Zomato, Swiggy using AI, machine learning to drive more growth
If routine jobs will 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. Both Swiggy and Zomato boast of handling over a million orders a day across more than 300 cities.
The automation made up for almost 10% of the workforce in certain support roles across Zomato’s customer, merchant, and delivery partner teams, redundant, around 540 support staff last week, let go off because of improvement in its after-sales technology forced its hand.
Each customer order is now being influenced by the customer’s own previous history of order preferences .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.
Now both food-tech apps are now primarily using data to tap demand. 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. Zomato currently provides a business dashboard for restaurants on the web as well as the app, according to a company spokesperson. They have focused on tracking dish-level ratings and are working towards adding more features to the dashboard.
According to Singhal, Artificial Intelligence (AI) might be able to do a good job in predicting and bringing back the customer to the platform but it will only make an incremental difference–it will not change the world for these companies. But this is not because the AI models are not mature enough–it’s more because of human nature.
