OLA Trip Match Making Algorithm
Today, booking cabs over the phone is a common practice. It would take about 2 minutes to book a cab and this can be done at the comfort of our homes or offices. Companies such as OLA and Uber have succeeded in this field greatly. It is very convenient to book autos or cabs from phones rather than to go out and actually look out for one. Other important features are in terms of safety and payments. Customers can pay through UPI or cards immediately, they do not need cash to make the payment. Details about the driver, the ratings are clearly shown, this ensures safety to the customers.
From the customer point of view, it is very simple to book a cab. The drop off location has to be selected along with the type of cab needed. The customer is then allocated to a driver. Customers receive a notification when the driver reaches the location, the payment method is set up. Overall, the experience is free flowing and easy. It is much more convenient than going out and looking for cabs on your own.
The question asked is, how does this work? There has to be certain algorithms that are running in the background that match the customer with the driver. This algorithm not only has to be fast but also has to be accurate. Customers are the king and they should not be left disappointed.
Here is an insight into algorithms that are being used by Uber, OLA and other cab services to match customers and drivers.
The main algorithm in play here is the buyer pick model. As the name suggests the buyers or the customers are in a luxurious position to pick according to their preferences. The customer here picks the type of cab he needs. Usually, in a buyer pick model, after the preferences are chosen, the customer is given a list of choices to pick from. In the case of OLA or Uber, this part is automated. The driver is automatically picked. The customer is then shown the fare of the trip, if the buyer is happy with the cost, the cab can be booked.
OLA and Uber have with them a large database of drivers, once a customer requests a cab, the driver closest to them at that point would be assigned the trip. Lots of data such as traffic data, location data, time are constantly used to predict the demand and supply at that point of time to decide the prices.
One of the main concepts these cab companies use is the concept of surge pricing. Prices increase or surge at a rush hours in the day. If the customer is travelling to a crowded part of the city, the prices may shoot up. Surge pricing is also used in bookings for hotels and flights. Increase in pricing is done very carefully considering demand and supply.
These matching algorithms usually have a concept of double commit. In this concept, the trip has to be committed from both ends, i.e. from the rider and the driver. Once, the customer accepts the cab at a given rate, the driver can then choose to accept or reject the request.
These algorithms also include a concept of hard and soft filters.
Hard filters ensures a comfortable ride to both the drivers and the riders. These filters can be set by both according to their preferences. These filters are the conditions that have to be met before the match is made. Some of the hard filters can be the location, price criteria, time of pickup etc. In countries like the US, where it is common for women to work as cab drivers. The algorithm also allows the rider to choose the gender of the driver. These filters are known as hard filters because these are conditions that have to be met.
Soft filters help in filtering out the results. These can be filters related to the type of cab, ratings of the driver etc. Soft filters can help balance out the load and ensure that drivers are not over burdened with trips. These algorithms can also help in providing the driver the optimum route to the destination. These filters are subtle in nature, it may not be visible easily but they are continuously applied in the background.
These are some ways in which OLA and Uber use data science techniques to improve their business. The algorithms used by these companies are very powerful and these algorithms are very private. There maybe some features that are maybe giving them an edge over their competition. Ensuring customer satisfaction is very important for companies in the long run. Cab companies such as OLA and Uber are also becoming very environmental friendly by running electric cabs. These cabs can reduce air pollution and avoid harm to the environment.
