Headquartered in Berlin, Germany, Foodpanda is a global food delivery company that operates in more than a dozen countries. Since it relies on a platform that delivers piping-hot meals to its customers directly to their homes or offices, GIS, location technology and mapping are crucial to the company’s business.
Open Street Map and Google are the main partners of Foodpanda in mapping and location. As every restaurant has a delivery polygon, the company uses the customers’ geo-location.
“We use geofencing to mark the restaurant’s geolocation and then we have about three to ten radius where the restaurant can deliver”, says Ashwin Irappa, Director of Product, Foodpanda.
In case the location of the customer and the restaurant overlaps, the app shows all nearby restaurants to the customers and they can chose and order from wherever they want to.
Location Intelligence for crucial insights
The role of location technology in food delivery business doesn’t simply end at geo-fencing. Location intelligence is also used for gaining more useful and actionable insights. One of the uses cases is in fetching insights of a customer to know the kinds of cuisines that are there, cuisine gaps, what restaurants are open till what time, and how far the distance is.
Based on this information, Foodpanda does a cohort analysis which tells cuisine gaps, which are used to get more restaurants in the customer location, so that he can get more options, as per Irappa.
Other than location intelligence and mapping, Foodpanda is also banking on emerging technologies like AI, Big Data and Machine Learning for exceeding customer expectations. In 2018, the company announced that it will open a dedicated technology center in Bengaluru.
FoodPanda is also starting a 500 people team in APAC region which would focus primarily on data sciences and location-based services. The company has hired 60 people for this new team and plans to hire 40 more by the end of October this year.
Accuracy at the core
Foodpanda usually delivers in less than 20 minutes in most markets. With the help of Data Science and Machine Learning, it predicts the best routing, rider, and restaurant based on customer location.
While a lot of people rue about analytics capabilities not keeping pace with data proliferation, Irappa has a different take and sees more opportunities and ample analytics capabilities than challenges ahead for the industry. For people who are from a traditional retail background, e-commerce transactional data is new and one needs to have a business intelligence sense to make predictions, he points out.
What matters most for the location-based service industry currently, as per him, is not transition to automation or business reorientation driven by technological convergence and 5G, but the need for greater accuracy. He believes that AI shouldn’t focus only on routing algorithms because accuracy is essential for ensuring customer satisfaction.
“AI coupled with the geo-location services can improve the accuracy of the location but AI clubbed with 5G will not improve the location accuracy, and that is what the industry needs”, Irappa underlines.