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The Impact of Data Analytics in Food Industry

The information overload and the amount of data available for every industry have led to the inclusion of Big Data Analytics in our everyday life. 90% of the world’s data was created in the last few years alone. 

From understanding the target audience to knowing what they prefer on a regular basis, there is data available for everything. Some of the data available are noise, and it is important for industries to ignore it while analyzing.

The food industry has reinvented itself with Big Data, IoT and Artificial Intelligence. Big Data has a lot to offer to Mobile Apps also.

More than $1B was invested in CPG startups in 2015.

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Here we will talk about the interesting combination of Big Data and the world of food.

Despite being so largely present, even in the food industry, hardly any of the data is being analyzed as of date. 

In this blog, you will learn how Big Data analytics is essential, and how it has managed to transform the food industry.

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Promotes On-time Delivery

Data analytics plays an important role in ensuring quick and on-time delivery of food. Earlier only a few pizza delivery places offered the quick delivery services. Today, with the help of data analytics, it is possible for every restaurant in the world to offer the same service that too with greater accuracy. 

Let’s see how?

What is the main concern when you want to deliver food faster? You will obviously point towards logistics. If the factors contributing to delivery is good, then it is going to be quick and easy. However, there are various elements that you need to take into account including traffic, weather, and routes. 

Big Data helps the drivers know their routes well, helps them know if there is a need to take a detour to reach the location quickly and helps restaurants and the users track their drivers in real-time. You will need to use data in conjunction with AI to help develop patterns that can, in turn, optimize the delivery methods for you. 

Sprig, the on-demand healthy meals food delivery app has been offering this quick and accurate service for a while now. 

They use data analytics to keep their supplies updated, which lowers the delivery time. They also use the information to understand what the user is likely to order, and where the order will be placed from, for quicker and accurate delivery information. This will be assigned to their drivers and even optimize the routes according to the delivery type and location.

Smooth Operations

One of the major issues facing food delivery apps or the food industry, in general, is the operations. At ground level, there are quite a few factors governing the operations, which makes it difficult for the restaurant or the app to make sure the customers are satisfied at all times, and the employees are empowered to make smooth and fast deliveries. The operations should be such that they don’t compromise on the quality of the food. They also need to ensure that the food does not stock out.

The analytics helps understand what the customer preferences are, and how they will look at a particular product. If the product needs to be sold cold, then the analytics will provide insights into the temperature at which the product should be placed to increase the customer’s satisfaction levels.

DoorDash is into food delivery, and for them, the quality of the food, as well as the temperature at which the food reaches, is of utmost importance. They use analytics to determine the fleet capacity so that there are just enough drivers to help reach all the customers. Also, use analytics to determine the food preparation time so that the quality is maintained. They make on-demand fast, and accurate. 

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Predictive Analytics

The food supply chain is enormous and complex. As a result, you may face issues when moving from one part of the supply chain to the other. Predictive analytics, the result of Big Data, can help assure the quality of the food, as well as predict the inventory that requires to be restored. It can also help with predicting the freshness of the food that is coming to you.

  • You will know, based on the data available for soil samples, whether the harvest had matured before it was cut or not. You will also know what price to pay for the crops
  • The weather conditions can help you predict if the crop will survive or not. In the case of food delivery apps, it can predict how fresh and hot the food will be before it reaches you.
  • Finally, the farmers are critical to the supply chain, and predictive analysis will determine if the crops will survive and make it to the market or not. Based on historical data, it will also determine the price these crops would fetch and the final food price for the vendors.

Customer Preferences and Recommendations 

Big Data analytics largely caters to customer preferences and the recommendations that will help build a good base for your restaurant.

The historical data when analyzed will help you know what the customers generally prefer buying from you. if you are into farm-fresh food, then you will know just what kind of farm food to stock up so as to increase your ROI. In the case of a normal food store, there are some items that sell more with the target audience. You will know exactly what to stock in this case.

Restaurants can use the Big Data analytics to understand what was ordered previously, what kind of orders are mostly preferred and the price ranges opted by the customer before suggesting the food types to these users. It will not just boost sales, but also positively impact the restaurant. 

GrubHub has been offering recommendations to the users based on their previous orders. They also look at the demographics and other purchase behaviours before offering the recommendations. 

The recommendations take personalization into the food industry as well, which will eventually improve the customer’s experience and interactions with the food business. 

Tracking the Origin

You want to know where and when the particular food originated and is it contaminated or not. In the case of food, the food inspectors conduct regular audits to check for this possibility. With Big Data analytics combined with IoT, you can easily detect if the food is stale, there are bacteria in it or, track the food shipments back to the origin as in when and where it was ordered from. It not only helps restaurant owners keep a tab on the food sold at their outlets, but also prevents a shutdown, which becomes a possibility in case they sell outdated food.

You can even keep up with the safety and food temperature guidelines as a result of technology. 

Also Read: How Delivery Apps Hide Their Charges

Summing up

Food Industry is one of the most dynamic industries in the world, as it is constantly evolving and customer preferences are constantly changing. You need to keep up with the quality needs, changing preferences and even the operational trends to make sure you boost their experience at your outlet and improve their satisfaction levels. 

Big Data analytics will help you know how the customer prefers their food and predict the changing landscape of the industry. Every bit of data can be analyzed to make the supply chain operational, and every stakeholder within the supply chain more aware and informed to make real-time and quick decisions. 

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