The Influence of Rating Scales
In 2017, a content creator called Oobah Butler decided that he wanted to do something with the experience he’d gained writing fake positive restaurant reviews on TripAdvisor.
What if, he wondered, he set up an entirely fictitious restaurant based in the shed in his garden and then started to manipulate TripAdvisor ratings?
What happened surpassed his wildest expectations. In just six months The Shed at Dulwich became the top-rated restaurant in London, even though nobody had ever actually eaten there, based solely on fake reviews, fake pictures and the word of mouth created by a complete inability for anybody to book a table.
It’s a tale that tells us an awful lot about the way we live now. Not least, the way in which we rely on rating systems and the Internet to tell us what we should think and do.
We routinely check TripAdvisor for our meals and hotel stays, IMDb to tell us which movies to watch and even crave the dopamine kick we get when somebody likes something we share on social media.
According to a report from online marketing firm Podium, reviews impact purchasing decisions for 93 percent of buyers, 82 percent of people now read reviews before making purchase decisions, 60 percent look at reviews on a weekly basis and if the reviews make them confident in a product or service then 68 percent of them are then willing to pay up to 15 percent more than a standard price.
This is just one part of a wider issue rooted in the increasing convergence of the digital and physical world and its ability to generate a huge amount of useful information. This process is so pervasive and based on so many data points, that it has even generated its own terminology and a number of new jobs and disciplines. Data Scientist has now been identified as the ‘best job in America’ for three years running.
Its creeping definition now incorporates a wide range of fields such as business analytics, the application of data, and good old-fashioned statistics.
In a workplace context it can range from the sort of Big Data organisations generate through the use of building sensors through to HR Analytics and the use of ratings in the supply chain.
This kind of information is obviously extremely valuable for a business. But its usefulness will depend on context and objectives. There is also a temptation to complicate issues that may be best judged with a simple binary decision between two possible outcomes.
We also have unprecedented access to the experience of our peers. Most of us commonly experience this in our day to day lives when making decisions about products and services but it’s a commonplace practice in B2B purchasing decisions too.
Google, Trustpilot, Feefo and Bazaarvoice are all commonly used B2B review sites, although Google claims an extra degree of impartiality because it does not make money directly from its reviews. Glassdoor is also important to prospective customers because they will often make a judgement about the way a firm treats its employees as a guide to its general approach to business.
Concluding, although there is a call for restrictions in the ability to create false ratings and manipulation of ratings, we must remember to never take the individual out of decision making and goal setting and remain focused on people, with all their unquantifiable preferences and behaviours.