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Fining customers for negative Yelp reviews? Welcome to the future of big data

Lisa Schmeiser | Aug. 8, 2014
The Union Street Guest House made news this week with its purportedly tongue-in-cheek policy of fining a wedding party $500 for each negative online review left by their wedding guests. The "We were joking!" defense defuses the original story. However, it doesn't neutralize the very real prospect of businesses trying to strike back against negative reviews by hitting customers right where it hurts--the wallet.

The Union Street Guest House made news this week with its purportedly tongue-in-cheek policy of fining a wedding party $500 for each negative online review left by their wedding guests. The "We were joking!" defense defuses the original story. However, it doesn't neutralize the very real prospect of businesses trying to strike back against negative reviews by hitting customers right where it hurts — the wallet.

How, you ask, is that possible? Blame — or thank — the thoroughly modern combination of big data, startups and a cashless economy.

Consider the following scenario: You're out with friends at a new-to-you restaurant. You checked in on Foursquare's new Swarm app and tweeted the check-in. The food was okay, the service was iffy. When the check comes, you opt to pay with a credit card, and there's a line of fine print on the bill saying that by paying with credit card, you are agreeing to abide by the restaurant's terms and conditions, which are available on its website. You swipe, you're on your way, and later, you leave a two-star review on Yelp.

When you get your credit card statement two weeks later, you find that the restaurant charged you an additional $500 two days later. A phone call to your credit card company informs you that the charge is billed as a "terms of service fee." That's when you visit the restaurant's website and learn that under the terms of service, if you leave a review they don't like, they can ding you $500. And how did the restaurant find you? By hiring a big-data startup to cross-reference the restaurant's credit card records against high-traffic social media networks and consumer feedback websites.

Terms of Disservice

This may sound far-fetched, but in a digital world that already supports a multimillion-dollar "reputation management" sector — one where firms work hard to divert or delete their clients' online footprints, and where tactics have already rendered up to 20 percent of Yelp reviews as planted fakes — a next step is to combine two common digital-native behaviors and use them to benefit businesses. Common behavior number one: Not reading through a business's lengthy legal terms of agreement before clicking "I agree" or completing a transaction that comes with the disclaimer "By doing this, you consent to our terms and conditions." Common behavior number two: Leaving real-world footprints, like physical locations, evening activities, and meals out, all over the Internet. People generate a lot of publicly available data, free for the grabbing. Combine that digital trail with the hastily approved consent linked to a financial transaction, and it's a recipe for an enterprising startup. After all, what is big data but an umbrella term for framing specific queries, then sifting through vast pools of disparate datasets until an answer pops up?

 

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