There are numerous variables that influence our purchasing choices.
Many of them are related to physical proximity and placement: on which shelf the various items are displayed, which are easiest to see and reach, which are placed at the end of aisles and which are tucked amongst many identical-seeming options, mid-aisle, what their packaging looks like, the colors utilized, the texture of the packaging.
But some are related to a more fundamental perception of quality, and our sense of quality can be distorted by an array of categorization-related variables.
Although reviews can sometimes help us figure out whether a particular product is right for our use-case, they're often also utilized to justify decisions we've already made.
We figure out which product we want, and then we check the reviews to find supporting evidence for that choice. So while it may seem like we use reviews as an initial indicator of quality, we sometimes think that’s what we’re doing, but we’re actually using them as a source of downstream confirmation.
Rankings, on the other hand, often serve as an upstream influence.
In this context, upstream means a lens that shapes our perception of something early in the process of perceiving it, while downstream means we're being influenced later, after already having been pre-influenced by those upstream variables.
Some of these rankings are human-made: curated Top Mops lists that tell us which mop is the best mop, based on a website operator's preferences and priorities.
Some are completely data-driven, as is the case with many online sales platforms which auto-generate top-seller lists based on previous sales.
Others, though, are tweaked by software, but otherwise crowdsourced. And the most common ranking system of this kind wasn't invented by Amazon, but was definitely mainstreamed by it, at least in the context of selling products via online sales channels.
The five-star review system is manipulatable, flawed, and often biased toward one- and five-star reviews because most of us are only willing to take the time to click those stars when our experience with a product is very good or very bad.
Even savvy shoppers who are aware of these flaws, though, tend to subconsciously take these rankings into consideration, using them to inform later, conscious decisions.
We look at two near-identical mops, one that has 4.5 stars and another that has 3.7, and we then hunt for more information, subconsciously giving more weight to the positive data we collect about the mop with 4.5 stars, while taking more seriously the negative feedback about the 3.7 star mop.
The cognitive processes at play here seem to be related to our penchant for avoiding decision fatigue, our desire to sort and categorize, and the satisfaction we tend to derive from ranking things, possibly in order to bring a sense of legibility to an otherwise scattered-seeming space.
If I know little about mops, feeling like I've gleaned an understanding of which are the good mops and which are the bad mops brings a sort of order to my cognitive universe.
And this is especially important when it comes to products about which I know little: if I’m a mop expert, I’ll probably be less inclined to care about how many stars the mops I’m considering received, because I have a bundle of other pre-vetted datapoints I’m using to judge and rank these products.
When I know little about a particular product category, on the other hand, I’ll mentally scramble for anything I can find that seems to bring order and coherence to an otherwise meaningless jumble of options.
Whatever data I use during this upstream, pre-sorting period, can then go on to inform other decisions I make in the future, influencing my perception of mops, brooms, dust bins, brands that make such products, and even people who possess products made by various brands.
Even when aware of the many flaws in our ranking systems, then, we can fall prey to the latent desire to create hierarchies, which can at times be a useful tendency, but in other cases can be a vulnerability by which we're manipulated, resulting in seeming understandings about the world and the relative quality of things that are, unfortunately, based on little actual, meaningful data, leading to flawed perceptions and less-than-ideal decisions.
Brain Lenses is an Understandary project.
You can find the Brain Lenses podcast at brainlenses.com or wherever you get your podcasts.