“We have tools to provide fact based evidence through processes such as marketing mix modeling, conjoint analyses and simulated test market models. However, they are typically not integrated nor do they all reach the decision maker at the same time”
Marketing Science Unit director of a leading consumer good marketer, 2017
In this most wonderful time of the year, predictions abound. Over the last years, I had the pleasure of participating in an international and interdisciplinary think-tank on the Future of Market Research. The futuristic exercises are cool, as are the participants from social media industry leaders, machine learning and visualization professors to white hat hackers. There is much we disagree about, such as the value of Single Source data in market research (half of the participants hadn’t even heard about the concept) and whether the future will look more like Star Trek (the professors) or Star Wars (the hacker), with less or more conflict over resources.
Much to agree about we found as well. Allow me to synthesize them as the 3 As: Augmented Reality, Analytic Assistants and Artificial Customers. How will these AAAs evolve in 2018 ?
AUGMENTED REALITY: Based on the typical client complaint in the opening quote, much of my work has focused on merging online and offline information, mostly surveys, observation and online behavior (http://www.msi.org/reports/do-online-behavior-tracking-or-attitude-survey-metrics-drive-brand-sales-an/). At the consumer level, I have always been skeptical of virtual reality going mainstream. Why waste so much resources and computing power to realistically depict nature if nature is all around us? It is fun for spectacular games, but most consumers want to integrate their offline and online identities. Wearables allow consumers to be fully present in the offline reality and connecting with online information about their health and what their online friends or rivals are doing. We will see much more technologies allowing them to do so in the near future. This will give us market researchers fascinating data on how consumers react to online and offline stimuli. Single source data integrates consumer exposure to marketing stimuli with their online browsing and online + offline buying behavior, their product experience and its expression in complaints or word-of-mouth, and will be further augmented by this new data.
ANALYTIC ASSISTANTS: taking my concept of analytic dashboards into the future (https://analyticdashboards.wordpress.com/2014/01/30/what-is-an-analytic-dashboard-do-you-agree-it-needs-all-5-elements/), ‘always on’ analytic assistants will not only select among metrics and visualizations what they infer the decision maker WANTS them to show. They will also aim to get her out of her comfort zone by showing her what the analytics believes she NEEDS to know. In the typical ‘6 block’ paper presentation in use by top companies, one out of the six figures will be selected based on the likelihood it will lead the decision maker to explore and think deeper about threats and opportunities. Just as human market researchers had to evolve to consultants (giving specific and accountable recommendations instead of only collecting and presenting the best data), analytics assistants will evolve to better understand exactly what the decision maker needs and inspire her to action.
ARTIFICIAL CUSTOMERS: Artificial Intelligence does not only help managers, it also helps consumers, in the form of recommendation systems, smart vehicles, houses and one-push-buying buttons. While marketing and market research has focused forever on understanding and nudging human behavior, we now have to include marketing to artificial customers. Beyond teaching machines what to learn, we now also have to learn from machines how they are teaching human consumers that increasingly rely on their advice. Digital marketers have already done so for years, aiming to understand and influence search and social media feed algorithms. As analytic assistants become mainstream for key customers, we need to educate our students and clients on how to market to artificial intelligence. Easy it is not. But aim and practice we must.
What do you think? Which of these predictions will and won’t come true and when? Early next year, we will be evaluating how wrong I was in my response to the Princeton study claiming that Facebook would lose half of its users in the 2015-2017 time period. Happy holidays and a healthy and productive 2018 – May the Force be with You !