“Data Science” : The Important Ingredient in Food & Beverage Industry
Data Science has revolutionized business all around the world. Food and beverages industry, in particular, can largely benefit from Data Science. The FOOD INDUSTRY is one of the largest and most vital industries in the world. It encompasses everything from producers and shipping companies, to grocers and restaurants. Thus, it makes sense that this industry would take advantage of the same Data Science services as financial firms and marketing departments to better understand their consumer, increase efficiency and even create new and innovative recipes to try. This article will focus on few uses of Data Science in Food & Beverage industry and how data is revolutionizing the food industry.
- Can Data Science make new recipes for us?
Yes you read it right. Data Science does create new recipes for the customers. Few questions are asked to the users where they are given options to select their favorite cuisine, ingredient, flavour preferences,etc. and then the machine learning algorithm works by scanning the big data repository that has all the relationships between various ingredients, various chemical compounds, customer flavour preferences, etc. The computer then generates new and creative recipe ideas based on the inputs provided by the user. Based on quality and uniqueness- the best recipe idea is selected. Finally, the recipe created by Machine Learning algorithm is produced to the Chef so that they try it out in the kitchen.
2. Role of Data Science in Opinion Mining
It can analyze customer sentiment by combining reviews, feedback, and social media data. Sentiment analysis is the monitoring of customer emotions over social media networks. Using techniques like natural language processing, it can go through the text and categorize it into positive, negative or neutral. Analysis on text data can also unearth hidden insights which otherwise could be missed, such as which food item is losing its popularity or which particular food chain is receiving negative remarks and for what reasons. They can assess negative reviews to resolve customers’ complaints for preventing poor impressions. To track the strengths & weakness of competitors in the market.
3. Role of Data Science to increase Customers who is passing nearby your Restaurant
The Food and beverage companies use GPS & Location Data to increase traffic in their stores. The GPS location capabilities of most mobile phones provide a channel for retailers to display “pop-up” promotional messages that are highly relevant to an individual’s specific location and past purchasing history. For example, a customer standing in a frozen food aisle can receive a text offering a discount for a certain ice cream flavour nearby that she has bought in the past.
4. Use of Big Data for Market Basket Analysis
Market Basket Analysis is a modelling technique based upon the theory that if you buy a certain group of items, you are more (or less) likely to buy another group of items. For example, if you are in an English pub and you buy a pint of beer and don’t buy a bar meal, you are more likely to buy crisps (US. chips) at the same time than somebody who didn’t buy beer.
Food and beverage companies use Big Data for “market basket analysis” which predicts the most obvious item that a customer is likely to purchase next based on her purchase history and the items already in her cart. Food retailers and restaurants use these projections to create effective combo deals and improve their marketing messages. For example, if the market basket analysis identifies that a customer prefers fries with her burger, then it can create a combo to help her enjoy them together.
5. Use of Data Science for Menu Analytics
Restaurant menus are fertile ground for analytics. Menus can be evaluated by text appearance (fonts, colors, placement), complementary items, and layout using transaction and past order history. A few extra words in the description-”succulent Italian seafood filet” instead of “seafood filet”-translated into increased sales. Diners were even willing to pay more for that very dish. Menu analytics can have far-reaching benefits, whether in identifying trendy food items, creating discounts for winning combinations of such items, or identifying non-performing items and removing them.
6. Consumer Segmentation
It helps to build strategies for segments with similar Consumer attributes/behaviour. Even the biggest food companies categorize their offerings into different customer segments to more effectively meet the needs of the marketplace. With better customer segmentation, designing marketing campaigns and putting customer loyalty programs in place become a piece of cake.
End Note
With many new initiatives coming every day in the Data Science space it is certain that this will soon revolutionize the working of many industries.
Knowledge is power when it comes to Data Science. Just ask the food and beverage industry.
