Tell us about your role and the team/technology you handle at Anexinet.
I am the Director of Advanced Analytics at Anexinet. I help clients devise strategies to ensure the success of their machine learning and analytics initiatives. Our team takes advantage of many technologies to enable clients to best solve complex and varied analytics problems. I am also product owner of our ListenLogic Platform, which uses natural language processing and machine learning to analyze customer experiences.
Why are B2B marketing teams steadily moving toward Applied Data Science for Sales and Marketing initiatives?
Data science is revolutionizing analytics initiatives across all departments. Sales and marketing teams use machine learning and data science to create and adapt campaigns faster than ever before, and apply predictive analytics to answer questions previously based on a hunch. One specific example is the use of supervised and continuous learning for lead scoring. Previous lead-scoring techniques were either manual or based on limited fields/datasets marketers believed had a large impact on conversion. Machine learning allows marketers to utilize much broader datasets and automatically identifies critical buying signals, based on common attributes of historical leads that converted. Further, these models continuously learn and improve, resulting in much greater score accuracy overall.
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