Analysis of Trustfeed.com
Update: Trustfeed is now listed on OTCmarket (OTC:HEME)
There are good reviews and bad reviews. It is not possible to tell whether a glowing review
was written by the business owner, its employee or a paid reviewer.
A study of fraud found that up to 16% of Yelp review were suspicious. Some Amazon categories had up to 64% of fake reviews.
- The importance of positive and legitimate reviews can be leveraged by a company
during lead acquisition. According to an article by Hubspot 92% of consumers are
more likely to purchase a product online after reading a positive review about it.
- Behind many review-system failures lies a common assumption: that building these
systems represents a technological challenge rather than a managerial one. Business
leaders often invest heavily in the technology behind a system but fail to actively
manage the content, leading to common problems.
- The implications of poor design choices can be severe: It’s hard to imagine that
travelers would trust Airbnb without a way for hosts to establish a reputation (which
leans heavily on reviews), or that shoppers could navigate Amazon as seamlessly
Initially when review platforms start out they are faced with the challenge of getting
reviews, as for Trustfeed we will not be faced with this problem to such an extreme level as
we are acting as a marketplace scraping real time data from all review websites and
comparing them on ours.
Selection bias can become even more pronounced when businesses nudge only happy
customers to leave a review. This is when the majority of customer reviews are
positive, therefore making it difficult to distinguish between good and bad reviews.
eBay encountered the challenge of selection bias in 2011, when it noticed that its
sellers’ scores were suspiciously high: Most sellers on the site had over 99% positive
At trustfeed we intend to utilize the latest modern day technology such as machine learning
and artificial intelligence to create an algorithm using laws such as Bayes theorem to enable
our system to tell the difference between a fake review and a real review.
Additionally we may implement for all users to confirm their identity before making
an account using a third party confirmation software.
High growth and recurring SaaS revenues and freemium service
Trustfeed will introduce a flexible, modular subscription model where businesses can use
Trustfeed’s basic services for free and will be able to subscribe for additional services on
In order to establish real time data from a variety of websites Trustfeed will need to
purchase a variety of static proxy services to obtain the real time data.
Amazon Customer reviews
Amazon has been recently subject to fraudulent reviews via their third party sellers. In a
recent breach discovered by Safety detectives cybersecurity team they discovered
13,124,962 of these records that have been exposed. Totalling up to 7GB worth of data.
According to a recent transparency report published by Trustpilot It says of the 39 million
written reviews posted to its platform in 2020:
• 2.2 million were removed for being fake or harmful, representing 5.7% of the total
• 1.5 million were automatically deleted by its fraud detection software
• just under 660,000 were taken down manually
• businesses reported about 469,000 suspicious reviews, of which 62% were taken
• consumers reported nearly 90,000 suspicious reviews, of which 12% were removed
In their most recent transparency report published by Search Engine Land just over 2% of
reviews reported were faked. This equates to around 1.4 million reviews.
Total Addressable Market (“TAM”). The global TAM (excluding China) is
estimated by OC&C Strategy Consultants LLP (“OC&C”) to be approximately US$50 billion.
According to an eMarketer.com report in May 2019, retail ecommerce was approximately
14.1 per cent of all global retail spending, or US$3.5 trillion, in 2019 and is forecast to
amount to approximately 22.0 per cent. of all global retail spending, or US$6.5 trillion, by
Trustworthy systems can give consumers the confidence they need to buy a relatively
unknown product, whether a new book or dinner at a local restaurant.