Most of the time, restauranteurs cannot put a finger on whether it is the food or the ambiance or the crowd or the service or the mood in the restaurants that makes them popular. But data science can decipher what works for your business.
Have you ever wondered why out of the two seemingly similar restaurants with similar kind of menu and location, one does extremely well while the other struggles to survive? Every restaurant owner wants to unlock that magic combination of menu, timing, price, customer engagement, staff and supplies in order to keep clicking and generating incremental profits, while delighting the customers each time. But as the fast and casual dining landscape evolves, it has become harder to do business without understanding your customers deeply and connecting with their core values. Analytics and data sciences can now make behavioural insights actionable, and with digital targeting and personalisation capabilities, you can make your guests like you more than your competition.
How can you put advanced analytics to use to understand customer expectations and gratify them? How can restauranteurs put their time, energy and investments in the right places? Here are some top tips:
No customer visit to a particular restaurant outlet, in a particular street, at a particular time is by fluke; it is a result of a combination of various touchpoints that the customer experienced consciously or sub-consciously before they chose to step into your restaurant and not the one across the street. As you must know by now, one size does not fit all. Restauranteurs must collect, analyse, and test options to ensure customers keep walking in. This requires analysis of customer behaviour, so that you can create behavioural segments that isolate the causal drivers behind their visits such as timing, menu choices, spends, and promotion response patterns.
Let’s study Harry. He visits a quick service restaurant thrice a week on an average, usually orders breakfasts and lunches on weekdays and occasional dinners, finishes the food in under 20 minutes, spends $7 average per weekday visit and $12 average per weekend visit. Given the above information, we can infer that he is probably single, works somewhere nearby where it’s convenient for him to catch a quick meal and probably needs to get back in time after breakfast or lunch break. As you already know, Harry is not the only one with such attributes. Segmentation classifies behaviour like Harry’s across all your customers and identifies people with similar patterns, and therefore similar needs and life/work situations. This segment of people can be targeted with similar engagement strategies and tactics to generate more powerful results.
Data science can help you identify needs that are not fulfilled by your present offerings. Apart from improving your current operations and practices, you can also study how to get the most of what you already have. Is there any scope to improve your margins with the same set of customers? What is the size of this unrealised opportunity? What configuration of your business can achieve this? Would it be profitable to do so?
Let’s look at a leading US fast food chain. They traditionally served lunch and dinner only. Analysis showed that there was a large number of loyal guests (in restaurants around office areas) who visited during evenings for a takeaway order that served one person. The insight that there were many single customers who packed dinner from the restaurant, encouraged the restaurant chain to offer another meal option to capture more share of the palate, and so they decided to launch the Breakfast Menu in select restaurants frequented by such customers. The restaurant chain streamlined the menu, meal combinations, labour and the supply chain to meet the breakfast needs. And, luckily for the restaurant chain, they saw a 12 percent revenue increase that could be attributed to this new meal coverage. But would you really call that luck?
A perfect menu is the holy-grail of any restaurant. Picking the most appropriate items, pricing them right, creating combinations that work well with the customers, modifying the menu according to seasons, and adding new items frequently to keep the menu fresh are some of the important challenges that data sciences can solve. Analytics can help look at the patterns in ordering and consumption data to identify new ways to package existing menu offerings or targeting/promoting a new occasion, in order to uncover new demand.
Domino’s is well known for delivering pizzas quickly to your home, but there’s an entire segment of customers who visit Domino’s outlets for their meals. And out of those, there is a healthy number of families that visit with kids in the age bracket of five to 12 years. So, Domino’s decided to target those kids and offer them a great time eating one of their favorite meals – Pizza. Domino’s created a special kids’ meal called the Joy Box. It was also promoted with occasions such as birthdays, school results, etc., which call for a treat for kids. Domino’s combined other slower moving items on the menu with the Joy Box meal. This targeted and calculated effort by Domino’s drove traffic, engagement and revenue upwards.
Why do favourite joints become favourite? Most of the time, restauranteurs cannot put a finger on whether it is the food or the ambience or the crowd or the service or the mood in the restaurants. But data science can decipher what works for you and distill those insights into opportunities you can create for your business. Restaurant owners must analyse key areas that develop the overall experience; these include ordering, waiting, menu, pricing, ingredients, service, staff, ambience, weather, communication, promotions, and more. These factors should then be correlated with their impact on the customer behaviour including amount spent, length and frequency of visit, promotion response and redemptions, menu preferences, etc., to analyse gaps in your brand’s total impact. Based on the insights gathered, restaurateurs must devise strategies to complete a winning experience and execute tactics to engage and shift behaviour. Yes, it can be done with the power of analytics.
One of the popular fine dining restaurants observed that there was a spike in the number of customers who gave low ratings in their feedback. Digging deeper showed that most of these customers had an order waiting time of 30 minutes or more. Further analysis signaled that the average waiting time in the restaurant had gone up by 15 percent, which was annoying the customers. The restaurant realised that the issue can be resolved by adding more customer-facing staff. The waiting time was successfully brought down and the restaurant observed a drop in negative ratings, an overall improvement in guest satisfaction, and an increase in guest frequency.
There is gold in your data. You need to put that into use by getting an analytics platform that can uncover your opportunities. Let the insights drive your strategies and execution. Integrate the insights with a targeted engagement platform to build an ‘Insight Platform’ that can help you make your restaurant the chosen one.
(Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the views of YourStory.)