Leverage Data Science and Machine Learning to Optimize the Marketing Mix
Digital marketing software Cake announced several enhancements focused on tracking, algorithmic attribution and marketing campaign optimization, providing users with better tools to measure the impact and return each media channel and campaign has on their advertising spend.
Users of the SaaS-based platform will be able to understand the impact of digital marketing campaigns across multiple touchpoints and channels (including search, social, display, affiliate, video and more) and target prospects and users based on channel and traffic source, as well as geography, device, operating systems, language and other custom rules.
Those using the system will also seem some enhancements to the platform's attribution (including the addition of rules-driven models including first- and last-touch, linear, time decay and custom modes) and optimization features (such as the ability to identify top performers with data comparison and visualization across marketing channels).
"CAKE strives to empower marketers with a deep understanding about the performance of their advertising choices and the ability to immediately act upon these insights," said Dave Stewart, Chief Technology Officer of CAKE by Accelerize. "We've built an industry-leading technology that not only gathers granular information about the customer path to conversion, but also leverages data science and machine learning to optimize the marketing mix and automatically understand how to shift spend to maximize ROAS."