The response to the blog articles I’ve been writing for several months has been quite gratifying.  Thanks for all the questions, comments and suggestions people have emailed, posted and texted.  One request that I’ve gotten repeatedly is for tools and techniques that can be used right now.   So, I’ve decided to write a few pieces about mindsets.  These are underused concepts that can take your understanding of marketing and consumer behavior issues to a much higher level.

So, let’s talk about maximizing and satisficing mindsets.  Herbert Simon, the Nobel Prize winning economist, introduced the concept of satisficing in 1956.  For those of you who think you’ve already caught two typos, not so!  ‘Satisficing’ is a word—it’s Simon’s concept of seeking an adequate, rather than optimal, outcome.  Technically, this is called the ‘theory of bounded rationality’ which questioned the then-accepted wisdom among economists (and still accepted today) that individuals always seek an optimal outcome. It points out that there is a significant cost to continued assessment and information gathering once one has identified a satisfactory solution.  The problem is that this cost is difficult to quantify.

If you want to see this in real life, go to an electronics store and watch people shop for TVs.  You’ll be able to distinguish very easily between those who seek the television with the very best picture quality vs. those who just want the cheapest set that’s good enough to watch Hogan’s Heroes reruns.  Simon theorized that people tend in general to be one or the other—maximizers or satisficers— in terms of their overall disposition.  However, keep in mind any particular decision-making challenge can influence one’s mindset.  For instance, a person seeking the very best TV may later visit a grocery store where he’ll buy store brand breakfast cereal because … “it’s good enough.”

Why should we care about this?  Because, in my experience, marketers tend to assume a maximizing mindset when trying to understand and describe consumer decision-making processes.  We take for granted that individuals seek to maximize quantifiable economic utility in all situations, and lose sight of the fact that often this isn’t at all how people behave.  This assumption can significantly skew our research results, and so we need to stop making it.  For instance, when talking with vacationers about a recent trip, instead of asking them what was the best part of it, ask them instead just to name some of the things they enjoyed.  There’s nothing wrong with following up with a question that asks them to identify their favorite, but answering it should be optional.  Similarly, every time I see a survey questionnaire that asks respondents to rank brand attributes or experiences, it makes me uneasy—why are we assuming that this is how an individual perceives this issue?  Forcing people into a maximizing mindset creates the risk of generating data that appears to be meaningful, but actually quantifies nonexistent perceptions.  A better approach would be to ask individual respondents to rate those elements, and then to derive a ranking across the entire dataset.

So here’s my big tip: when delving into consumer attitudes, perceptions or decision-making, one of the first things you should do is establish the respondent’s operative mindset.  This isn’t difficult.  If you’re conducting qualitative research, simply ask people to describe their desired outcomes … “what are you hoping for here?”  In quantitative research, it’s a simple matter to begin with some questions that give people an opportunity to describe their mindset – “on a scale of 1 to 5, with 1 meaning ‘OK is fine’ and 5 meaning ‘I want the very best,’ what is your goal for this purchase?”  Beginning with inquiries like these will enable you to understand the respondent’s intentions and state of mind, thus establishing a context for understanding their attitudes, perceptions and behavior.

One final thought: these principles can be applied to circumstances outside of market research.  When evaluating alternatives in business situations, remember to ask yourself if it’s worth the time and effort needed to identify the optimal solution or course of action — it very well might be, as long term success is often contingent upon excellence.  However, occasionally it’s appropriate to identify a sufficient solution, thus enabling you to move ahead more quickly.   And as for your personal life, it’s well documented that satisficers are generally happier than maximizers.  Everything in your life doesn’t have to be perfect– seeking ‘the best’ is often a fool’s errand, and contentment can often be found in adequacy.

I recently came across something called Brandolini’s Law.  It was first stated in 2013 by Alberto Brandolini, an Italian software engineer, and it says that the amount of energy needed to refute bullsh*t is an order of magnitude greater than the energy required to produce it.  It’s also called the Bullsh*t Asymmetry Principle.  Mr. Brandolini is hardly the first person to notice this.  Winston Churchill is often credited with having observed that “a lie gets halfway around the world before the truth has a chance to get its pants on.”  (In a beautiful irony, it seems that this attribution itself is BS.  The remark was probably made by Cordell Hull, FDR’s Secretary of State, but people continue to credit it to Churchill.)

If Brandolini is correct that accurate information is at a fundamental disadvantage to nonsense, this has significant implications to market research.  I often find that one of the most important priorities I face when conducting research is avoiding jumping to conclusions.  I know my clients struggle with this as well.  It’s unsurprising that this is a challenge.  We are pattern seekers by nature, and so we look for explanations when presented with data.  Humans are also naturally uncomfortable with not understanding something, and will sometimes prefer a bad explanation to no explanation.  From an evolutionary standpoint, these traits have clear value.  However, in this modern world, they don’t often serve us well.  And exacerbating that problem is the fact that we’re usually under pressure to deliver findings and implications as quickly as possible—often on the spot.

With market research, rushing to judgement can work against you—particularly in the case of qualitative approaches, which allow us to watch findings accumulate over time.  If you’ve ever sat in a focus group back room, or observed an online bulletin board, you’ve had the opportunity to see data be created in real time.  Not only is it important to resist drawing conclusions before all the information is in, but, once you do have the data, it’s wise to give yourself some time to mull things over – psychologists call this ‘consolidation’ – before forming opinions.  Doing so too hastily can lead to poorly-thought-out implications and unsound recommendations.  And once these flawed ideas are articulated, they can spread like wildfire, and abandoning or revising them after the fact is nearly impossible – hence Signore Brandolini’s observation.

So, here are some practices I follow to avoid this problem:

• I make a point of distinguishing very clearly in my own mind between the tasks of determining what I have heard and considering what I think it means.

• While I’m conducting research, and for at least a few days afterward, I restrict myself to the first task, and hold off on the second. I strongly encourage my clients to do the same.

• I’ll often schedule a debrief call with clients a few days after the research, the express purpose of which is to allow ourselves to engage in the second task.

• I consciously give myself permission to change my mind about things in the days following the research.

• I also strongly encourage all members of the research team to disagree with each other and me. As George Patton used to say, “If everyone is thinking alike, then somebody isn’t thinking.”

One final point. It’s important to bear in mind when looking at quantitative research results that the information you’re reviewing is incomplete.  As we all know, quant gives you a lot of ‘what,’ but not much ‘why.’  It’s qualitative that will provide the story behind the numbers.  So, before you start drawing conclusions based on quantitative data, try to work some qualitative information into your analysis.

I’d love to know your thoughts on this topic.  Feel free to email me or leave a comment on the blog.