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Post No.: 0697reviews


Furrywisepuppy says:


Honest reviewers behave altruistically because they voluntarily spend a little of their own furry time to pass benefits onto others because they inform others and keep retailers and manufacturers themselves honest – which helps every potential customer, including those who don’t ever leave reviews.


However, dishonest reviewers do the opposite. Fake or paid-for (whether with cash, a free product or any other incentive) reviews muddy the pool of information that genuine customers reply upon to make well-informed purchasing decisions.


And it’s not just fake positive or 5-star reviews for one’s own products – some firms pay people to give fake negative reviews for competitors’ products. People tend to give far more attention to, and more weight to, negative comments than positive comments, hence every single fake 1-star review takes a lot of 4 or 5-star reviews to perceptually balance out. This is why sellers might try to persuade or pressure buyers into removing or not publicly posting their negative reviews.


Well because fraud is a game of fraudsters using tactics, authorities using counter-tactics, fraudsters avoiding or exploiting these counter-tactics, etc. – businesses might even flood tons of positive reviews onto a competitor’s product so that it’ll trigger suspicions according to a selling platform’s algorithms, which may then lead to a temporary suspension of that competitor’s account or products.


Retailers may specifically solicit reviews from those who are most likely to give a positive review, or they might offer something like a discount for a future purchase if customers give a positive review. If a manufacturer controls the platform where the reviews are held, like on their own e-commerce website – genuine negative reviews may be blocked or the reviews may be presented in misleading ways. (It’s strange that we sometimes accept it as ‘being shrewd’ when businesses twist market research feedback, testimonials or statistics to give a misleading picture in their marketing, when it’s called propaganda when governments do the same!)


If you must give or do something, like give a 5-star review, in order to receive a ‘free’ gift then it’s not technically a free gift. In this case it’s essentially a bribe – an incentive to act dishonestly.


Even if there’s no obligation to return a favour – if one receives a free sample to review, one will still be unconsciously nudged to give a positive review out of the power of reciprocation. It’s more difficult, almost tasteless, to diss something we had gotten for free and were not entitled to – it’s not impossible but it takes a lot of reminding ourselves to give an honest review. Even so, we’ll likely still be relatively more lenient and forgiving e.g. we’ll be more disappointed rather than fuming barking about a faulty feature of a product we didn’t pay for compared to if we did pay for it with our own hard-earned cash.


Receiving surprise valuable freebies put us in a happier mood too, and our mood always affects our judgements. It’s like if you’re not in the mood for something you normally like (say perhaps eating jerky treats or catching flying discs) then you probably won’t like it as much at the time i.e. it’s not just the thing or event we’re judging that shapes our feelings towards it but also our current frame of mind, which can depend on other things that are happening in our lives, our current hormone levels, our expectations, our current level of expertise or experience, and other internal and external factors, including our present company, what our peers think about that something, environmental primes or anchors – or indeed whether we received something to review for free. Yet when we give our verdicts, we tend to neglect to mention ‘I have given this product this particular score according to my mood at this time’ – under the assumption that we’re always objective and impartial judges.


One might also or alternatively be consciously calculating in the hope that giving a positive review will mean receiving further free product samples from that manufacturer in the future, or from other manufacturers who might notice one’s reputation for giving positive reviews. (Some people who give products a rating, and usually a high rating, even admit in their reviews that they’ve not yet tried what they’ve just purchased and reviewed, which suggests some hidden motive for doing so!) Social media influencers, in particular, want to be the type of people that companies think ‘they’re most likely going to give any product we give them a glowing review thus we’ll consider sponsoring them (again) in the future’. They might even (contractually need to) totally follow the script that a manufacturer gives them to tell. A manufacturer will conversely likely hesitate to sponsor or give another free product to a person who previously gave them a review they didn’t like. Celebrities, influencers or anyone else who gets paid to endorse a product or brand are obviously going to be biased to give positive endorsements, for the sake of their current and potential future contracts.


So manufacturers specifically identify who are most likely to give their products a rapturous review based on how they’ve reviewed similar products in the past, and will only give free products or free download codes to those particular reviewers or influencers – which results in a selection bias. This is still the case when influencers are provided with freebies for the purpose of posting an ‘impartial’ review.


So if someone is reviewing a product – check if they unambiguously declare whether it was purchased independently or supplied for free or at a discount from the manufacturer? (This is actually a legal requirement in at least some countries, although it’s not always obeyed.) Do they also get to keep the product or must they return it after the review? (Although even if they do need to return it – because getting stuff for free, even for a short while, is nice, and because it helps give them content to write up about or post on their social media channels – the reviewer will still likely, consciously or unconsciously, be biased to give a better review than they would if they had independently bought that item.) Is the product or service from a company that’s affiliated (or some other relationship) with the media outlet it’s being advertised on? And do they make this relationship clear? These kinds of questions help gauge the potential impartiality of an author or media outlet.


