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Breaking the marketing mold with machine learning

 

 

Breaking the marketing mold with machine learning
Breaking the marketing mold with machine learning

Leading-edge marketing organizations are shifting both strategy and culture to prioritize data storage and application to produce actionable insights. Results from a recent survey conducted by MIT Technology Review Insights in association with Google showed that “leaders” (companies that have experienced significant growth in revenue or market share) are more likely than “laggard” organizations to leverage machine learning (ML) to help their marketers better understand customer intent. Armed with insight into customer behaviors, marketers can focus on those customers with high lifetime value, providing the personalized and relevant offers they seek.

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ML assists marketers in extracting intelligence from the enormous amounts of data their organizations generate daily, enabling certain customers to view the performance of specific marketing campaigns during specific time periods. ML is a powerful tool that uses empirical data to allow marketers to quickly respond to changing market conditions and customer needs by making informed decisions in real time.

According to the survey, professional services firms and retailers are ahead of the pack when it comes to understanding that predicting customer intent drives better marketing results, and that ML is an adept tool for capturing customer intent. Automotive and financial services are among the other industries where marketers are using ML and analytics to better identify high-value customers.

Analytics and ML can change not just how the marketing function uses data to optimize its messages and anticipate the needs of high-value customers, the survey concludes—it can elevate the definition of the marketing role in the organization.

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This article was written by cool news network.

 

 

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