Building upon last week’s thoughts from PTG guest blogger and innovation expert, Pete Foley, we are pleased to share the second in a series of long form blogs where Pete explores psychology, behavioral and perceptual science and how it can be applied to consumer research. Today’s installment addresses the power of noninvasive research and the unconscious drivers of consumer behavior.
This is the second in a series of blogs where I explore how psychology, behavioral and perceptual science can be applied to consumer research. In the first blog I talked about the value of running research in real contexts, and of using noninvasive techniques to unearth unconscious drivers of consumer behavior. Today I’ll talk in more detail about how this can help us to better understand and leverage the cognitive and perceptual biases that often drive behavior, making research a more powerful iterative and prototyping partner for innovation and design.
Recording what people do is of course an important part of research. However, as I mentioned in my last blog, if we want our research to be an integral part of optimizing product, package or communication design, then we need to dig deeper, and understand the mechanisms behind those decisions. That means exploring the cognitive and perceptual biases and heuristics that often drive actions and decisions. By combining knowledge of these with noninvasive techniques that measure both nonconscious and conscious behavior, we can help to design communication, products and services that better resonate with how people really make decisions.
Mixed Conscious-Unconscious Decisions: Most human behavior is driven by a mixture of conscious and unconscious mental processes. Take driving as an example. Many of us will probably at some time have experienced arriving home from our daily commute, only to remember very little detail about the journey. This realization is often a little surprising, even disturbing. However, our autopilot, or unconscious brain is actually quite capable of handling the complex, but routine task of driving a familiar route. It can direct where we look, and our actions, and in many cases does so more effectively than our conscious self. However, with driving, as with most tasks, our conscious and unconscious minds work together. Our unconscious, or autopilot, handles the routine stuff, with our conscious mind taking over when our habits, defaults and automatic responses can no longer handle a situation. In this case, autopilot can usually manage a familiar freeway drive, freeing us up to listen to the radio, or mull over an important meeting from earlier in the day. However, if something unusual happens, and provided we are not overly distracted with something like texting, autopilot will hand over control to our conscious mind as needed. For example, if someone pulls out in front of us, our unconscious will likely slam on the brakes, because it is faster to action, but then hand over to our frontal cortex to help deal with any consequences. If road work closes our normal route, or if it starts snowing, then we may get a similar handover, as autopilot does not have the experience to deal with atypical situations.
This interplay between fast, routine, largely unconscious mental processes, and more considered, slower, ones plays out in many human behaviors from playing sports to shopping. As I mentioned in my last blog, Daniel Kahneman in his Nobel Prize winning work on Behavioral Economics labeled them System 1 and 2 thinking in the context of human decisions. However, we also see similar effects in perception – where we look is often automatic, but we can also evoke manual override, and direct our vision as well.
Underestimating Automatic Decisions: An important insight for research that the driving analogy illustrates, but that applies to a wide variety of tasks is that we tend to underestimate how big the unconscious component of our thinking is, and often discount it. However, understanding the unconscious biases and heuristics that guide perception and decision can open up all sorts of opportunities to help people find what they need. In fact, this can be a more powerful tool than persuasion, as biases are often more consistent than more thoughtful preferences.
This is potentially powerful, but not simple. There are a lot of biases. I keep a list of over 200 cognitive, memory and perceptual biases, and that is far from comprehensive. One way to simplify is to recognize that some biases are more often relevant to retail than others. For example, “following the crowd” (herding in Behavioral Economics), “preferring familiar choices” (the mere exposure effect in psychology), and “choosing the middle of a choice distribution” (Compromise Effect) often drive time constrained decisions on the web or in the supermarket.
But the real world is messy, and in virtually every real situation, multiple biases and heuristics compete. To understand each unique situation, we therefore still need to run research. But the better we understand how these biases work, the better we know what to look for, what ‘questions’ to ask, and hence the better research we can design.
