Translating predictive marketing analytics through visualization

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Marketing analytics continues to explode with more data sources and fascinating predictive marketing approaches to solve important business problems, yet one challenge continues to bubble up. The ability to translate the technical math behind predictive analytics into easy-to-understand business language and visualization to help c-suite executives make data-driven decisions with confidence. Developing this business skill is highly valuable as leadership decisions will not be made with data-driven evidence without transparent understanding, and how one communicates to a senior executive within the C-Suite versus a departmental technical manager is very different.

This was the challenge I embarked to address at the 2015 &Then DMA conference in Boston, Massachusetts. Over the past few years, I have developed a personal frustration of attending various marketing conferences, and repeatedly observing high-level presentations about the potential of analytics. Even more challenging has been the recent trend of companies presenting magical (i.e. "easy-button") black-box marketing cloud solutions that address every imaginable analytical problem; in my opinion, high-quality advanced analytics has not reached a point of commoditization. There is a reason that the data scientist is the sexiest job of the 21st century, there are over 120 universities offering business analytic graduate degree programs, and U.S. President Obama appointed the first ever chief data scientist earlier this year . It is my personal belief that data driven marketing is on the rise, and will continue to provide competitive differentiation for organizations that invest in best practices and talent, as compared to others that select the short-cut approach.

When it comes to championing analytics within a marketing organization, part of the solution is to enable and perform effective marketing analysis that incorporates analytics across the spectrum - descriptive, diagnostic, predictive, and prescriptive. However, I strongly believe there are other important, and often, overlooked components that complement an analytic team's ability in becoming successful.

  • The ability to communicate and frame an analytics problem as it relates to a marketing challenge
  • The ability to explain the findings of the analytics process in sufficient detail (i.e. telling a story with data visualization) to ensure clear understanding
  • The ability to connect the dots between analysis, and empowering a downstream marketing process

As a principal solutions architect by day for SAS, and a professorial lecturer by night at The George Washington University, I take aim to raise awareness of these subjects to my clients and students. An individual's ability to communicate clearly, succinctly, and in the appropriate language vernacular when presenting analytical recommendations to the marketing organization is extremely important when focused on driving change with data-driven methods and visualization. My main intent is to prove that the days of leaving a business meeting where the CMO states “that was interesting, but maybe next year” are over.

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Did I succeed? You be the judge:

 

Let me know what you think in the comments section below. Lastly, if you would like to connect on social media, link with me on Twitter or LinkedIn.

 

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About Author

Suneel Grover

Principal Solutions Architect

Suneel Grover is a Principal Solutions Architect supporting Digital Intelligence, Marketing Analytics and Omni-Channel Marketing at SAS. By providing client-facing services for SAS in the areas of predictive analytics, digital analytics, visualization and data-driven integrated marketing, Grover provides technical consulting support in industry verticals such as media, entertainment, hospitality, communications, and sports. In addition to his role at SAS, Grover is an professorial lecturer at The George Washington University (GWU) in Washington DC, teaching in the Masters of Science in Business Analytics graduate program within the School of Business and Decision Science. Through this hybrid of activity, he provides thought leadership through white papers, featured speaker presentations, and program advisory services for entities such as the Direct Marketing Association (DMA), Interactive Advertising Bureau (IAB), Indiana University (IUSB), University of Missouri (UMSL), Radford University (RU-COBE), and New York University (NYU-SCPS). In addition to his contributions to industry and academia, Grover has a MBA in Marketing Research & Decision Science from The George Washington University (GWU) and a MS in Integrated Marketing Analytics from New York University (NYU).

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