Nissan achieves 43% media savings for new car model promotion
Learn how the global car manufacturer improved the targeting of its acquisition campaigns and created the conditions for higher conversion rates onsite.
increase in conversions
in media savings
Nissan is a global car manufacturer that sells a full line of vehicles under the Nissan, INFINITI and Datsun brands. One of the top 10 largest car manufacturers in the world and a leading manufacturer of electric vehicles, Nissan aims to make cars that are more efficient, more beautiful, more inspiring and more human than ever before.
ENHANCING THE DIGITAL EXPERIENCE TO PROMOTE THE LAUNCH OF A NEW CAR MODEL
Staying one step ahead means creating new digital services at speed that meet customer expectations for ‘always on’ engagement. The next step is to target the right customers who will engage with them, increasing conversion and ROI.
In Nissan’s case, the company wanted to transform how its niche target audience engages with its new car model, Juke, via a car configuration module online. It aimed to do this by launching a paid acquisition strategy that identified relevant audiences to engage with the module and steered them towards the website.
LEVERAGE THIRD PARTY DATA SEGMENTS WITH ID-VERIFIED AUDIENCES
Nissan partnered with Zeotap in order to tap into accurate third party Enterprise Data with ID-verified audiences, enabling the company to engage with the right customers without unnecessary increases in budget or irrelevant customer targeting.
By creating segments of customers based on verified data, Nissan was able to improve the targeting of its acquisition campaigns and create the conditions for higher conversion rates.
REFINED AUDIENCE TARGETING THAT DRIVES MORE (OF THE RIGHT) CUSTOMERS ONSITE
Zeotap provided third-party audiences that suited what Nissan was looking for, with unmatched precision and scale. This resulted in a 107% increase in conversion due to customers configuring cars online, and a 43% in media savings compared to campaigns built with probabilistic data.
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