its writer, to compare his review history and his writing style. In addition, it can detect multiple client accounts tied to one IP address.

Still, scammers always evolve. They develop new ways to game the system. Hence merchants should put money into prevention technology. The option is for shoppers to eliminate trust in the reviews or have awful shopping experiences. Both can lead them to leave and never return.

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