Marketing thinking, fast and slow
Through a special arrangement, presented here for discussion is an excerpt of a current article from the Joel Rubinson on Marketing Research Consulting blog.
In his best-seller, "Thinking, Fast and Slow," Daniel Kahneman tells us that humans have two decision making systems. The fast system one is automated, semi-conscious and occurs frequently throughout the day. The slow system is highly cognitive and computationally intensive. It requires lots of energy, so we use it sparingly.
Marketing used to be a slow decision business. When I first joined Unilever in the late seventies, market shares were reported bi-monthly by Nielsen. Marketing plans were set for the year and advertising was scheduled well in advance. There simply were not a lot of decisions to be made and not a lot of data to base them on. In fact, the whole world was slower. News came at us only once or twice per day. We shopped only when stores were open and watched TV when the show was scheduled. Most "female heads of house" were not working. Life was synchronized, and that made marketing easier to understand.
Today, the cadence of life is different, driven by technology. Marketing has become a fast, daily decision business. Torrents of data feed marketing decisions being made each minute, by trading desks rather than people, in the form of programmatic advertising and real time bidding for an impression opportunity in the two-tenths of a second it takes a webpage to load. Programmatic media buying is a lot like system one — and it is a big deal. For example, Kellogg’s shared that it spends about one fourth of all above the line marketing funds via programmatic buying.
Despite all of this change — from slow decision-making, to fast decision making based on automation, algorithms, and data — most marketing research teams are still operating as if it’s a slow world. We might be conducting research in faster ways, but we still conduct a survey, pick at the data like buzzards, and develop insights on a project schedule that stimulate thinking but have no direct connection to decision making.
Consider tools that guide our marketing investments, like brand tracking and marketing mix modeling. Trackers aren’t fast enough to help campaigns in flight, and they are a backhand form of strategy research that doesn’t provide as much value as it should because it is on a reporting schedule and survey time limitation. Marketing mix modeling informs media strategy, but it does so as a report card on the past so it can’t be used to move money around — it is a system two solution for a system one need. It also doesn’t help with burning issues, such as how to rework plans around content marketing, native advertising, cross-media and cross screen optimization.
Is marketing and research becoming more of a system-one (fast) versus a system-two (slow) process? What are the challenges of moving beyond slowly-derived insights to prediction through digital data?