Big data analytics changing the rules of road travel

Published September 10, 2013   |   

San Francisco-based radio cab service provider Uber started operations in India recently. While one can book Uber’s luxury taxi service using a smartphone app, most Indian radio cab players, too, are using similar technology, making use of big data to understand the future demand scenario.

Companies such as Meru Cabs and OlaCabs among radio cabs and bus ticket booking provider Redbus have also been using

“By using this data and based on everyday predictability of data, we try to enhance the number of trips that one cab makes per day,” said Siddhartha Pahwa, chief executive officer of Meru Cabs, one of the earliest players which claims to have a customer base of about two million and a fleet of 5,000 cabs. It has been collecting data over the past six years.

About a year-and-a-half- ago, the average trip made by a taxi driver at Meru was four per day. This has improved to 5.8 trips now. Radio cab firms are also collecting data on traffic situation, road condition and speed, which they say help them offer better services to customers.

Take, for instance, OlaCabs, which has been mapping the demand-and-supply scenario from Day One of its operations. This has given it insights into where the demand will peak, at what time of the day, so that they can place more cabs in that area. This is something Uber has been doing in the US. “Since we can predict the demand, we can allow the cab driver who is closer to the location take the business. This reduces his travel time and gives him better returns. In general, the maximum capacity utilisation among taxis is 40 per cent. With us, drivers have increased their utilisation to 85 per cent by understanding what is the best time for them to make maximum business,” said Bhavish Aggarwal, co-founder and CEO.

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