BrainTrust Query: Breaking the Concept Testing Habit
Through a special arrangement, presented here for discussion is an excerpt from a current article from the Joel Rubinson on Marketing Research blog.
Much of consumer and shopping behavior is based on habits and rituals. Think about what you do when you wake up in the morning. Â If you’re like me, you’re on auto-pilot for the first 30 minutes. Bathroom, bathrobe, brew coffee … brain not engaged … must have coffee! Yet, each of you reading this has different morning rituals and, collectively, we see that our options for waking up in the morning are really unlimited.
The difference between unlimited options and routine behavior is habit. The degree to which we are governed by habits varies.
As you shop in a grocery store for example, you probably have a habitual way you navigate the store. For certain product categories, you don’t even think about choice; you simply look for the brand you intend to buy. In some categories, you behave differently because you ARE making choices. Being on autopilot for certain product categories lets you conserve your mental glucose for when you really need it … when you have chosen to actively consider alternatives.
Now, consider how most concept testing and choice experiments work. We throw all of that insight about habit out the window. We put people into choice and decision-making mode whether they are ever there in real life or not. We force people to tell us if they are interested in a particular new product idea without measuring if they are interested in any new product idea at all for a given situation. Yet, the key for new product adoption is disruption of existing habits and rituals.
We need to break the concept testing habit and start researching new product adoption in ways that are closer to how people really decide.
Behavioral economists like Dan Ariely understand this. They understand that people have heuristics, "little tricks", that allow them to decide in non-fully compensatory ways … basically, the reality is exactly the opposite from how choice experiments and traditional concept testing work.
Traditional concept testing does not study how people decide, it merely gets at purchase interest IF they were deciding. Usually less than half of those who say "definitely would buy" ever buy for this reason; we are forcing people into active decision-making mode when many are not there in real life. This unnatural situation is what creates such poor individual-level predictive validity for purchase intent.
First and foremost, a new product must disrupt existing behaviors or leverage behaviors that are already disrupted to be "seen" by the consumer.
In real life, disruption is all around us in an age where digital technology is producing bone-rattling change in everyday life. Imagine location-aware offers, brand stories, and payment all converging at point of purchase via your smartphone. This is already happening in parts of Asia. As touchpoints emerge (weekly it seems), marketing and research approaches need to constantly evolve.
We need to start studying how people decide and how to break habits. Maybe, CPG can do better than the 80 percent new product failure rate?
Discussion Questions
Discussion Questions: What promise do digital technologies such as smartphones hold for improving new product trial rates and understanding the shopper decision-making process? Will smartphone shopping ultimately prove to be a better tool to improve new product launch success?
Joel is right on (as he usually is). There are a number of meta-studies showing the poor relationship between purchase intent and actual performance. While the modelers have been able to factor much of this into their equations, accounting for overstatement of interest, the failure rate of new products suggests that a new methodology is required. There is also a large volume of psychological research (attribution theory) showing that behavior is different when you force a choice than when it occurs naturally.
Digital technology is irrelevant to much of this discussion (IMHO). Shoppers are not looking up toilet paper information on their smartphones, nor do I imagine many reading Charmin or Cottonelle ads in social media. As Joel points out, we save our brain power for things that matter–choosing your toilet paper is not one of those things.
We’ve had a lot of success with unobtrusive data gathering (via Virtual Reality), but that is not the only way to gather information in a more natural way. And that is what is needed–methodologies that tap into how people really behave.
Joel, I couldn’t agree with you more. I have been and still am a proponent of “context” when it comes to research of any sort. Providing a framework that simulates the visual environment of the shopping experience generates a platform for research success and well informed business decisions.
However, many marketers enjoy hiding behind the screen of “norms” so they test as they tested before and then they can compare their results and back into that 80% failure rate. Sometimes it takes courage to use what is a “new” research approach for the company, even if the “new” is incredibly proven and for some traditional.
I’ve worked with eye tracking over 30 years and my research has shown how typical concept tests depend on reading a complete description, but respondents don’t, and perhaps seeing a picture of the product (packaged as it won’t be in the marketplace). These are but two factors that fly in the face of accurate predictions. Now add the lack of any appropriate consumer context–the shelf, internet page, the mobile phone screen–and the inability to accurately forecast has been compounded.
Joel, is anybody listening?
Behavioral consumer research is more accurate when it can be observed and tested at the points of purchase.
