TOKYO: Automotive manufacturer Nissan Motors is embracing big data and analytics as a tool to measure marketing ROI, increase conversions, and evolve its brand for a new generation of consumers.
Asako Hoshino, SVP/ Japan Marketing & Sales, Nissan Motors, spoke at Advertising Week Asia in Tokyo about how Nissan is putting data and analytics at the heart of its growth strategy. (For more, including how the brand targeted a new generation of Chinese buyers, read Warc's exclusive report: Pairing boldness with science: How Nissan uses big data to increase sales.)
The company uses big data, analytics and marketing science to make better business decisions – from measuring the success of marketing initiatives, to determining pricing for various dealership locations, to evolving its brand for a new generation of car buyers.
One successful use of analytics has been examining trends at key sales locations, which helps inform decisions on locations of stores, pricing and potential marketing initiatives.
"We look at the population distribution and what kind of Nissan models are selling by region," Hoshino explained.
"If you have a dealer shop here, then what is the competitive landscape of that particular dealer's shop? Perhaps in a specific region a certain model is preferred.
"If sales are decreasing, then perhaps that dealer shop should be moved to some other area," she said.
Consumer insights generated by data analysis are also used in the design and production of Nissan's various automotive brands, a strategy that allows Nissan to evolve the brand to showcase new technologies while also building cars people want to buy.
Without a foundation of data science to provide intelligence, Hoshino argued, it is impossible to make a truly innovative decision that moves the brand forward.
"You can't just be bold, because your success rate will not increase. You have to couple boldness with science," she said.
"It has to be grounded in science, and it has to be a data set that will underline and support the big decisions you make."
Data sourced from Warc