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Brilliance@Work: Data Storytelling Expert Earl Taylor

Photo: James Lee, Chester, NH, USA

Photo: James Lee, Chester, NH, USA

Welcome to Brilliance@Work, a series of profiles about stellar collaboration professionals and their best practices at work. Throughout May, we’ll feature Marketing Analytics & Data Science experts.

Earl Taylor is Chief Marketing Officer for the Marketing Science Institute (MSI) in Cambridge, Massachusetts. Founded in 1961, MSI is a nonprofit, membership-based organization dedicated to bridging the gap between academic marketing theory and business practice.

Earl Taylor

Earl Taylor

Read on to learn how Earl and MSI use quantitative and qualitative data to help their members stay on the forefront of marketing thought and practice.

Peggy L. Bieniek, ABC: How does MSI help to shape the future of marketing science?
Earl Taylor: MSI’s corporate sponsors represent a cross-section of the U.S. business community. We continuously solicit input from our trustees and others who represent our corporate members about their most pressing marketing challenges.

Every two years, we ask our corporate trustees and leading marketing academics to prioritize these topics to guide our funding of academic research and the focus of our events. Results are summarized in our recently released 2016-2018 Research Priorities, which can be viewed and downloaded free from our website at http://www.msi.org/research/2016-2018-research-priorities//.

PB: How do you use big data to measure brand performance?
ET: Marketing academics and MSI corporate sponsors are using big data in a variety of ways to assess marketing effectiveness and brand performance. Increasingly, datasets that link exposure to advertising and other marketing activities with outcomes such as sales and profitability allows managers to determine the exact effects of each element of the overall marketing mix and to allocate resources more efficiently and effectively.

Academic research supported by MSI has demonstrated that properly interpreted and weighted data from social media can be closely correlated with traditional brand health tracking metrics. In fact, social media can yield leading indicators of brand health, allowing managers to anticipate and respond to emerging trends (positive or negative).

MSI helped found and continues to support the Marketing Accountability Standards Board (www.themasb.org), which is dedicated to vetting and promoting metrics agreed to by both marketing and finance that can reliably demonstrate the value created by marketing and branding.

PB: How can data and analytics help tell a marketing story?
ET: Most traditional quantitative market research relies on theories of consumer behavior that yield hypotheses that can be tested against empirical findings. The advantage of this approach is that results can be incorporated into a coherent framework for interpretation and application, yielding a cumulative body of knowledge over time.

With the advent of big data analytics using machine learning and other techniques, we can now efficiently discover patterns in data that we might not otherwise have noticed, but which can be interpreted theoretically and applied, thus advancing marketing science and practice.

Regardless of how they are obtained, insights are best shared the way humans have always communicated— through stories, personas and the like that allow managers to understand, assimilate and extrapolate from them as new situations arise.

PB: What will people gain from attending your conference presentation?
ET: When data does not readily fit existing quantitative formats and analytics, it is often referred to as “unstructured.” In fact, datasets taken from social media, online review sites and the like are highly structured! Whether in real-time or asynchronously, exchanges in social media are variants of the structures that inform ordinary conversation where sequencing and context largely determine what a given contribution means to others engaged in the dialogue.

While certain insights can be derived from techniques that extract words or phrases and re-assemble them as word clouds, in many cases preserving sequential structure is critical to understanding what consumers are saying and why.

Drawing on sociological research, I will make the case that conversational analysis offers a distinct alternative to purely inductive big data analyses of social media. Importantly, findings on how information is conveyed in stories, jokes and other forms of ordinary conversation can also help us better communicate insights from all forms of quantitative and qualitative analyses.

Want to hear more from Earl Taylor? Join us at the Marketing Analytics & Data Science Conference on June 8-10, 2016 in San Francisco, California, as he presents “What’s the Story with Big Data?” #MADSCONF


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Brilliance@Work: R&D Informatics Expert Laura Aguiar

Photo: James Lee, Chester, NH, USA

Photo: James Lee, Chester, NH, USA

Welcome to Brilliance@Work, a series of profiles about stellar collaboration professionals and their best practices at work.