I have been working on a project that utilizes smartphones and other hand-held devices in-store to promote products while a customer shops. Like anything new, the solution’s ultimate value is still being distilled. What we do know is that a customer being contacted about a $1.00 coupon while they are in front of the bag of new flavor of potato chips causes a reaction. The question then becomes how do you follow up that reaction to create a new repetitive behavior? Do you have another coupon in the bag so the customer goes back to buy another bag? Maybe you also deliver a Catalina coupon for another $1 off when they purchase the item. The answer is still yet to be determined, but what I will say is like any other promotional vehicle, smartphone marketing should be part of an overall campaign that incorporates several approaches (Catalina, FSIs, shelf coupon machines, circulars and displays). On its own, you are only grabbing 20% at most of the value it truly has to offer.
Joel–great topic and insight. In my work I have come across very much related phenomena–and if I may give you a quick peek into it–I would quibble with the emphasis on existing behavior. New Products (or any products for that matter) have to focus on fulfilling “jobs to be done” and NEW BEHAVIOR. So, studying existing behavior or asking a shopper what they may or might do when confronted with the options assumes or overlooks very important parts of that decision-making process. Right on in pointing that out!
What a wonderful topic Joel and Dan Ariely’s work is the perfect reference point. The truth is that when we ASK people what they would do, they often respond with completely rational and logical responses. However, when we simply observe what they actually DO in exactly the same situation, their behavior is often entirely irrational.
Mobile technology, NFC, heatmapping, facial recognition, etc., will allow us to first answer the WHAT about consumer behavior and then work backwards to the WHY–if in fact the consumer even knows why they behaved in a certain way. But as Joel points out so brilliantly, what we get now is often just a bunch of cognitive nonsense that ends up being meaningless once the product fails!
I packaged some of these thoughts up in the article "Death of the Focus Group: Research Meets Mobility."
Joel (and others), if you haven’t already, I encourage you to read “Habit: The 95% of Behavior Marketers Ignore”by Dr. Neale Martin. The insights into the pernicious impact of the unconscious mind on our marketing efforts are relevant to the discussion at hand. Neale and I have been working for several years now on what we call ‘habit-based marketing’ strategies for our CPG, Healthcare, and Telecom clients. At its heart, all marketing is about one of three things–creating a new habit, disrupting an existing habit, or maintaining a current habit. Unfortunately, all sectors of marketing, from product development to social media, do not recognize the power of the unconscious mind and its overwhelming influence on consumer behavior. It’s far easier to appeal to the ‘rational’ conscious mind, and all our own business habits tell us its the right thing to do.
A smartphone is a great technological resource in store because so many consumers already habitually bring theirs wherever they go. One application (ignoring privacy debates for a moment) could be to use the phones to understand how quickly the shoppers move from aisle to aisle–the shorter the amount of the time at a purchase decision, the more habitual that purchase probably is. You could use this information to find which products are more consciously considered, and thus easier to disrupt.
But product developers need to also understand why it is so hard to get consumers to buy their new products. Habits form in context, are in response to cues, and are strengthened through reinforcement. Is there a context for the product, and how does it fit into the consumer’s day? What should trigger its use? Instead of just offering a coupon to induce a behavior (a bribe), how are you reinforcing the purchase behavior afterwards to encourage another trial? The disconnect between what the conscious mind thinks it knows and how the brain actually makes decisions is where so many of these failed new products went wrong.
One of things we have been doing with Kroger for some time now is a “pre-launch” trial in some of their stores that we run as a behavior lab. By looking at the shopper data we can understand customer engagement with these products in a real environment and help assess which launches are going to work with which customer groups.
There’s a lot more to it than this (I’m probably not doing it justice) to ensure it is as representative as possible, and allows other aspects of product launches to be tested. It has certainly proved to be useful in enabling better decisions by CPGs and Kroger on new product launches.
These kinds of tests and then early read repurchase rates from shopper data can help make better new launch choices (e.g. for marketing, distribution, promotion and whether or not to pull it).
However, connecting behavior data throughout the innovation chain is still way under-utilized. It can be really powerful in identifying or validating and quantifying opportunities and is much more effective for gaining accurate and consistent research as you can target research groups based upon known behaviors instead of claims.
Clearly lots of opportunity to do better in this space…great article!
There is a webinar on this topic that Joel hosted with Dave Lundahl that was very informative and shows the necessity of disruption in order for new products to have success. Disruption, the breaking from the habitual actions, is not possible without creating an emotional impact. By understanding more about emotions and the emotions frameworks by which market researchers can mine them, we can better understand the catalyst for product success, born from behavior driven innovation.