Food tech is a growing segment which needs to capitalise on data and analytics to scale up

Back in the day, ordering a meal from a neighbourhood restaurant was a rather tedious task. There were limited restaurants to choose from and a majority of them did not prefer setting up a system for home deliveries in order to keep the operational costs down. With technology hitting the food ordering industry, consumers today are closer to their favourite meal, more than ever before. They have the convenience of selection, customisation and getting the food they want at a time they like, with just a few taps.

Representational image

Representational image

With this superior ease of accessibility, their expectations of comfort and convenience have increased. Therefore, the most successful food tech companies are the ones who have not just built a strong technology but also delivered on fulfilling these expectations while keeping a check on their operational costs.

Technology today has the power to help businesses make decisions, scale up and innovate. Before the launch of a standalone app, you need to test out the concept, maybe with a small geo and only during lunch hour. Once you gain good traction among the small consumer base, you can work on the expansion.

In 2018, India will overtake the United States to emerge as the second largest market of smartphone users in the world. This holds immense potential for app-based food tech players to attract new customers while retaining and keeping the existing ones engaged. As the demand increases, businesses will need to increase focus on specific factors that contribute to the consumer’s decision-making process — quality of food, on-time delivery, selection, the accuracy of order, ease of ordering and overall customer service.

Here are some ways in which data and analytics can help businesses improve their service quality:

Machine learning and big data analytics

Together, these can help in mapping customer behaviour patterns. Brands can categorise existing and potential customers on the basis of their preferences. This can then be used to intelligently recommend options or cross-sell products. Further, it helps to streamline operations at the back end and seamlessly manage quick and reliable delivery by factoring in the logistics.

Order delivery time

This is one of the most important factors that makes a consumer choose one service provider over the other, in any industry. The challenge is to ensure exceptional point-to-point delivery of service always and everywhere. By leveraging advanced technology solutions such as machine learning, big data and real-time analytics, businesses can get a competitive edge and create enhanced service experience for consumers.

Structuring data to get relevant insights

Online food delivery platforms are sitting on a bulk of customer data. Analysing and structuring these into useful information such as average wait time, experience with the delivery, menu availability, loyalty card points helps in building greater traction on the platform.

Increasing customisation

Every customer is unique in their choices and ordering patterns. With the power of data collected from the customer's behaviour on the platform, developing customised offerings for every customer can go a long way in building a loyal and highly engaged customer base.

Enhancing product search

This can be done by leveraging machine learning algorithms and adding relevant search results or keywords can help in creating a better consumer experience. While this requires heavy dependence on data, machine learning and big data analytics have a potential to increase efficiency and build a seamless user experience.

The future of food will look very different from what it is today. Restaurants and food delivery businesses that are not yet using real-time analytics are missing out on a beneficial opportunity to increase their ROI and gain customer satisfaction which is the core of this industry.

The author is the head of UberEATS India


Published Date: Nov 23, 2017 01:05 pm | Updated Date: Nov 23, 2017 01:05 pm