Posted by David Mihm
In its recent report on "Yelp's Rocky Relationship with Small Businesses," PBS Media Shift was the latest mainstream media outlet to cover one of the most controversial topics in all of local search: search engines' filtering of customer reviews.
The topic first came to prominence four years ago in Kathleen Richards' landmark piece on Yelp's aggressive sales pitches — or extortion, depending on your perspective and whom you believe. While I was never fully convinced of corporate misbehavior on Yelp's part, the company hasn't done itself any favors by continuing to allow its field operatives to use deceptive sales tactics. Despite its best efforts to educate both business owners and everyday users of the site, the poor reputation of Yelp's salespeople continues to contribute to confusion around review filtering among the small business community. I hope to be able to clear up some of that confusion with this post and offer a few tactical tips to help avoid the frustration these filters can cause.
As local search usage among the general public has exploded over the last several years, more and more directories have (rightly) seen reviews as a way to:
In many ways, Yelp was ahead of its time on all four of these bullet points, and as a result, it had to tackle the inevitable review spam that accompanied its popularity.
Its answer was arguably the first widespread local review filter: an algorithm for detecting and removing spam or suspicious-looking content. In Yelp's own words:
For those of you who couldn't quite keep up with Yelp's version of Micro Machines man, the primary reasons are:
Yelp's CEO, Jeremy Stoppelman, recently gave his own slower version of this rationale in a company-produced video:
While I don't have any detailed knowledge of Yelp's review filter specifically, many comparable filters seem to kick into action if any of the following is present in the content of the review:
Another criterion that also tends to trigger filtering is a sudden burst of reviews preceded by or followed by a long lull between them.
Some of the more sophisticated review filters, including Yelp's, take a look at user characteristics, too, including:
The algorithms behind review filters are far from perfect, as many readers probably know, and Yelp is far from the only local search engine with a review filter. In fact, Google+ has probably accrued more ire from business owners as a result of its filter in 2012 and 2013 than any other site.
Unfortunately, these filters frequently:
All of which leads to frustration from the standpoint of a small business owner.
Yelp is probably the most aggressive of its peers at enforcing its business review guidelines, which also happen to be the most onerous guidelines of any local search engine. Yelp's filtering is so aggressive that one in five reviews written on Yelp never shows up on the site!
To sum up those guidelines:
O ye business owner who disobeys those guidelines, beware! You run the risk of a public shaming.
Although Yelp's guidelines are considerably more onerous than its peers', Google+ is not far behind in stringency. However, many local search engines are far less prickly about soliciting reviews from customers, or even incentivizing them, and some (including Google) have even engaged in this behavior themselves.
For those who have been caught in the Google+ review filter, Mike Blumenthal has covered your travails par excellence and has authored a most reasonable response. Miriam Ellis and Joy Hawkins have also given excellent advice on this front.
Here are direct links to those guidelines at a few of the biggest players:
The primary methods of these filters, though, I think will change pretty dramatically. Rather than judging a review by its content or looking at website behavior (e.g. how many reviews a user has left for other businesses), the explosion in smartphone adoption is enabling a couple of far less easily-manipulated criteria to judge the veracity of a review.
And even for those platforms without the handset or payment-processing advantage, requiring location-awareness for users of mobile applications prior to leaving a review seems like a no-brainer (which Yelp has already implemented and Google may be well on its way to doing).
For those sites that are more desktop-dependent, widespread adoption of primary social logins (Google+, Facebook, Twitter, etc.) could lead to a baked-in layer of spam-fighting.
As Eric Schmidt recently said:
“Within search results, information tied to verified online profiles will be ranked higher than content without such verification, which will result in most users naturally clicking on the top (verified) results. The true cost of remaining anonymous, then, might be irrelevance.”
In some industries (e.g., DUI law, plastic surgery, psychology), anonymity may be a pre-requisite for any user reviews and these local search platforms may need a Plan B. But for most industries, requiring some sort of verified social profile would solve a lot of problems.
Facebook, of course, has a huge leg up on everyone else based on its knowledge of a user's social connections. Google+, meanwhile, could look at a user's activity across Google's entire range of products (web search, Gmail, YouTube, etc.) to stop spammers in their tracks.
While consumer privacy concerns around these mechanisms for review filtering may arise, many business owners would likely rejoice at a truer, less bug-ridden filtering algorithm and a more accurate and complete representation of their customers' experience.
Well, that's enough out of me for this week! How about you? What are some of your strategies for avoiding these dreaded review filters? What other methods of filtering do you see coming to Local Search?
Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don’t have time to hunt down but want to read!
Comments are closed.