Carsome uses data to elevate the customer experience

As Southeast Asia’s largest integrated car e-commerce platform, Carsome is at the forefront of digitizing the region’s used car industry and elevating the experience of both buyers and sellers. The company’s end-to-end solutions for consumers and dealers include everything from inspection to ownership transfer to financing and promise a hassle-free service that’s trusted, convenient, and efficient.

Throughout its six years of operation, Carsome has gained a wealth of data points about the region’s used car industry, which it uses to understand customer behaviour, inventory, and pricing. Tableau has simplified the analysis of this data, providing Carsome with faster insights which in return help to improve the customer experience.

Carsome’s analysis of demand and supply and clickstream analytics is extensive. It combines raw data from multiple sources and presents it in an easy-to-consume format to help employees make better and smarter decisions. For example, they can decide which inventory to source based on demand and fine-tune pricing algorithms to deliver the best value to sellers.

The challenge before Tableau was that analysis consumed too much time, and it was difficult to drill down into the details. Insights were delayed, and employees could get lost in a barrage of dashboards and data that was not always relevant to their role.

“Decisions can be especially tough when we don’t have all the information and that’s why it’s important for us to have the whole story,” said Piyush Palkar, Chief Data Officer at Carsome. “Whether we’re helping someone find their dream car or helping them get the best value for their used car, we can make sure every decision we make is the best one for our customers.”

Replacing its previous BI tool with Tableau has helped Carsome get the whole story from its data quickly and easily. Analysis can be performed at a much faster pace, and the visualizations are easy to digest so that users can see critical information at a glance.

“Getting faster insights to make faster decisions is the key to success in any business today. We are now able to easily do drill-down and bottom-up analysis as well as slicing and dicing the data quickly,” said Palkar. “Tableau supports us with automated dashboards that provide up-to-date information and help us narrow in on what’s important.”

For example, when evaluating funnel analytics, Carsome can quickly identify where drop-offs are occurring and direct its focus to the underlying cause.

Carsome chose Tableau for a number of reasons, including its features, value, and massive community of users, which makes it easy to onboard BI resources. Deployment time was also a consideration for the fast-moving startup, and, in the end, it only took the company a couple of days to install and configure Tableau Server.

Close to 300 employees have been onboarded so far as Carsome keeps growing and actively builds its data culture. The company wants to empower individuals at all levels with a sense of how data can add value to their work, and it holds frequent training sessions and weekly user groups to build data literacy.

“Many employees are already feeling empowered after discovering that much of the information they want is readily available, and there’s no need for them to learn to write SQL scripts,” said Palkar.

While the data team supports various cross-functional teams with visualizations and reports, some employees take the initiative to create their own. Encouraged by the company, many have also turned to Tableau’s broader community of users to seek answers and support.

As a result of all these efforts, Carsome has seen a significant improvement in self-service and data-led decision making. For example, car inspectors and retail managers are able to come up with price proposals on their own using the company’s Reserve Price Proposal & Price Prediction dashboard.

There's also great collaboration around data, with employees sharing and commenting on Tableau workbooks to communicate and digest complex ideas and numbers.

Carsome’s business is centered on improving the experience of buyers and sellers, and they are, of course, the clear beneficiaries of its data transformation. For example, the decisions made with Tableau help to ensure Carsome has the cars that buyers want and allows the business development teams to recommend the best cars to dealers as well.

Carsome is now building on these benefits by enriching the data in Tableau and making it a golden source of curated, validated, and trusted data. A new datalake plays an integral part in this and brings together production and third party market data where even machine learning model inputs are feeded back to Tableau.

In the future, Palkar anticipates automation and augmented analytics will help Carsome do much more with its data by decreasing the time spent organizing and preparing datasets. “In time, we should be able to ask more questions of our data without worrying about the underlying infrastructure. Or, to put it simply, we can worry less about tying our shoes and focus more on running.”