Data Science and Competitive Analysis of the Indian Food delivery industry

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The pandemic has increased the trend of ordering online food in India. It is gaining more prominence and delivery platforms such as Zomato, Swiggy, Faasos (now Rebel Food), etc.. are on increasing demand day today. These delivery platforms are making use of data science to lift their business and expand their base.

What is the role of knowledge science within the food delivery industry?

Online food delivery companies affect huge sets of knowledge. These sets of knowledge are within the sort of customer orders, GPS service, location of the customer, reviews, etc. Data scientists from the food delivery industry extract valuable information from the data and increase sales and guarantees build brand image and help in building a special bond and relationship with customers.

With digital transformation, we will see that the food delivery industries are adopting data science effectively to serve improved services and to compete within the market. Through the info collected from the purchasers, they understand their customers and determine their tastes and preferences.

According to research, the food delivery market is predicted to succeed in $5 Billion by 2021. As observed, data science is that the drive behind such a rise. The food delivery companies are optimizing data science to an outsized extent to reinforce customer experience and boost business.

How do various food delivery companies utilize data science?

 This article will take you thru a comparative analysis between Swiggy, Zomato, and Faasos.

1. Swiggy

Swiggy has mostly emphasized food delivery with the utmost convenience to the urban livelihood of the country. It operates with data science to provide improved customer experience and drive operational efficiency. Swiggy collects huge sets of knowledge from customer demand and provide, from vendors like restaurants and stores, and delivery executives. This data is extracted for getting insights to extend delivery efficiency and to attach customers to the proper restaurants. Swiggy also provides an app through which both the corporate and therefore the customers can get information. The app helps the purchasers to trace their order, to understand the delivery time, to offer a review, to talk with the chief if required, to ascertain ratings, etc, and all these increase customer experience. From the company’s side, data science is employed to differentiate food dishes from images and categorizing and separating them as veg and non-veg dishes.

2. Zomato

Within the case of Swiggy, how it uses data science to increase customer experience and boost its business, Zomato being its competitor isn’t dropping it’s because of the competition. The food delivery company uses data science to supply order personalization like providing recommendations to the purchasers. Recommendations as in specific various cuisines, price, locations, brands, etc. because of the personalized recommendation, there has been an improvement of 15% within the click-through rates and order conversions. The data scientists of the corporate extract insights from the info that’s collected from reviews and help the team to seek out out the foremost popular dish and to understand a customer’s sentiments.

3. Rebel Food (Formerly Faasos)

Data science plays an important role in Rebel Food. They execute many reviving data science use cases like personalization, recommendation engine, predictive analytics, customer engagement, dynamic pricing, visual computing, sentiment analysis of customer’s reviews, etc. To implement personalization the corporate collects huge amounts of knowledge which is interpreted by the info scientists to reinforce customer experience.

Whether Swiggy or Zomato or Faasos, all use data science to reinforce customer experience and uplift their businesses. Where Swiggy is using data science to supply nutriment delivery, Zomato is using it to serve personalized recommendations to the purchasers. Diversely, Faasos is using data science for dynamic pricing. The only thing that creates a difference between them is that the market share.

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