The filtering of customer reviews by search engines has always been a topic of heated arguments. Reviews help search engines judge the offline reputation of a business, help viewers get important information before visiting that business, and also help build trust and rankings with major search engines such as Google.
In order to ensure that reviews posted were genuine and actually written by people that were not hired by businesses or to ensure that unscrupulous businesses did not post glowing reviews about themselves sites such as Yelp began filtering customer reviews. They created an algorithm that filtered customer reviews based on parameters such as abusive language used in a review, keyword stuffing, including links in reviews, and a sudden bout of reviews that appear before or after a long period of inactivity.
In addition, Yelp also looked at review frequency by a user, total amount of reviews posted by a user, rating distribution of each user, and the IP address or addresses of a user that posted reviews on their site. This filtering system could actually benefit users that posted reviews at regular intervals rather than those that posted reviews for the first time or after a period of inactivity.
There are several search engines including Yelp and Google that employ similar review filters for local search. However, as most business owners and users have realized, these filters are not perfect and often end up flagging genuine reviews while allowing spammy ones to pass through. New users may fear posting reviews since these may have a high chance of being filtered.
At the end of the day, a small business that could receive many glowing reviews might just end up with a few or with none, depending on the aggressiveness of the review filter. If you have faced similar problems in the past or wish to avoid seeing genuine reviews get sidetracked by major search engines then the best strategy is to first understand review filter guidelines posted by those engines at their website.
All search engines such as Google, Yelp, Yahoo, Citysearch, etc., provide guidelines and have a FAQ section that should enable you to understand their filtering methods to an extent. However, in the future, most search engines will themselves need to review their filtering methods since looking at the number of reviews posted by a user or looking at lull periods between reviews does not seem to be an accurate method of filtering reviews.
The increase in smartphone usage to surf, shop, and post reviews too will need to be considered as more people now use the internet on the go. Search engines may in the future tie review filters with specific device IDs to ensure that the review is posted by an actual person. In addition, some sites may also insist on a user having completed a transaction before he or she is allowed to post reviews. Search engines may also accept reviews of users with a presence on social media, especially for users posting reviews through desktops, as a further measure to filter reviews effectively.
While some search engines may still need to allow anonymous reviews, most may demand some sort of identification and verification in the future to ensure posting of reviews by genuine reviewers. Some search engines such as Google may well track a user’s movements across their services such as Gmail, YouTube, etc., before displaying reviews of such users.
While there may be concerns raised on privacy issues, most businesses may well be happy with the thought that only genuine reviews and reviewers would be able to get past improved review filters for local search in the future.