Understanding and working with self-reported behavior

Editor’s note: Alicia Cleary is the vice president of marketing and industry relations at VideoMining. This is an edited version of an article that originally appeared under the title “The Problem with Self-Reported Behavior.” 

All marketers dream of being a fly on the wall during their customer’s path to purchase journey. 

The story goes that the closer you can get to your customer – to understanding their hopes, dreams, preferences, motivators and so on – the closer you will get to building informed marketing strategies that are destined for greatness.

To gain deeper insights in market research, qualitative studies are often employed. These studies involve methods such as focus groups and in-depth interviews, which allow for open-ended questions and valuable feedback. However, it's important to note that the information gathered from qualitative research is, frankly, subjective and based on feelings, perceptions and impressions rather than objective, evidence-based data. 

The dangers within qualitative research

While these methods can offer significant context for marketers seeking to better understand the consumer mind-set, it's important to acknowledge that it may also introduce bias and lead to dangerous blind spots in the insights if not properly considered.

While focus groups and surveys can provide valuable insights, they should not be the sole source of information when it comes to understanding consumer behavior. Behavioral scientists have found that people often make decisions unconsciously and based on emotions, which they are, practically speaking, not able to articulate or recall with accuracy. So, we might think we know why we made certain buying decisions, but truthfully, there are missing pieces of human recollection. 

Why survey results are not always 100% accurate

One leading behavioral scientist, Susan Weinschenk (2019) explains it like this: “Research shows that most of our decisions – big or small – are made unconsciously and involve emotion.” Since most decisions are made unconsciously, it stands to reason that, despite their best efforts, respondents of qualitative research can’t provide us with the big picture – because they themselves cannot see it.

This blank space triggers an autonomy bias response – considered one of the most powerful motivators of human behavior. Autonomy bias is the brain’s innate desire to control oneself and one's environment by acting with a certain level of independence. Behavioral scientists have found that once this level of agency, or independent decision making, is achieved, people are happier, less stressed and more satisfied. 

So, when asked to explain why we do certain things, the brain eliminates the blank space, manufacturing a reason that logically explains the actions. Have you ever found your misplaced keys and told yourself that you put them there for a specific reason? This is an example of the brain filling in the gaps to fit into your narrative and give the continued assurance of agency. 

This might sound like awful news for marketers who rely heavily on qualitative research, but believe me, it is not. It is through knowing the science of behavior, and how and why we do what we do, that you can seek out information to contextualize your decisions and illuminate your blind spots.

So, now what? Well, if you are concerned with getting closer to understanding the true behavior of your shopper, you should look to observational research to close the gap.

How implementing observational research can help self-reported behaviors

Observational research allows you to observe without interfering, thereby giving you the most authentic behavioral responses and the most bulletproof analysis of in-store performance. Observational research can be conducted in one of three ways. 

The first is online tracking. Online tracking can be a powerful tool for building an understanding of online user behavior – how they shop, how they browse, what categories and interests they engage with, and so on. This technique is powerful, but when it comes to observing physical in-store behavior, irrelevant.

The second way observational research is conducted is through human observation. While productive, in theory, the limitations of human beings as the primary gatherer of data limits it from producing any kind of meaningful results at scale. The third technique involves employing the power of AI technology to build an expansive behavioral understanding. If you are looking for authentic and indisputable shopper behavioral data, observational research powered by AI technology may be a good choice.