What We Can Learn From the Fake Restaurant Fiasco on TripAdvisor
Hotels and restaurants live and die by reviews. And for the longest time, rankings on sites like TripAdvisor have been used as a leading indicator for popularity and satisfaction. But the algorithm used by those sites presents a problem; it takes only a handful of recent, 5-star reviews to boost the ranking of your venue. A reporter from VICE actually pulled this off last month when he successfully created a fake restaurant and made it the top-rated eatery in London. Can you believe that? He gamed the system in one of the best restaurant cities in the world — with a completely made-up business.
So what does this mean for restaurants and hotels? Reviews will, of course, continue to act as a signal for consumers. But hospitality businesses should start looking at other signals to truly understand the popularity of their location and satisfaction of their guests. Consider the impetus for a review: A customer either had a really good experience or a really bad one, and they want to tell other people about it. So the vast majority of your reviews are likely very positive, while a subset of them will be quite negative. It’s very polarizing. Plus, something like one out of every 2,000 hotel guests leaves a review, so you’re not working with a representative sample size.
What we’ve started to notice, however, is a macro trend of location-specific social content — what we call “geosocial data.” As social networks have gone mobile, more and more people are sharing their experiences with the context of location. This produces orders of magnitude more content than reviews (I’ve read that one out of ten people post publicly while traveling), generating a democratic ranking system that can’t easily be gamed. Sure, influencers may post a positive story about a hotel after getting a free room or vice versa, but there’s so much organic content on social media that it’s so incredibly difficult for one single person (or a few bad apples) to get away with affecting a hotel’s or restaurant’s ranking in a meaningful way.
Geosocial signals are a way for us to look at an unfiltered dataset of real experiences, and it acts as a powerful tool for businesses with locations.
Geosocial data allows us to look at a massive number of signals from real people, on location, sharing their experiences publicly for all the world to see. That’s so much more authentic than looking at a few reviews people have left for a property. These posts also guide our experiences as consumers. I may look at TripAdvisor to find a place to eat, but before making a reservation, I’ll look at the restaurant’s Instagram geotag feed to see what happens when other people go there. It’s a way for us to look at an unfiltered dataset of real experiences, and it acts as a powerful tool for businesses with locations.
For example, hotels use RevPAR (revenue per available room) as an apples-to-apples comparison of revenue generation across the industry. But what about experience? With geosocial data, we can normalize the volume of social posts generated from a venue by its capacity, creating an apples-to-apples comparison of experience across all hotels (which is what we did with our Geosocial Index). In this way, geosocial data unlocks the “experience” equivalent of RevPAR — and we gave it a name: LovePAR ?.
And this is just the start. HYP3R is building the world’s first-ever geosocial CRM of high-value consumers across the globe so that hotels, restaurants, gyms, airlines and countless other business with foot traffic can create meaningful customer experiences, convert unknown consumers and, ultimately increase revenue.
Hotels like Marriott, Hard Rock and Westin are using geosocial data right now to analyze guest and competitive behavior on location, engage guests on-property in delightful ways, and acquire high-value guests and loyalty members. Click here to learn more.