How Hotels Create Real Relationships with Customers

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Our CEO and co-founder Jeff Catlin just posted a great essay over at about how sentiment analysis can help hotels and other guest-based services improve their customer experience.

He sums it up nicely, saying that learning how to “listen better” is both the key to success and frustratingly vague. As any of us know, we will often say one thing to our friends or on social media and something completely different when talking to a hotel clerk or server in a restaurant.

For example if while at a restaurant, your server is inattentive, flustered, and makes mistakes, any person (or semi-sentient android) would know to tell the server, “that’s okay.” Yet, if you end up chatting about your night on social media, you’ll tell your friends the service wasn’t that great. This is the kind of thing sentiment analysis can help businesses identify and correct.

But, as Jeff pointed out, just hearing what people are saying about your business isn’t enough. There are multiple layers of sentiment analysis, which can reveal more accurately what your customers are talking about. He says that a search for “bat” could return a negative result, but rather than the Dark Knight and his pals whooping it up in the halls, it’s really negative reviews of a nearby batting cage.

Sentiment analysis can also help the hospitality industry create real relationships with customers. Jeff writes about how a mostly positive review praised one hotel’s wifi service, but complained about the temperature in the room. He posits that with a quick fix of the AC on that floor and not a lot of money, the problem could be repaired. Sentiment analysis would also allow management to reply to the online review that tipped them off, likely ensuring that customer’s continued business.

You can check out Jeff’s post at to dig into the data and details about the benefits (and pitfalls) of text mining! It’s a great read, and we’re not just saying that because he’s the boss!

Categories: Customer Experience Management, Reputation Management, Sentiment Analysis, Social Media, Technology, Voice of Customer