Use Artificial Intelligence to collect, respond to and analyze customer reviews of your restaurant

Collecting more customer reviews for your restaurant, and responding to them, play a decisive role in your e-reputation, your position in search results and customer loyalty. But are you then analyzing this feedback to improve your restaurant's performance and experience? A very difficult task, but we explain howArtificial Intelligence does it for you!

Artificial Intelligence plays a new role today in the management of your restaurant. Whether it's your inventory, your employees or your online communication: Artificial Intelligence will help you outperform.

Today, it's essential to collect more positive customer reviews. To reflect a positive image of your restaurant online, to build loyalty and convert new customers. Responding to all reviews, both positive and negative, shows your appreciation and satisfies the search engine algorithm. But that's not all. You need to go even further, and analyze the reviews left by your restaurant's customers. To improve your service, adapt your menu and keep only the bestsellers, adjust certain recipes...

Here's a step-by-step guide to generating and managing customer reviews for your restaurant. And how to put Artificial Intelligence to good use.

1. Why and how to get up to 10X more positive customer reviews for your restaurant

a. The importance of customer reviews for your restaurant's business

Your customer reviews play a decisive role in your reputation. But also your restaurant's SEO. They tell the public about your past experiences, both positive and negative, which has a major influence on the decision of potential customers. In fact, 90% of Internet users say they consult customer reviews. And 46% of them choose their restaurant on this basis. And the more (positive) reviews you have, the more customers are attracted to your restaurant. Your reviews therefore reflect the satisfaction and popularity of your restaurant, which is why it's so important to have them.

Google's algorithm also judges your establishment partly on the basis of customer reviews. Its aim: to provide the best possible result for Internet users. So the more reviews you have, and the more time you take to respond to each one, the more positive signals you send to Google. Considered a reliable restaurant, and one that cares about the customer experience, the algorithm takes this into account. It improves your position in the search results and reduces the weighting of bad ratings in your average for responding to them. Collecting as many customer reviews as possible plays an important role, but it's not about collecting negative reviews. Quite the opposite, in fact. 

→ To find out more about the importance of collecting customer reviews, head over to our article here! 

We hear it all too often: when they're dissatisfied, customers are more likely to leave a negative review than when they've enjoyed their experience. So what levers can be put in place to encourage satisfied customers to testify?

b. Start by training your team to use a strategic approach

Your front-of-house team plays an important role in the customer experience. Your employees are therefore in the best position to encourage customers to leave a review. But you need to find the right approach, without appearing pushy or opportunistic. Train your teams to know when customers seem satisfied, and then how to invite them live to leave a review in a subtle way.

A few sentences are all it takes to gently ask them to leave a review, and show them the procedure. 

c. Launch positive customer review campaigns

With reservation and delivery platforms, social media... Today, there are many ways to collect your customers' data. If you have their e-mail address or telephone number, you can send them a message directly. This gives you the opportunity to ask them about their feelings after their visit. 

Personalize your message (emailing or sms) to each customer after their visit, so that they really feel involved. This maximizes the chances of them leaving a review. It's a marketing action that takes time, and involves a risk: asking a customer who may have been dissatisfied with their experience to leave you a review.

What if you could send automated email campaigns that were still personalized to each customer, and that filtered out negative reviews so as not to publish them online? At Malou, we've created this unique feature, so you can collect more reviews with just one click! 

→ To find out more about positive review campaigns, visit our article HERE.

d. Make the process even easier with magic totems

Today, placing QR codes on restaurant tables, receipts or delivery bags is one way of inviting customers to leave a review. Malou gives you the trick for redirecting your QR codes directly to the "Leave a review" page.

→ Find our tip here!

But once again, it's hard to control that the QR code doesn't fall into the hands of a disgruntled customer... However, thanks to this lever, the customer only has to take 4 steps to leave you a review. 1. scan the QR code with their phone 2. click on the link 3. write the review 4. send.

What if we went one step further, from 4 to 2? At Malou, we've created magical totems for restaurateurs! Thanks to contactless technology, customers simply hold their phone up to the wooden tablet, and the "Leave a review" page opens by itself!

