“Have I procured enough for next week?”
“Will my raw vegetables/non-preservative materials get utilized fully, before getting rotten?”
“Should I price this item for 250 bucks or 300 bucks?”
“How to maximize the profits with given demand and price points?”
These are some of the questions which are at the top of the head of every restaurant owner. Dine-In or QSR – nature of problem remains the same for both, if not the magnitude. Whether it’s an online ordering food app or offline serving restaurant, everyone is facing some of the basic problems since ages.
The problem itself is not so challenging or big, but the methods that have been used to solve these problems are very naïve. With this advancement of technology and world becoming more data-centric these problems can be solved much easier and in a more elegant way with better accuracy. Market leaders like Domino’s, McDonald’s etc have already adopted this approach much early. Have you ever given a thought, why Domino’s ask for your info like name, birth date, contact number during placing an order? The purpose is simple, they want to collect as much data points as they can and use this data later.
I have highlighted some of the use cases of food and restaurant industry, that can be solved in a much better way with the help of data analytics and machine learning.
1) Demand Estimation/Prediction:- When I talk with Restaurants/Food Industry Owners about their pain points, the most important and first most thing that comes to their mind is fluctuating demand. Though working for past 2-3 years they have developed a basic idea of variable demand, but quite often they miss the demand guess with huge margins.
As a result, it leads to wastage of raw materials, staff effort to prepare things and overall loss in business. Moreover, if they beforehand get a better idea of demand, they can make effort to promote their demand on low demand days and procure much better. ML techniques like Time Series Forecasting, ARIMA model have made this task much simpler and more data-driven.
2) Menu Selection:- “What kind of Menu should I keep to minimize preparation effort and maximize sales and revenue?”
This problem may not be so much big for large restaurant owners and industry leaders with more staff bandwidth and much wider reach. But it is a very trivial problem to solve for Mid-size Restaurant Owners and Food delivery Merchants. Due to small/mid-size in nature and limited manpower to prepare the food these kinds of restaurants, can’t serve all kind of foodies.
So having a better menu design can help them in this case. A technique called “BCG Matrix” can help you to give an idea of which things to keep and what things to scrap. A low-priced, highly popular item called “Horse” can help to pull in more foodies for high-priced, highly popular item like “Stars”. Menu Engineering has a different effect on common man’s eating psychology.
3) Price Optimization:- Deciding the price of our sales is the most critical thing in any business. No matter how much volume you sell, if your prices are not set effectively. The most common argument in setting the price of an item is to keep it on the basis of profit percentage, but this is not an optimized way of doing it and it may affect our profits significantly. More variables like Demand, Supply, Peer items on the menu can be other variables that can help to determine an optimized price for an item. “Liner Optimization” is the best technique to perform for setting the price of items in given constraints like demand, supply, profit targets etc.
4) Combos/Recommendations:- In companies like Domino’s, McDonald’s we encounter some trending offers like “Pizza with Cheeze Dip”, “Burger with Soft Drink” etc. Selling combos have emerged as a good marketing strategy in recent times to maximize the revenue with the existing set of customers. Many other factors like the placement of items on the menu also affect buying behavior of individuals. New data trends can be figured out with more and more data and more such recommendations can be produced in order to manipulate user’s buying behavior and maximize the profits.
5) Delivery Time Prediction:- Customer Satisfaction is the foremost thing a business owner thinks about. Best food quality and meeting the SLA’s are the two main factors that can take the customer satisfaction to the very next level. Getting to know about how long will it take to deliver, at order placing time, can improve a customer’s experience very much. Machine Learning Techniques like Deep Learning, Regression Models etc can predict the preparation time and delivery time very accurately. Type of dish being prepared, Hour of the day, Amount of order etc is some of the important features that can contribute to the intelligence of model.
In a nutshell, Machine Learning and Data Analytics hold the power to solve some of the very trivial problems of restaurant owners and food delivery services in a very simple and elegant manner. We here at DataToBiz connects businesses to data and excels in cutting-edge ML technologies in order to solve most of the simple and trivial problems of business owners with the help of data. Feel free to Contact Us.