This week’s roundup discusses why marketing analytics hasn’t lived up to its promise, how machine learning is impacting the role of data scientists, tips for better earned media reporting, and how to maintain GDPR-compliant machine learning programs.
by Carl F. Mela, T. Austin Finch Foundation Professor of Marketing at Duke University’s Fuqua School of Business and Executive Director at the Marketing Science Institute, and Christine Moorman, T. Austin Finch, Sr. Professor of Business Administration at Duke University’s Fuqua School of Business and the Editor-in-Chief designate of the Journal of Marketing, featured on Harvard Business Review
In light of the exponential growth in customer, competitor, and marketplace information, companies face an unprecedented opportunity to delight their customers by delivering the right products and services to the right people at the right time and the right format, location, devices, and channels. Realizing that potential, however, requires a proactive and strategic approach to marketing analytics. Companies need to invest in the right mix of data, systems, and people to realize these gains.
by Bernardo Lustosa, Partner, Co-Founder, and COO at ClearSale, featured on VentureBeat
In the early days of machine learning, hiring good statisticians was the key challenge for AI projects. Now, machine learning has evolved from its early focus on statistics to more emphasis on computation. As the process of building algorithms has become simpler and the applications for AI technology have grown, human resources professionals in AI face a new challenge. Not only are data scientists in short supply, but what makes a successful data scientist has changed.
by Chris Lynch, CMO at Cision, featured on MarTech Advisor
According to a survey by PR Week, nearly 70% of people who work in marketing communications don’t have enough data and analytics to properly attribute their earned media programs’ impact on financial and business results. When it comes to reporting up to the CMO or CEO, communications rely on vanity metrics such as overall mentions and share of voice to help make a case to top executives about the value of media coverage. However, marketing technology and best practices in communications are evolving, leaving you room to modernize your approach.
by Andrew Burt, Chief Privacy Officer and Legal Engineer at Immuta, featured on O’Reilly
Much has been made about the potential impact of the EU’s General Data Protection Regulation (GDPR) on data science programs. But there’s perhaps no more important—or uncertain—question than how the regulation will impact machine learning (ML), in particular. Given the recent advancements in ML, and given increasing investments in the field by global organizations, ML is fast becoming the future of enterprise data science.
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