Restaurant review

The Hidden Gem in Restaurant Reviews Data

Owners and managers may intuitively know everything their customers think about food and service, but review data makes it definitive.

Most restaurants see online reviews as stars or star ratings. This is literally only the visible part of the reviews universe. There is so much more there.

The power of review data to help owners create a better customer experience is virtually endless. All it takes is a little analysis. For example, a famous and iconic East Coast seafood restaurant was plagued with more negative reviews than it should have received. Looking at the negative review data, three simple things that were driving down scores stood out:

Whenever “clams” were mentioned (24 times over the time period analyzed), these reviews averaged 2.33 stars. Interestingly, every time “oysters” was mentioned (20 times), those reviews averaged 3.9 stars. The restaurant started suggesting oysters instead of clams, and the negative clam reviews were drastically reduced as the restaurant worked hard to find better clams.

“Bread” was mentioned in 16 reviews with an average of 2.38 stars. In each case, the reviewer complained about the lack of bread being served. The restaurant served free bread on every table, but they saw that it created a lot of waste – people didn’t actually eat the bread. So they stopped serving it automatically. But clearly, customers wanted the bread on the table and thought the restaurant was skimping by not serving it. As a compromise, the restaurant started asking servers to ask customers if they wanted bread. This eliminated almost all of those bad reviews going forward.

“Wait” was mentioned 14 times, and those reviews averaged 1.4 stars (people said they waited up to 1.5 hours for their food to arrive). Of course the restaurant knew there were delays in service but weren’t exactly aware of the damage it was creating.

Owners and managers may intuitively know everything their customers think about the food and service, but review data makes it definitive; where you don’t have to think about it, you can see it.

Weeding out bad reviews knowing the data is valuable not only helps you improve the customer experience, but also boosts your rating on review sites. For example, if a restaurant gets an average of 3.74 in its ratings, it is displayed as 3.5 stars. To have a rating displayed as four stars, they only need an average of 3.75, or 1/100th star change. To get this advantage, it is often enough to make a few adjustments, like what was mentioned above.

Most importantly, restaurants do not react based on individual reviews. Bringing in just one important review could be rogue and taking action because of it could cause more problems than it solves. You should definitely pay attention to this, but make changes based on the review data aggregate. One of our customers in Chicago, known for his pasta dishes, received an incendiary review about the salty taste of his bolognese sauce. The guest said that no Italian should ever have to suffer from this sauce and subsequent water consumption. But we let the client know that in the last six months his Bolognese had a Net Promoter Score of 89.

The Net Promoter Score is a measure of customer satisfaction that represents the percentage of promoters (5 star reviews) minus the percentage of detractors (1, 2 and 3 star reviews). A 4-star review is neutral and does not affect the rating. Scores range from -100 (all negative reviews) to +100 (all positive reviews). Any NPS score above 0 is considered “good”, above 50 is considered “excellent”, and above 70 is considered “world class”. In this case, there were 41 positive bolognese mentions and only five negative comments. Nothing needed to be “fixed” with the Bolognese.

Do you believe in yourself or your chef more than in your guests? Read James Surowiecki’s seminal book The Wisdom of Crowds, Why the Many are Smarter Than The Few. There he proves that large groups of people are smarter than an elite when it comes to solving problems, finding solutions, and predicting the future. When you trust the data, attach a sentiment score to every keyword you care about in your reviews, you can start gathering amazing insights and start seeing it, too.

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