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.
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?
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17 Comments on "Marketing thinking, fast and slow"
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Even fast digital data will be less than optimally effective in marketing unless the industry begins to measure what matters. And that’s the system one decision making drivers, they are fast, but are mainly emotional and subconscious. Measuring decision triggers is hard given that the subconscious mind has no “voice box” and renders survey research virtually useless, no matter how fast it gets done. People simply cannot give the “real answer” to why they chose brand A over B, so they make up something to put on the survey.
So as marketers, we have to choose to make our measurement work harder and more expensive if we desire more effectiveness from it. The shift in this direction is slow but steady. But the application of real knowledge can be immediate.
Joel might be stretching the analogy here and using fast and slow thinking to describe agile marketing in a way I don’t agree with (sorry Joel). Marketing should never move away from slower, deliberate thinking about what the data means for their business. That said, they may have to do it faster, and research may need to keep up with the faster speed of operation in those businesses that have the ability to react quickly.
Marketing and research needs to become a system one process—but there is a huge number of steps in the way. Manufacturers and retailers collect data from so many different sources and then have to spend a significant amount of time cleaning and compiling that data before they can begin to analyze and identify insight. On top of that, the people with the highly in-demand skill of being able to read complex data are rarely also skilled at presenting that data in a way that makes sense to the every day business user, so it takes them time to attempt to organize their ideas into an easily understandable and shareable format. With today’s system-one culture, organizations that haven’t found a way to automate this process will be left behind.
I hope I will be forgiven for a quick shameless plug—but this is precisely the situation that Interactive Edge and XP3 has been solving for years now. I would be happy to discuss our solution further with anyone who is interested.
I would have to read Daniel’s book to truly know if I would totally agree or have some issues with his premise, but on the surface I concur that the process of marketing communication has sped up significantly as technology enables it to do so.
Brands are thinking more about “disruption” than instilling their brand’s attributes deliberately in the minds of consumers. Consumers are now exposed to multitudes of product images, attributes and benefits and because of their increased number of options, must filter and process this information much faster than in the past.
Certainly higher-ticket items continue to lend themselves to a slower, more deliberate communication and decision-making process. For everything else, programmatic buying is becoming the norm. That means new timelines, new methods and even new metrics must be embraced to effectively market through new media and technology.
Both slow and fast thinking are required. However, as Anne says, it is imperative that marketers clearly identify which data they need to make which decisions. Otherwise the massive amount of data leaves marketers chasing numbers and responding to everything. That is not a good situation. Even when using data that arrives quickly, it is being processed using algorithms that require slow thinking to develop. Trends, patterns and deviations need to be examined to create, edit and monitor those algorithms. The world is not an either/or situation. There are so many possibilities and so much data that it is essential to determine which data is valuable for which decisions before being inundated with data.
I loved Kahneman’s book and it is a great read. I think there’s a lot more to the fast and slow decision process. Behavioral economics and their masses would love nothing more than to distill these behaviors into all-telling statistics and models to help us sell more, buy more and use more.
But we’re still dealing with human beings here folks, and there’s still behaviors of feeling, thinking, good moods and bad moods that statistical models may not yet be able to comprehend. Then watch the Boomers and the Millennials in their quest for product (or service) and satisfaction.
If you don’t believe me, just spend time watching people shop. It’s amazing what you see in real life.
The question of prediction itself seems antiquated in an age of near instantaneous digital response. Prediction may be a remnant of inferior data, where assumptions were used to limit variables, creating an illusion of accuracy and control. The relevant question of interest is how best to influence behavior through content and access, in an age of near infinite communication channels.
One word: Infographics.
Market research, as well as many marketing systems, are still based on an annual planning cycle, evaluating the impact of slow-acting marketing vehicles on a slowly changing consumer population.
Those days are fundamentally over. Consumers are changing their perceptions and buying patterns over minutes, hours and days, not weeks and months, based on social media feedback, email marketing, remarketing and other near-time marketing programs.
The key for market research is to migrate from a backward-looking evaluation tool into a forward looking predictive tool based on historical behavior. Predictive modeling is the future of marketing, as marketers seek to anticipate the needs of their customers before the customers themselves. Market research must become part of that paradigm or risk being left behind.
The increased speed of analytics is only as useful as the reflex of the rest of the system to react and execute the changes. Faster is better only when the rest of the system can respond and make changes in real time. With digital media it is easier to adjust marketing message and mix in near real time, not so much for physical displays, in-store pricing etc. Make sure your investment in decision support is balanced with investment in execution.
It doesn’t matter—slow or fast—unless it is right. We have many tools at our disposal. And, there are new ones coming on the scene all of the time. The key is to measure what should be measured in the most effective way. Effective doesn’t always mean efficient (time and dollars). So, the CMO and CIO must work together to determine what must be measured and how to go about doing it. Then once the information is available, move into a phase that takes advantage of this information to benefit the marketing effort.
There is an ability now to derive predictive as well as prescriptive consumer insights that can be continuously remodeled throughout the planning, execution and post-event stages of promotions. Entire marketing plans can be developed by looking at the strategy of the merchant and drilling down to the tactics in a swift and effective manner that drives measurable results.
It is just fine to marry both of the processes described in the article in order to execute an agile plan. The only obstacles to successfully running these campaigns are the culture of the merchant (risk-taker vs. risk-adverse, etc.) and leveraging the tools available right now in the marketplace.
Marketing—like software development—is a mix of fast and slow. In the past, both areas were slow-slow. Today it is about knowing where you want to be, monitoring the progress, and executing while measuring the success along with the progress. Gaining mindshare in marketing takes consistency, timing, and focus. The speed element all depends on the market or segment you wish to own.
Software development is the same—the demands of the target markets change, either in large or small ways, and you must refine the final deliverable to cross the path with the right product at the right time. Then the software or app quickly becomes the norm in the market it was targeted at.