Our magic totems have proved their worth: 800 reviews in 1 month for Kozy Kanopé, 160 reviews in 1 week for Breathe... Watch their reaction on video 👇

-> magic totem pole video

2. Why and how to respond to customer reviews in the best possible way, using Artificial Intelligence

a. Decisive impact on restaurant appeal, customer loyalty and local referencing

Responding to your customers' reviews is first and foremost a way of thanking them and showing your appreciation. You consolidate a stronger bond with them, which helps build loyalty. And did you know that with every response, the reviewer receives an e-mail notification ? An opportunity for you to create a new point of contact with the customer. Take advantage of this opportunity to inform them of new products, current offers, etc.

Responding to your reviews also plays a role in converting your potential customers. After all, the attention you pay to your customers' experience influences the decision of many Internet users when choosing a restaurant. By responding to reviews, both positive and negative, you show that you're listening to concerns and taking feedback into account to improve your offering. All this has a positive influence on your restaurant's image, and helps convince Internet users to visit you.

Finally, Google values establishments that care about customer satisfaction. The algorithm pays particular attention to the answers you provide, for both positive and negative reviews.

b. Follow a relevant keyword strategy in your answers

To move up in the search results of your potential customers, a keyword strategy is essential. For example, the Bon Bouquet brunch restaurant is positioned on the words "brunch paris 9", "pancakes paris", "brunch galeries lafayette"... 

→ To follow the steps of an effective keyword strategy, go to our article here!

The next step is to use your keywords wisely in all strategic areas of expression. Your Google listing description, your post captions, the names of your photos and, of course, your responses to customer reviews. The use of your keywords must not distort the meaning of your sentences. 

→ To find out how to use your keywords properly in all expression spaces, visit our article here!

At Malou, we help restaurant owners work on their positioning on the most relevant keywords. After filling in a questionnaire about the restaurant, the MalouApp, connected to Google feeds, generates a list of strategic keywords, their respective search volumes and the best-positioned competitors. To ensure they are used correctly, a gauge, ranging from green to red, tells the restaurateur where and how to use his keywords.

c. Don't leave negative customer reviews unanswered

Don't ignore reviews left by unhappy customers. Responding to them shows that you care about each and every customer, and take it to heart to improve. This is appreciated by the people concerned, potential customers and the Google algorithm. The search engine rewards your attention by moving up your listing in the search results, and by reducing the weighting of negative reviews on your average. Your Google rating will be less affected by a negative review that's answered than by one that isn't.

But how do you respond? First, make sure it's not a fake review. In 2022, TripAdvisor removed 1.3 million fake reviews left on the platform.

→ To find out how to spot fake reviews, and remove them, our friends at Lightspeed explain in detail here!

If it's a real customer, it's up to you to remember their visit, to make sure they're honest. In any case, don't get involved in a conflict. Instead, invite them to express their dissatisfaction in private.

d. Automate responses to customer reviews for better performance using Artificial Intelligence

Responding quickly to customer reviews of your restaurant is important for a number of reasons. 

• Show your commitment to your customers. By responding promptly to their comments, you take their satisfaction seriously. This helps to retain the customer who visited you only a short time ago.
• Avoid misunderstandings. By responding quickly to negative comments, you can defuse a situation before it escalates, and ease the frustration of an unhappy customer. 
• Influence potential customers. If someone sees that you've responded quickly, they're more likely to trust you and try your restaurant.
• Positively impact your local SEO. Google takes into account how restaurants engage with their customers online, including how quickly you respond to customer reviews. The faster you respond, the higher your online profile, which in turn improves your visibility in Google search results.

But to achieve this, you need to devote time to it on a daily basis. Time that you, as restaurateurs, don't necessarily have, in parallel with all your operational tasks.

What if your replies were sent automatically, AND personalized according to the author and the content of the review left? At Malou, we're developing a function based on Artificial Intelligence to send responses without waiting! By detecting what the customer feels, whether positive or negative, Artificial Intelligence formulates an appropriate response. Taking into account the feedback provided by the reviewer.

3. Improve operational efficiency and customer experience by analyzing customer reviews

a. The importance of understanding customer feedback

Collecting positive reviews and responding to all those received is essential. What if you used your customers' feedback to benefit your business? Understanding and assimilating what is said in your reviews will enable you to improve your restaurant's efficiency, fine-tune your menu, warn or congratulate your teams... Because what better feedback than that of your customers?