On Amazon, merged product pages and hijacking old reviews for different products can lead to reviews appearing for products that are completely different – like 5-star reviews for plush toys appearing on a product page for a pair of headphones. This means we must carefully go through each review rather than simply rely on the overall star rating.


Prospective buyers of products don’t just look at the reviews but sales rankings too. The lazy mental decision shortcut here is the belief that a product/seller couldn’t be that popular if it wasn’t/they weren’t that good/trustworthy. So many people cannot all be mugs, can they? Yes they can because fraudsters often attempt to manipulate sales figures too. Popularity is routinely overstated or artificially boosted through fraud.


‘Brushing’ is the technique of generating fake orders or sending unsolicited cheap products (or sometimes even empty parcels) to customers to artificially boost a seller’s sales figures. Stolen personal data could be used to send those goods to someone innocent and unsuspecting, but the fraudsters actually hold and control these customers’ accounts and then publish partial reviews under them. These reviews will therefore appear as ‘verified purchases’.


And it’s not right when genuine businesses that don’t use fraudulent methods to attract custom risk losing business to those who do. The danger is that it could then descend into a situation where these businesses follow suit and give a sort of similar excuse as people who dope in sports give for why they dope – ‘because everyone’s doing it’. This is why e-commerce services need to get on top of all types of fraud conducted on their platforms.


Since fake reviewers might be using stolen identities – watch out for cloned websites that may steal your sensitive payment data, by checking the web addresses you click on carefully. Watch out for cloned social media accounts too. If you are a seller then conduct a regular search of your own hashtags and reverse image search your own images to see if they’re being used elsewhere. It often takes alert and benevolent citizens and journalists to report fraud found on e-commerce and social media platforms to reveal it, and for those platforms to finally deal with it – suggesting that their own algorithms are fallible and leaves us to wonder how much falsehood there is out there that could easily catch out the innocent? Like regarding search engine optimisation for webpages, the algorithms employed can be deliberately gamed too.


Paying citizens to complete online surveys for scientific research is risky too because this may result in sampling biases where any findings speak more about the particular demographic of people who are more likely to be directed to these surveys and then are more likely to spend time on these surveys for a few bob, than about the overall population in general.


Honest and impartial reviewers and survey respondents are important. Likewise, savvy customers who look for bargains all of the time help reduce the prices of products where there’s healthy competition for custom – which benefits every customer once again, including those who cannot be bothered to shop around themselves.


However, different types of shoppers can be segregated and targeted separately hence retailers can extract what they can from the savvy shoppers and what they can (which will be more) from less-savvy shoppers e.g. through different ranges such as ‘basic’, ‘standard’ and ‘premium’ brand products. Retailers can do this more easily online by collecting individual data about us and our browsing and purchasing habits, then targeting specific adverts at us depending on which group their algorithms place us in e.g. as price-conscious or non-price-conscious consumers.


There needs to be enough savvy customers anyway, and they need to have a way of spreading their influence to have an effect. It’s like – since incredibly few people in the market ever bother to read though and scrutinise, or can understand all the legalese written in, long terms and conditions before agreeing to the use of some service – essentially no one is keeping these corporations and their terms and conditions under check so that we’re not all being taken advantage of. Or who, as a customer, even bothers testing, or can feasibly test without specialist equipment, whether their honey has been diluted with cheaper sugar syrup, or processed beef has been substituted with horsemeat, or not? (Other commonly adulterated products include olive oil diluted with cheaper oils, river cobbler sold as cod, turkey used instead of pork when something is labelled as ham, coffee, herbs like oregano, harmful additives in baby milk formula, and less-fresh tuna masquerading as more-fresh tuna through the use of artificial colouring. It’s not just something that happens in the black market!) In these kinds of cases where consumers find it difficult or impractical to help themselves – dedicated independent watchdogs or regulators help protect the interests of consumers. Woof!


Online e-commerce and review services are constantly trying to tackle the problem of fake reviews, fake sales figures and fraud in general, but the fraudsters will always try to stay one step ahead with their tricks. These services can sometimes get it wrong too e.g. genuine reviews can be flagged as fake by other users on some platforms, where they’ll then be at least temporarily hidden, which might be the plan of some fraudster. It again shows how fraudsters can sometimes exploit anti-fraud measures themselves. It also means that customers will need to (continue to) be savvy and read more than just the overall star ratings, popularity ratings, or the first and last reviews in a list.




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