The way consumers shop, trade in and purchase vehicles has rapidly transformed from an overwhelmingly traditional dealer-based sales model to one that puts customers in the driver’s seat. This evolution includes providing dealerships with solutions to transact completely online while delivering best-in-class experiences via new retail channels and fresh markets.

A U.S. provider of end-to-end products that helps car dealers compete in the virtual retailing space against disruptive competitors (such as Carvana) needed to adapt to this evolution.

The company turned to NTT DATA for help developing advanced analytics that would interpret large amounts of dealer and buyer data to better support its dealer network and enhance the buying experience.

Business Needs

COVID-19 accelerated changes in how people shop. With consumers now driving the vehicle purchasing cycle, this company needed to develop an enhanced virtual shopping experience. In fact, it had become critical for customer satisfaction and dealership continuity across remote and hybrid retail environments.

The company turned to NTT DATA’s decision-driven analytics framework, Decision Architecture, to learn:

  • What information consumers need to transact online, and at what stage in the sales process
  • Whether systems were operating effectively and driving sales for dealers
  • If dealers were satisfied with their investment in these innovative tools


  • Interprets large amounts of customer data to make decisions
  • Helps dealers attract and engage more buyers
  • Equips dealers to serve clients better and manage their inventory based on customer preferences
  • Increases dealer subscriptions to the company’s services


Using Decision Architecture, the team developed tools that provide two types of diagnostics: internal diagnostics for the company to optimize its offering, and external diagnostics that its dealers can use to analyze and adjust various levers at their disposal.

For example, are there enhancements the company can make to improve the dealers’ online experience on the site and boost their return on investment? Is spending for marketing/advertising effectively driving traffic to the site? Once people are on the site, are they converting into customers? If they drop out before purchasing, where does that occur? Is it a problem with inventory, with credit approvals, with other parts of the transaction?

With powerful web analytics at their disposal, the company and its dealer network can easily interpret large amounts of customer data — and that’s good for both parties. Armed with insight, the company can make adjustments that better serve its dealer customers and increase subscriptions to its services.

In turn, dealers can extract more value from their investment by managing their inventory based on a better understanding of customer preferences. They can also attract and engage more buyers through a desirable online experience that capitalizes on the growing demand for click-to-buy purchasing.

About the case study

A provider of digital automotive marketplace services uses advanced web analytics to optimize offerings and support its dealer network.




United States

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