The Future of Marketing – and Next Generation Social Science: a Visit to the Center for Advanced Modeling
The Future of Marketing – and Next Generation Social Science: a Visit to the Center for Advanced Modeling
Chris Meyer is a thought leader focusing on the information economy, globalization and business innovation. His latest book is "Standing on the Sun".
Got Nerve
Got Nerve
Chris's mission is to anticipate and shape the future of business. He has pursued this goal as an entrepreneur, executive, consultant, author, and the leader of a think tank. Based on the ideas in his 2002 book Future Wealth, Chris developed a plan for a business based on a network of thought leaders. He joined The Monitor Group in 2006 to develop this idea as Monitor Networks, where he was Chief Executive from 2004 to 2009. In 2006, he co-founded Monitor Talent, to take these ideas forward operationally. Prior to joining Monitor Group, he was the Director of the Center for Business Innovation at Cap Gemini Ernst & Young, from 1995 until its closing in December 2002. The Center fostered the conversation of leading issues among the business community, developed public conferences,…...
Read more2009: “SOCIAL FUSION”
Five years ago, as part of Monitor Talent’s annual gathering of thought leaders, we gathered a set of marketing and social media experts to discuss a hypothesis about how current trends would affect marketing.
Our group included thought leaders and entrepreneurs like Clay Shirky (author of Here Comes Everybody), Deb Roy (founder of Bluefin Labs), Charlene Li (Founder of Ray Wang’s former firm, Altimeter and author of Groundswell), and Marc Mathieu, now SVP of Marketing at Unilever. Practitioners from companies including Intel, Nestle, Cisco, Samsung, and Silicon Valley Bank participated as well.
We met to explore a vision of the future that we labeled “Social Fusion.” The term derived from the then-new explosion of social media and the growing capabilities for “data fusion,” the integration of multiple data sets to create a picture of an individual. Now we call that “Big Data.”
We began with a five-step argument (see chart below):
- Consumers had begun to continually describe their own behavior in media observable to marketers.
- Additional information about them was being ubiquitously through their clickstreams, cellphones and credit cards (now we can add FitBits and Nests), and the technology to fuse these data was developing quickly. Together, these trends implied that robust characterizations of large numbers of consumers would become inexpensive, and would be continually updated.
- Advances in cognitive science were providing insights into how the mind makes the choices it does, and
- Behavioral scientists (including behavioral economists) were able to test these insights experimentally. Because of trends #1 and #2, the hypotheses could be tested beyond experimental settings like FMRI machines (cognitive scientists) and rooms full of starving students (behavioral economists).
- Finally, through the use of agent-based modeling, it was becoming possible to simulate the interaction of heterogeneous individuals in the real world to validate these hypotheses—and test marketing programs.
In other words, in 2009 we could foresee the development of true behavioral science, with data gathered from real life leading to testable hypotheses, supporting models that can be used to assess campaigns and guide experimentation in the marketplace.
We came up with some interesting thoughts (e.g. using online video for ethnography) and anticipated how marketing organizations would integrate social-media-based relationships and real-time customer interaction with the older elements of the marketing mix.
At the time, we agreed that the embodiment of behavioral and cognitive findings into simulation models was the frontier, years away—hence the dotted line around the “Agent Based Modeling” circle above.
2014: THE CENTER FOR ADVANCED MODELING
Last week I visited Josh Epstein, founder of Johns Hopkins Center for Advanced Modeling and IMO the most important practitioner of ABM today. Josh has just published Agent_Zero: Toward Neurological Foundations for Generative Social Science.
In it, Epstein demonstrates that the 2009 prophecy has been fulfilled. He is building neurologically validated models of behavior into his agent-based simulations.To explain, one paragraph about ABM: the statistical models of, say, econometrics are “data-reduction” models—they throw away information about individuals and model the average. For example, a model of the growth of personal income as a function of growth of GDP and change in interest rates treats everyone as exactly average—and does not allow for interaction among the decision makers (“agents”).
As our #1 and #2 premises state, the wealth of data and computing power now available support modeling choices at the level of unique individuals. For example, Humana was puzzled that more employees didn’t choose the health plan best suited to their age and family structure. They observed the choices, interviewed the choosers, and found that people often gave great weight to the choice their colleague in the next cube made, even though he might be in a different situation. With this understanding, they built an ABM that more accurately predicted actual choices—and figured out how to educate people to make better ones.
Beyond the Wikipedia article cited above, there’s a good primer on ABM here, or you might consider my HBR article withEric Bonabeau (who did the Humana work) called Swarm: A Whole New Way To Think About Management, though it’s from 2001.
What Epstein has done is create a system for ABM that allows you—marketer, HR manager, policy maker, researcher, social engineer—to incorporate neurological findings about how people’s reactions are conditioned. Specifically, he’s incorporated the Rascorla-Wagner model of conditioning, “one of the most influential models of learning” according to Wikipedia. This conditioning changes the tendency of an agent to make a choice. For example, an investor may be tolerant to daily movements of 2% in the DJIA, but each time she loses that amount she becomes a little more fearful of a repeat. At some point, a 2% change could trigger her selloff, and other agents’ behavior might be affected. This model could predict the unpredictable—the conditions that would signal a market turn. Epstein has applied these techniques to social violence, vaccination strategies, the collapse of the Anasazi civilization, and many other social behaviors.
A current application: In 2013, the EU established CRISIS, the Complexity Research Initiative for Systemic Instabilities to develop “a new approach to economic modeling and understanding risks and instabilities in the global economy and financial system. At the heart of this innovation is the idea that the agents within the groups used in traditional models—households, firms, banks and policymakers—behave differently…based on their own characteristics…not always rationally.”
Agent_Zero is an academic-level book, but soon the quants in various fields will assimilate these ideas, and the practices of marketing, social policy formation, politics, and our understanding of how we influence each other in daily life will take giant steps forward.
And, incidentally, Social Fusion will become a reality. – CAM
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