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Fake Reviews have become the scourge on the internet. As many as 90% are declared ‘unreliable using the same text, hyperbole or suspiciously positive words’.

An article on Channel Seven News on 25 April 2019 about Fake reviews prompted us to investigate further.

Channel 7 News Seven says it is easy to buy fake reviews – good or bad to affect your, or other brand’s products.

The ACCC found that online reviews are incredibly powerful with 80% of readers using them to decide on major purchases. It claims at least 15% of all online reviews are fabrications.

But website Fakespot is about to challenge Fake reviews.

At present, it analyses only Amazon products, Yelp listings, App Store apps and TripAdvisor listings. It has analysed 1,417,263,672 reviews to date.

Fake reviews

We used the Arlo Go LTE to see the results. We are not picking on Arlo per se – it is just that so many so-called reviews use the same words and terms.

Fake reviews
Fake reviews

Fake reviews are everywhere

There is a huge industry in places like India and the Philippines where English is usually the first language.

There are comprehensive Reddit Boards and YouTube tutorials that teach people how to write fake reviews.

Thousands of workers submit fake reviews to Facebook, Fakebook, Google, Amazon and anywhere else they can find an audience. Payment is a few dollars (big money to them). The aim – to either boost ratings of product X or take down a competitor’s ratings.

Boosting means a plethora of reviews suddenly appear (as evidenced by a timeline). Taking down a competitor takes longer – a concerted attack over many months.

Wikihow offers a guide to spotting fake Amazon reviews – the problem is that it is not all that easy.

Many major brands encourage Fake reviews

Whether it is the brand itself or its social media agency, this is happening.

Again, we hesitate to mention good names but Sonos One, a new Alexa speaker, launched tomorrow in Australia, has had an avalanche of reviews building its rating from zero to four out of five stars.

ReviewMeta warns that ‘Our algorithm has detected a large number of suspicious reviews.”