Retail Application: The same applies for perception and attention. Take a new product in retail as an example. If we want a shopper to notice and try something new, we first have to ‘snap’ them out of autopilot, which favors past habits and defaults. Understanding perceptual biases is key to creating the attention cues that will grab attention in this way. However, a common intuition is to think there is a fixed hierarchy of cues that we can tap into in order to do this. For example, we intuitively feel that our attention is drawn to things like movement, bright colors, or cues associated with sex or food. These are important, and all else being equal, we are primed to attend anything to do with threats to our survival, eating, or mating. But reality is more complex than this, and context plays a huge role. The cues that grab attention are those that are salient at that time, and that stand out against local background. For example:
1. Differentiated vs. Local Context: A bright, flashing light will catch our attention, but only if it is not surrounded by other bright flashing lights. We need to be differentiated versus the immediate surroundings. Add another flashing light to Times Square and it is probably not going to grab our attention.
2. Salient and Intuitive: If something isn’t salient to our goals, we may notice it, but will quite likely unconsciously deselect it. The same applies if it isn’t intuitive, especially in a time-constrained environment. Unless we have been primed to look for it, we may well notice, but then deselect or reject something that we don’t understand, before it even gets consciously considered.
Testing in realistic contexts and levels of engagement and distraction are key to measuring this bias. An environment that triggers unrealistic engagement in a visual search or decision is likely to overestimate the appeal of the new, novel, or unusual. This is why noninvasive research in realistic context is so important.
Mobile Cognition: In the case of bricks and mortar retail, we also need to account for mobile cognition. Real shoppers spend much of their time on the move. What we notice varies enormously as a function of distance, and the amount of attention we dedicate to a scene changes if we are moving, rather than standing still. We therefore need to build mobility and autonomy into our methods, and measure behavior at the distances where a shopper will naturally make decisions.
Leveraging the Shopping Cycle: This is made even more important because most retail decisions do not occur in a vacuum. Contextual effects such as goal, emotional state, degree of engagement, and surrounding visual and conceptual information all influence decisions, but so does time, and when a decision occurs in a shopping trip. Cognitive effects like priming and decision fatigue can strongly influence engagement, attention and ultimately, decisions. These effects change as we progress through a shopping trip, be it in a supermarket or on the web.
The Shopping Cycle and Decision Fatigue: For example, what we’ve already purchased can influence us in many ways. It may make us more likely to buy complimentary products. Or if a shopper is already close to their mental budget, and have depleted the ‘slack’ that is normally built into it for unexpected or forgotten items, they may be less likely to try new products, even if they notice them.
Another well known, and pertinent effect in psychology is called ‘Decision Fatigue’, or Ego Depletion. The energy we have available to make decisions is limited, and the more decisions we make, the less of that energy we have. The effects of this can be quite dramatic. A study of Israeli judges showed that they consistently gave parole to about 70% of people at the start of the day, but this rate drops to near zero towards the end of the day. Breaks for lunch or coffee briefly bumped it back up to 70%, but the trend was very much down as the day passed. In this case, the easier, or default decision is to not give parole, and so the more decisions they made as the day went on, the less likely they were to grant parole, as they fell back on the easier default of not granting parole.
Judges are professional decision makers, so imagine if decision fatigue has this kind of impact on them, how much it can impact our everyday lives. A shopping trip also involves many decisions, and so defaults are more likely to kick in towards the end of a shop. We see this play out with candy offered at checkout. The mental energy that we use to make decisions is the same as that used for self-control. We are therefore susceptible to grabbing a candy bar at checkout, even if we are not being cajoled by our children, because our self control has been depleted by all of the choices we’ve just made. And, this goes beyond just the checkout. For example, market-leading brands are often habitual or default choices, while buying a new, innovative, or growing brand typically requires more thought. For retailers and CPG manufacturers, where in the shopping cycle a category is placed can therefore be very important, with new products probably favored near the beginning, and big, established brands near the end.
Once again we can only effectively measure this if we keep context, engagement and autonomy in our tests. If shoppers know they are being tested, not only does it tend to make their decisions more considered and less automatic, this also increases the amount of energy that goes into them, in turn increasing decision fatigue. Forcing shoppers into an artificial context with too few decisions, asking them to follow what for them might be an unnatural route, or simply overtly observing them all change the amount of decision energy used.
It is always challenging to completely eliminate artifacts caused by the testing process. However, techniques like noninvasive eye tracking and biometrics can go a very long way towards helping us to avoid the act of testing influencing our results.
In my next blog I’ll talk about test designs that can compliment noninvasive measurements, how noninvasive techniques can help us design products and packages that invite us to handle them and take it off the shelf, and I’ll dig a little deeper into a concept I briefly mention here, selection and deselection.