Objection.co’s Sparky bot/service finds reasons why bad reviews should be taken down
The LA-based startup says this is the first automated service to help find violations of Terms of Service in the content of negative online reviews.
Online reviews can make or break small companies, which is why their marketers often look out for such feedback.
This week, LA-based startup Objection.co is out with a chatbot and service that helps pinpoint the reasons that Yelp, Google+ and Facebook might take down a bad review.
CEO Curtis Boyd told me that, to his knowledge, this is the only automated bot/service that gives reasons a bad review might violate Yelp’s or others’ Terms of Service (TOS), which are the only reasons the reviews will be taken down.
He added that TOS violations generally include offensive language, bigotry or hearsay reviews, such as posting that you heard your brother saying this restaurant wasn’t good.
A posting that is obviously promotional for a competing service can also be a violation, such as “Harry’s Restaurant has the same dinner special but at half the price.” But Sparky doesn’t flag the review if Harry’s Restaurant is simply mentioned, without comparison.
The bot, Sparky, is available on Slack or Facebook Messenger or through the Messenger plug-in on Objection.co’s website. A marketer can cut and paste a bad review into the bot and get back reasons why it appears to violate TOS, at no charge. But it’s up to the marketer to approach the review platform. Here’s a sample screen shot from Sparky in use on the Objection.co site:
(Click to enlarge)
Objection.co also offers a paid service, where the marketer provides the URL of the review page, and Sparky will automatically email perceived TOS violations for any review of three stars or less. Then, as an additional paid service, Objection.co can approach the review platform on behalf of the business for any of those reviews, or the business can do it.
Boyd said that Sparky has been programmed to recognize specific TOS violations and is refining its perception through machine learning. In bot or service form, Sparky can recognize about 80 percent of TOS violations, he said, adding that as many as half of bad reviews for a given business might violate TOS.
As for the success rate in getting a review removed, Boyd said it depended on how obvious the violation was and couldn’t be predicted.
Among competitors, Boyd said BirdEye and Reputation.com offer a similar service, but it’s largely manual. He noted that Grade.us, ReviewUs and ReviewTrackers encourage users to post reviews and share good ones, and they notify businesses of bad reviews, but they don’t give specific suggestions about how to remove them.
About The Author
Barry Levine covers marketing technology for Third Door Media. Previously, he covered this space as a Senior Writer for VentureBeat, and he has written about these and other tech subjects for such publications as CMSWire and NewsFactor. He founded and led the web site/unit at PBS station Thirteen/WNET; worked as an online Senior Producer/writer for Viacom; created a successful interactive game, PLAY IT BY EAR: The First CD Game; founded and led an independent film showcase, CENTER SCREEN, based at Harvard and M.I.T.; and served over five years as a consultant to the M.I.T. Media Lab. You can find him at LinkedIn, and on Twitter at xBarryLevine.
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