Know how big data analytics help restaurants & food delivery apps to understand customer preferences, predicting demand, and provide fast delivery to its customers.

Laughter is brightest where food is best. – A famous Irish proverb
Food is one of the necessities of our lives, we cannot survive without it, and we need it every day. But as humans have always done, we have made this requirement of ours into a full-blown industry. Food has grown into a multibillion-dollar sector all over the world, employing millions of people. With the rise of food delivery apps like Grubhub and Zomato, the food industry is going through a golden period experiencing an exponential increase.

​With the option of ordering online from their favorite restaurant, the customers are getting spoiled. As more and more people avail the facility of ordering their food online, the food delivery industry is growing phenomenally. A lot of data is generated when a customer requests food online. The kind of food that user orders, the time of ordering, taste that the user prefers, and so on. People are generally fussy about their food, and by analyzing the data mentioned above, the food delivery startups can cater to a delightful experience for their users.

Being a premier Big Data Analytics service provider, we know the impact that data analytics can have on a business. Having a robust Big Data Analytics system can have a positive impact on the bottom-line of a business.

Let us analyze how data can help you in your endeavor to become a successful food delivery company.

How Big Data Analytics benefits the Food Delivery Apps?

Big Data Analytics in the food industry helps you in understanding the preferences of your customers accurately. By analyzing the choices, you can tweak your offering to suit the taste of your customers. This will help you in improving the average revenue per user.

🔹 Improve your menu

By using Big Data in the food industry, a food delivery app can gather the feedback of the customers regarding the items on the menu of various restaurants registered. It can then suggest the restaurants regarding the menu items that can help the restaurant in increasing its revenues.

By changing the menu items, restaurants can boost their operational efficiency. They can also offer more promotions on popular items and generate more sales.

🔹 Provide faster deliveries

There are a lot of factors involved in the success of food delivery apps. The most prominent being fast delivery time. If a food delivery app can provide faster delivery times to its users as compared to its competitors, then it will significantly outperform its competitors.

Although the process of taking freshly cooked food from restaurants and delivering it to the customers may seem simple, there are many difficulties which need to be tackled.

Using Big Data Analytics systems, a food delivery app can monitor various elements like traffic, roadblocks in the route, climate conditions, and give the shortest possible path to a delivery person, ensuring that the food is delivered in the fastest possible manner.

The Artificial intelligence(AI) and machine learning systems can provide real-time updates to the delivery person so that he/she can change the route and ensure that the customer always gets the food in-time.

🔹 Analyzing customer sentiment

In today’s world, where social media is playing an essential role in deciding the success or failure of an app, you cannot afford to ignore the customer sentiment on social media. Using Big Data Analytics, you can gauge the inclination of the customers towards your brand.

Are your efforts paying off? Are your delivery persons delivering the food quickly? Are your customers happy with your overall performance? You can get the answers to all these questions and more after analyzing the social media chatter using a Big Data Analytics software.

Big Data Analytics software will compile and analyze all the mentions of your brand across various social media handles like Twitter, Instagram, LinkedIn, and Facebook. You can then drive your business decisions based on this data.

🔹 Predict demand through smart algorithms

By using a smart Big Data algorithm, a food delivery app can predict the customer’s next order. It is easier than you think; by analyzing the browsing history of a customer and the past order data, the food delivery app can predict when the customer is most likely to order.

For example, Joe is a customer who usually loves to eat cheeseburgers during dinner on weekends. A food delivery app can partner with Joe’s favorite restaurant and offer him some promotional discount on his favorite cheeseburger. The app can also nudge Joe to eat healthy by offering him various other options.

By using predictive analytics, a food delivery app can estimate precisely how many customers will order during a particular time of the day or week and from where. For example, it is common knowledge that their beer sales spike up during big match days. But, a predictive analytics algorithm can tell you exactly which brand of beer will sell in which area of the city.

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How Big Data Analytics benefits the Food Delivery Apps?
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