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Does Quantification In Market Research Lead To Disengagement?

Does Behavioral Economics deliver the missing piece to attain the "Holy Grail" of research: combining the insights of a qualitative survey with the robustness of a quantitative project?


Learning numbers


By Edward Appleton

Week 6 of the Dan Ariely/Duke University Behavioral Economics (BE) online course ( ) is about Emotions; one of the first reading assignments focuses on a phenomenon called “Psychic Numbing”.

A term originally coined in the 1960s, this refers to a cognitive process of disengagement, a numbing of feeling, induced by the use of numbers. It leads to apathy and inaction. To quote the authors:

“Numerical representations of human lives do not necessarily convey the importance of …. lives.”

My mind immediately flew to Quant. Research, Predictive Analytics and Big Data.

The actual article – ( authored jointly by Paul Slovic, David Zionts, Andrew K. Woods, Ryan Goodman,and Derek Jinks – addresses the apathy often witnessed towards mass atrocity and shows how psychologically engagement falls off the moment we start to portray a problem simply in terms of numbers. We engage far more actively, process information more effectively, when confronted with individual stories and narratives. Presenting “numbers” results in a “blurring of individuals” (Annie Dillard) – a phenomenon that can begin with as few as 2 people. Scary.

This BE finding has potential implications for Quantitative Research, especially in terms of how data is presented. Many quant. read-outs are concerned with measurability, statistics, percentages, sample sizes. They are seldom (never?) accompanied by a focus on the individuals making up the sample. Maybe we’re missing a trick. Here’s my take, borrowing from some of the implications outlined in the Article:

1. Building in Individual Experiences can Greatly Enrich a Quant. Survey.

Many straight quantitative surveys have some open-ended questions, requiring individuals to do more than tick a box. But how many actually ask respondents to share visuals with us to show us what they mean? Given the growing use of mobile, maybe we should ask participants to use their smartphones or tablets to take pictures more. This would give a quant. survey a qualitative feel without being truly qual./quant – and the de-brief would be much more engaging.

2. Counter “Numbing” by Emotionally Priming an Audience Prior to a Debrief

I’ve never tried this, but it’s an interesting idea. The article suggests priming audiences to “feel” prior to looking at any numbers – simply asking them to describe their feelings when thinking of something emotional, eg a baby. Translating this to a product category – easier for higher-involvement B2C areas, but not impossible even for low-interest products – might make a potentially “challenging” (strenuous, long) de-brief on a given commercial area a more engaged, emotionalized experience.

3. Use Imagery – but avoid Cliches.

Visualizing can be a powerful narrative technique, but using well worn images is invariably counterproductive, leading to swifter disengagement.

4. Anticipate Co-Creating Indicated Actions with Your Stakeholders

The authors suggest that faced with the danger of psychic numbing, building in a session focused purely on decision-making will heighten engagement and heighten the likelihood of action being taken. They call it a “deliberation-enforcing approach”. For researchers, it’s something worth considering – building an interactive, action-focused workshop session into a quant. debrief. 

Combining the insights of a qualitative survey with the robustness of a quantitative project is for me at least a sort of Holy Grail of Market Research. Maybe incorporating some of the above helps take us a step in that direction.

Curious, as ever, as to others’ views.

Please share...

6 responses to “Does Quantification In Market Research Lead To Disengagement?

  1. Correct, I would say. Mixing quality&quantity is the current mainstream. It works. A good example is the idea to produce “personas”, the psychological profiles of different types of customers, a short narrative with a photo, and associate to each “persona” a specific segment you have find with your statistical analysis. But the numbers come after: “personas” first. It is very useful to spread the idea among different levels of management in the company, and for different purposes from sw and IT managers, to advertisers.

    Ciao! Carlo

  2. Carlo, thanks for your comments. Are your “personas” real people? I find it irritating and unconvincing having “types” described to me, however good the segmentation and cluster work was – they simply don’t come alive. Real people, however, are simply what they are. Curious

  3. Great article! Taking advantage of smartphone technology to blend quantitative and qualitative is an excellent suggestion. A picture is worth a thousand words, provided the person is willing to send the photo.

    Mark Eversfield.

  4. Dear Mr. Appleton,

    You did a great job extending the implications of my psychic numbing article to quantification in market research.

    Seeing your post helps me solve the mystery as to why my article recently was downloaded 8,000 times off the internet. Dan Ariely’s course must have a lot of students.


    Paul Slovic

  5. I agree with Carlo, mixed methods and a deepest interest in in depth research associated with numbers will allow to better explore emerging Big Data questions.

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