Technology, today, plays a fundamental role in the restaurant industry. The data collected – not only via mobile phones – inform and reveal how an eatery is doing, how it should improve. But it is vital to know how to read them. What customers eat, how they pay, and how much they pay, how long they wait, what their preferences are, what they leave on the plate, what our food waste is, where they book… Analysing the resulting data can be used to improve customer experience and increase profits for the restaurant.
Jesús Pombo, at the helm of Poncelet – the best-stocked cheese shop in Madrid – foresaw the golden age of artisanal cheeses, and is today its messiah. His temple, next to the shop, is the Poncelet Cheese Bar, a meeting point bringing the public and cheese together. As an economist he understands Big Data and restaurant management to a T, and this year will appear at Madrid Fusión to offer an in-depth look at a topic that ‘allows restaurant owners to make the best decisions and improve customer experience.’ Let’s celebrate the New Year with him.
How can Big Data help restaurant owners?
Big Data must help us to adapt to – and anticipate – our customers’ decisions: to know what they are going to order before they do so (making pricing more effective…); know how many people will be at a given seating (staff efficiency…); which dishes they like (adjust the menu…); etc. When all this information has been gathered, it can be used to improve what you offer; in other words, you can draw on Big Data to make the best decisions and improve customer experience. Day-to-day actions, such as those described above, together with many others, produce an enormous amount of information which, after being treated and analysed, can be transformed into more personalized experiences for customers.
So, the goal is to personalize experiences?
One of the goals of Big Data is to offer each customer a unique experience based on their behaviour and preferences – extrapolated from previous visits to your premises. Another is to adapt it to the changing conditions your restaurant might undergo, such as a daily menu, and to other external factors (seating numbers, the weather, restaurant seating layout, etc).
Explain to us your experience of using this technology.
At Poncelet we have developed an algorithm to predict sales, volume, average bill, seating numbers depending on the season and weather temperature, rain or other kinds of climatic circumstances. Given these conditions, and using association rule learning (a rule-based machine-learning method), we can design the kind, or variety, of dishes that our customers might consume on a particular day, or days, and according to a specific situation. We can thus determine which dishes on the menu will be the most ordered by our customers on a particular day, at a particular time or season, or by a specific customer segment. Using all of this, we can forecast management and optimize purchases and human resources.
Data, and results that are advantageous for both parties.
We thus know which dishes on the menu are better to offer on a certain day, at a particular time or season, and depending on the type of customer. This allows us to achieve a ‘menu mix’ that interests us, creating combinations of dishes that increase sales and profitability.
Other parameters we use.
We have pinpointed, for example, how seating numbers in the restaurant affect the average bill, or how the seating layout can affect table turnover by observing if some tables make more money than others due to their position, or if one specific table affects the table turnover of others around it. We have also studied if a dish, or a type of dish (starter, meat, fish, vegetables, etc.), contributes to a greater or lesser extent to the success of the menu and, therefore, to the success of the restaurant; or if tables or diners who have a promotional discount influence the compositional nature of the dishes they order.
Are restaurants in Spain ready to implement this methodology? How much is it being used in Spain?
Although it really boomed about four or five years ago, Big Data in Spain is still in its early days, and more so in the restaurant industry. People are not yet aware of the huge importance of data. As we say at Poncelet, ‘data’ is just another ingredient.
This data is not only acquired via mobile phones…
No. The information needed to implement Big Data in a restaurant is not just collected from mobile phones. This information can be gathered from many sources.
Is the rise in the delivery sector a consequence of Big Data?
I don’t think it’s because of Big Data, but rather as a consequence of our customers’ needs and today’s lifestyle. Big Data helps us to foresee demand via this channel, regarding both the number and types of dishes, depending on the day it is, events, the weather, etc.
Which country is the pioneer in this methodology?
The United States. As a country, they immediately saw the importance of data. They came up with the first statistics, weather records, the first documented harvests, etc. Data collection and its analysis have been essential elements of social progress. The advances achieved during the 17th and 18th centuries in fields such as calculus, the theory of probability, and in statistics rapidly became indispensable tools for scientists for predicting the movement of stars, or anticipating crime rates, marriages, and suicide rates.
A new year has just begun. What’s in store for us in this context in 2019?
This year will see significant changes in technology such as 5G, Artificial Intelligence, Blockchain, data privacy, and the cloud; all areas where Big Data plays a role. And its use in restaurants will increase.