Reviews and endorsements are great tools to help you make informed purchases, except when they’re not. Here are a few tips to keep in mind that will help you separate real reviews from fake news.
Reviews are everywhere – Amazon product reviews, Yelp restaurant reviews, Glassdoor company reviews. At their best, they provide valuable insight and information that can help you make an informed decision. At their worst, they can be misleading tools that suck you into a morass of bad choices. The problem stems largely from the open and anonymous nature of a review. When you are allowed to use a pseudonym, or even no name at all, we know nothing about the validity of the review. Even if you use a real name and are a real person, we know nothing about your motivation. And that means we don’t know whether to pay attention to your review or not. Unfortunately, there is no magic answer that fits all cases, but there are a few things to watch out for. Here are four things to consider when reading any review.
1: Strip off the outliers. First of all, does it seem reasonable? Looking at a company review that simply gushes on and on about all the pros of the company, gives it a 5, and lists “none” for cons. Or the more engaging (and my favorite) response for cons “I honestly can’t think of any”. Why does someone take the time to go on a site like Glassdoor and write a review that makes it seem like the company is heaven on earth? Sure, people will vent if they are upset, but sadly, few people wake up in the morning and think, “Ohmigosh, I’m so happy with my job, I think I’ll go write a fabulous review of it”. That’s a big red flag right there. Is it a real review, or did someone in HR write that?
Conversely, a review of 1 with nothing nice to say and paragraphs about what a horrible place/product can be either a competitor (who will refuse to say anything nice) or a disgruntled employee. Disgruntled employees, especially if there are a lot of them, are worth noting but one or two people in any crowd are always going to be ticked off about something. As with super-good reviews, take super-bad ones with a grain of salt. Someone who has only good things to day or only bad things to say looks suspicious. Nothing is all good or all bad (except me, of course – I’m fabulous).
I generally drop the top 10% and bottom 10% of reviews just to remove outliers in either direction. And while we are talking about numbers, the spread is the most important thing. Assuming, of course, that you have enough reviews to make up a meaningful sample. A product/service/company with only a few reviews is too easy to manipulate and you should use any of them warily. If there are enough, then look at the distribution. Are most of the reviews 4s or 5s? That’s good. 1s and 2s? Stay away. Even if 20% of the reviews are 4 or 5, if the other 80% are 1 and 2 that can indicate very real problems.
2: How does it read? The next flag is to look at the language used. This applies to products, companies, and pretty much everything. Does the review talk about a “superior feature set”, or “solving their customer’s mission-critical enterprise challenges”? This is also either coming from HR or Marketing, or else someone who seriously drank the Kool-Aid. If the words sound like they came right out of a company or product brochure, they probably did.
3: Is it relevant? Another type of review to toss is the confused reviewer. “The product worked great but UPS driver left it by the garage instead of the front door – one star”. Or the always popular “The iPhone 5 case didn’t fit my iPhone 7 – one star”. Don’t laugh – I’ve seen sillier ones. If the substance of the comment is about something that is actually unrelated to the proper use of the product/service.
4: Are the dates suspicious? One last thing to look for is the date that the reviews were submitted. If there is a cluster of similar reviews around one week or month, it could just be a push from the company to get their users to write reviews. Or it could be a push from the HR/Marketing department to submit a series of fake reviews. If there is a cluster of negative reviews it could be a drive from a competitor to downgrade the reviews, or it could be the result of a big layoff or other negative company event. But again, clusters of reviews are worth looking at in more detail. Normal reviews come in a steady stream, not all at once.