Are All Emotional Measures in Consumer Behavior Research Created Equal?

By Alena Jule
August 25, 2014
Proportion of Emotion Model
An executive asked us recently if it really mattered, from a business perspective, whether the techniques they were using to measure emotional drivers of behavior were truly implicit. If you’ve been reading our blog, I’m sure you know what our answer must have been.
In this video from IIeX North America 2014, Dr. Reid provides evidence from research coming out of the Sentient Consumer Subconscious Research Lab, that all emotion measures for consumer behavior research are not equal.
Dr. Reid makes the case that we want our emotion measures to be distinct from derived conscious measures, as long as they are different in meaningful ways that better predict sales. The research compares emotional slider scales, “fast explicit” emotion measures, and true implicit emotion measures. The results show which emotional measures are different from derived conscious measures in meaningful ways.
[fve]http://youtu.be/xT5HepM-XIE[/fve]
TRANSCRIPT:
>>Dr. Reid: We wanted to know, “are all emotional measures equal?”
So we compared emotional slider scales to conscious preference; because we were interested in how much they would differentiate from conscious preference. We want something that is not the same. So when you use the slider scale, you’re saying, “tell me how you feel about this.”
We did the correlation. The correlation between explicit emotional slider scales and derived preference (that’s not sales, that’s preference) is 89%. What that tells you is that they’re largely measuring the same thing. They’re only 11% unique.
When we did it with fast explicit techniques, there was 85% overlap. Meaning fast explicit techniques (just making a conscious judgement quickly) is only 15% unique from conscious measures.
But, when we compare the true implicit research data to the conscious measures, there’s 34% overlap. What that means is that they are 66% unique. And that’s what you want. You want something that you’re capturing separate, meaningful variance in the behavior of interest.
And is it meaningful? We know from the sales data that it is meaningful variance, not error variance. True implicit has a predictive advantage over fast explicit and other explicit emotional techniques.
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