While routine jobs will continue to give way to automation, food-tech companies such as Swiggy and Zomato are increasingly turning to machine learning (ML) and automation to drive their businesses, using years of data accumulated from food orders and user-level consumption patterns.
Swiggy boasts of more than 1.3 lakh restaurant partners on its platform, while Zomato claims to have added around 1.5 lakh restaurants. With such a large supply base in place, both food-tech apps are now primarily using data to tap demand.
Swiggy, for instance, banks on its history of order-level data and real-time feet data to reduce customer wait times and for retaining customers. “We are processing around 40 billion messages (or data points) per day, which are unique data points purged from either customers ordering from our app and from drivers delivering orders. And if I look at that, scale, will probably touch 100 billion messages within a year," said Dale Vaz, head of Swiggy’s engineering and data sciences department in an interview.
Swiggy is using data analytics to individually curate the customer landing page—list of restaurants—to each user’s taste preferences rather than just curating on the basis on the customer’s location. According to him, food is a personal choice, and cannot be generalized on the basis of the location of the customer alone. The company said that it’s building a concept known as “food graph" which breaks down a food dish by recipe, cooking style, ingredients used, calorie value, and variations of the dish
Read More about how AI is driving the growth of Giants like Zomato and Swiggy...
#AI #ML #Zomato #Swiggy #BigData #Probyto #ProbytoAI
Subscribe and follow us for latest news in Data Science, Machine learning, technology and stay updated!