How innovations in data science lead the way for Uber’s business growth

While there are consistent ways on how data is used to improve customer experience across Uber globally, in some geographies such as India, data is used to solve some very specific problems, says Manikandan Thangarathnam, Senior Director, Engineering, Uber India

How is Uber using data analytics to deliver excellence in customer service?
The usage of data analytics to augment our customer experience is of paramount importance at Uber, and happens along the life cycle of every rider. It ranges from how to provide a frictionless, quick ride to the user, to improving the entire ride duration from the pickup experience, to the wait time, all the way to the completion of rides. Each and every workflow in the rider’s journey is continuously improved with the help of data.

For the earners on the platform, Uber is committed to ensuring we provide the most rewarding experience on the platform. Data is used to provide insights to the earners on how they are faring and how they could increase their earnings by choosing different gigs (Delivery vs Mobility), or even riding to a different location where the demand is high.

Lastly, data is also used extensively to flag any negative trends in any customer’s experience so that future downtimes or bad experiences can be mitigated within a matter of minutes.

Which are the various data segments you are using in everyday operations in India?
While there are consistent ways on how data is used to improve customer experience across Uber globally, in some geographies such as India, we use data to solve some very specific problems. As an example, using data, we are trying to solve mobility problems within categories of high capacity vehicles and ridesharing. We are also using data analytics to improve reliability on the platform to ensure shorter pick up times.

How critical is innovation in data science for Uber’s business growth ?
Uber has been leading innovation in the mobility and delivery spaces since its inception, and we continue to innovate as there are still many unresolved problems. Innovations in data science continue to lead the way for our business growth. Today, we are using data science innovations to onboard earners on the platform seamlessly, in quick time, and while meeting compliance requirements. Moreover, we are innovating on how an earner on our platform can opt for multiple gigs to improve their earnings and maximise their earnings while using the platform.

In addition, for all of Uber’s new growth areas, including new and existing features, data science innovations are used to predict the right customer segment to provide them with a very personalized experience.

What are the challenges you face regarding data quality and data governance ?
In most pioneering tech organisations, getting the feature out to the customer is always a priority. Uber has always focused on a data-first mindset and as a result we have matured very well in our data quality and governance journey. At Uber, we have a very clear ownership model of data that allows us to manage data exceedingly well in terms of its quality, completeness and compliance. Our investments on data have tripled over the past year and as a result, Uber has built various custom tools and monitoring frameworks to detect any data quality issues at the earliest, and mitigate them fast enough to ensure Uber relies on trustworthy data at all times.

Given the scale and the complexity of data at Uber, coupled with how critical data is at each and every life cycle of our customers, the challenges of scale and complexity still exist where we continue to push the boundaries and lead in the data quality journey.

Your views regarding how innovative technologies can shape urban transportation in India, in the not so distant future.
Innovative technologies such as ridesharing apps are commonly used, but still by a small segment of people in India. We are working to expand that segment by adding more products to our portfolio (UberAuto, UberMoto etc). We are investing in innovative technologies to build products such as Uber Bus, Uber Rentals, and Intercity, which will have a much wider acceptance in countries like India. India is mostly always a supply-constrained market, so if we are able to innovate and deliver the right product at the right price point, there will always be demand. We see this as a huge potential for Uber to leverage its core platform to deliver new product offerings in the country.

Data ScienceinnovationUber
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  • keerthi ravichandran

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