Laura Aguiar, Ph.D., MBA, MPM, PMP, is the Data Science Decision Support Service Manager for Roche Pharmaceutical Research and Early Development Informatics at the Roche Innovation Center in New York.

Laura Aguiar

Laura Aguiar

Throughout May, Brilliance@Work will feature Marketing Analytics & Data Science experts. Read on to learn how Laura and her data science team support R&D informatics innovation at Roche.

Peggy L. Bieniek, ABC: How does Roche use data to help shape the future of healthcare?
Laura Aguiar: Various types of data are used. For example, market research data is used for constructing/optimizing business strategy, by understanding the physicians’ needs and their expectations for specific disease indication. Genetics and genomics data is used for identifying and assessing biomarkers (predictive drug response biomarkers, drug safety biomarkers, etc.). Real world data (insurance claim data, Electronic Healthcare Record [EHR] data) is starting to be used for optimizing clinical trial study protocols (by understanding disease populations), patient recruitment, etc.

PB: How does R&D informatics support collaboration?
LA: R&D informatics can support collaboration on many levels. It can provide user-friendly collaboration platforms that makes it easier to store and share relevant information in unstructured (file share) and structured databases (for scientific data from collaboration). The R&D informaticians also provide a bridge between collaborators (usually scientists) and Roche, particularly for data and information sharing.

PB: How are big data and data science impacting R&D currently?
LA: We are making use of big data, like Next Generation Sequencing (NGS) data, to identify additional disease indications that certain drugs have the potential to cure (based on their mechanism of action and disease etiology fit) and to identify predictive drug response biomarkers. Using mixed data science capabilities, we combine different types of big data, like NGS, literature, and real world data to support pre-clinical and clinical project teams, scientists, and clinical operation experts.

PB: What will people gain from attending your conference presentation?
LA: People will get insight on the formation and value of a Data Science team in a Research Pharma organization. They will learn how it’s managed, the interface with stakeholders, value through drug project impacts, and employment of a cross-functional team in a global setting.

Want to hear more from Laura Aguiar? Join us at the Marketing Analytics & Data Science Conference on June 8-10, 2016 in San Francisco, California, as she presents “Data Science in Early R&D Informatics.” #MADSCONF


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Learning Opportunities are Blooming in Marketing Analytics & Data Science

Paper Flowers“All the flowers of all the tomorrows are in the seeds of today.” – Indian proverb

Advances in technology continue to shape our future. What we learn and do today will help us succeed tomorrow.

Join me June 8-10, 2016 for IIR USA’s Marketing Analytics & Data Science Conference (MADS) in San Francisco, California. Together we’ll learn how to deploy marketing analytics and data science to drive our businesses and organizations forward.

Here’s a peek at a few of the presentations and speakers on the agenda:

  • “Marketing in a Hyper Connected World” by Theo Priestley, Technology & Digital Evangelist and Forbes Contributor
  • “Industrial Internet: Building the Digital Industrial World with Data Science” by Beena Ammanath, Executive Director, Data Science, GE
  • “Foreseeing the Next Big Innovations and Marketplace Risks” by Alec Ross, Author, The Industries of the Future, New York Times Best Seller
  • “Customer Valuation: The Time is Now!” by Peter Fader, Professor of Marketing, Co-Director of the Wharton Customer Analytics Initiative

As a guest contributor to The Market Research Blog, I’ve created these MADS conference stories that will help you gain insights from experts across industries:

Register today for MADS to learn, network and share best practices with the most influential leaders in data science and analytics. Stay connected at #MADSCONF.

In the meantime, watch for my MADS presenter profiles and conference posts on LinkedIn, Twitter, Google+ and Starry Blue Brilliance.

Looking forward to attending this event with you!