![]() ![]() Locally, the company was instrumental in Royal Carribean’s split-funnel attribution model and new metrics to gauge its digital marketing and open up new customer insights. One of Quantcast’s primary areas of focus and education as digital advertising matures is around attribution. ![]() “It became a powerful tool to find the best audience for any given product or service.”īalancing retargeting with split-funnel attribution “With Quantcast Measure, we were collecting this great, proprietary first-party data set which is a window into commerce and culture and with Quantcast Advertise, we used that data to identify the people you were most likely to influence with your particular product,” Feldman explained. “But it didn’t make sense to me that regardless of who you were on the Internet, you would see the same ad, because from my perspective, you could use data to make all content far more relevant.”įollowing the launch of Quantcast, the team rolled out Quantcast Measure, which tracked customer behaviour online, followed by Quantcast Advertise in 2009, which focused on analysing customer’s product purchases via machine learning to discover any historical patterns in media consumption that could be used to prospect new customers. “Everyone in Silicon Valley at the time was talking about Internet advertising, but what they were really talking about was search,” he said. He co-founded Quantcast in 2006 after moving to San Francisco, after deciding he wanted to apply machine learning to Internet data. Programmatic, split-funnel attribution and retargeting are no longer martech buzzwords, they’re viable solutions for marketers wanting a more solid return on their investment, according to Quantcast’s CEO and co-founder, Konrad Feldman.įeldman has enjoyed a long-time fascination with machine learning starting his career in the UK. ![]() Quantcast's CEO and co-founder Konrad Feldman and ANZ managing director Andrew Double, speak with CMO about how marketers can leverage the latest martech offerings to gain deeper customer insights ![]()
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