Understanding your customers' feedback individually and as a whole enables you to draw numerous conclusions, so you can adjust your service operation à la carte. But whether you're collecting 200 or 2,000 reviews a month, gathering and analyzing all the feedback in an objective way quickly becomes very complicated and tedious. This is a real challenge for restaurateurs, if they are to improve and survive over the long term. In other words, it's difficult today to understand what's positive in the volume of reviews, and thus focus on it, and what's negative that needs to be changed.

To meet this challenge, we've integrated a unique feature into our Malou solution that provides restaurateurs with automated intelligent analysis of their reviews, based on different categories. Based on Artificial Intelligence, Malou's semantic analysis generates detailed customer feedback reports for restaurateurs. Find out more now!

b. Semantic analysis of restaurant reviews for better performance 

Ready to improve your service, adapt your menu to keep only the bestsellers, adjust certain recipes...? To find out how, analyze the reviews left by your customers.

Malou's integrated semantic analysis identifies, for each sentence of each review, the main categories referred to by the author: cuisine, ambiance, service, price... Then, the algorithm associates the customer's feeling with these categories: positive or negative. For example, if you receive a review saying that the pizza was overcooked, a red mention will appear in the "Cuisine" category, with the information that the pizza was perceived negatively. 

All the feelings expressed in each review are then grouped together in detailed reports provided by MalouApp, giving the restaurant an overall view of its business. In this way, the restaurant owner can keep track of his customers' feelings: 

• (1) For each category ("cuisine", "prix", "atmsophère"...) find out the proportion of positive and negative feelings perceived by your customers, as well as the overall proportion of feelings across all categories.
• (2) In each category, find out the details of what your customers liked and disliked. For a brunch restaurant, for example, if the term "pancake" in the "cuisine" category was reported many times as positive, then you should keep it on the menu! 
• (3) Discover the evolution of positive and negative feedback for each category over time. You can thus deduce, for example, when the reviews for "Service" were most positive, or vice versa.

These different views enable you to make decisions and adapt your actions in the restaurant. 

The semantic analysis of your reviews, i.e. the analysis of your customers' feedback, enables restaurants to : 

• Quickly understand what customers liked/disliked most about each review 
• Respond quickly and appropriately to the feelings expressed in the notice
• Get an overview of the elements, in different categories, appreciated or not by a large proportion of customers
• Track the evolution of customer satisfaction in each category over time
• Act accordingly

c. Semantic analysis of restaurant group reviews for better management

Semantic analysis of customer reviews also plays an important role at the level of a group of restaurants. 

Understanding general trends. Aggregated semantic analysis allows you to understand the general trends that emerge from all the reviews. The most popular dishes, recurring problems or strengths of each restaurant...

Track reputation. By aggregating the reviews of several restaurants, it becomes easier to track the reputation of each establishment and of the group as a whole. By monitoring positive and negative ratings as well as comments.

Make informed decisions. By understanding general trends and specific customer feedback, the restaurant group can make informed decisions. To improve the quality of its services, adapt its offer to customer needs and meet their expectations.

Reduce marketing costs. Aggregated semantic analysis can also help restaurants target their marketing more effectively and cut costs. By using data to understand their customers' preferences and needs.

In short, aggregated semantic analysis of reviews is a valuable tool for restaurant groups looking to improve their reputation, their offering and their understanding of their customers.

Malou's semantic analysis enables restaurant groups to visualize general trends across all the restaurants in the group. This can help them identify which categories have the greatest impact on overall customer satisfaction, as well as the group's strengths and weaknesses in each category.

Allows you to identify the differences between the group's establishments for each category of criteria. It shows which plants stand out positively or negatively from the others, and identifies the reasons for these differences.

4. Semantic analysis of your MalouApp reviews

We wanted to respond to this challenge: to use the opinions of the people in the best position, the customers, to improve our performance on the spot, but also to optimize our menu according to their preferences.

It's a unique feature on the market, and one that we at Malou have spent a lot of time working on, so that we can now offer you a version that's perfectly adapted to the needs of restaurateurs.
To get a better idea of how semantic analysis of your reviews works, get in touch with us! We'd be delighted to give you a short demonstration!