Research failures are not uncommon, even among large-scale, well-funded projects for very important causes.
Quite often, research is conducted with the best of intentions but not by specialized vendors that understand the entire process from pre-field planning all the way through data visualization.
Below we explore one very common failure - please contact us to learn more on other failures and how we can help you avoid them.
Research Failure #1:
EMOTIONAL DRIVERS ARE PARAMOUNT, YET ARE OFTEN IGNORED.
Actionable research relies on understanding drivers, not collecting answers.
Drivers: Drivers explain why and how a decision is made. Drivers provide deep insight and can be used to form strategies to convert people to a position they otherwise would outright reject.
Answers: Answers to basic, static questions are point-in-time responses that can readily change. Reliance on overly structured data (i.e., traditional political polling) cannot tell a full story.
DECISIONS ARE MADE BASED ON EMOTIONS
To best predict decision behavior, we must understand decision drivers, not just tally binary data points. “Yes/No” type questions and preset lists of historic issues force respondents to answer within a defined structure, which often leads to misrepresenting their intent and lean.
The highly touted political metrics below are contradictory and not informative/actionable.
DEEPER INSIGHT IS NEEDED.
How did at least 23%* approve of the leadership yet also feel the country was moving in the wrong direction? What was driving this conflict? Regardless of the constant headline coverage, these two figures are too thin to be useful.
* If all 23% who felt the country was on the right track also approved of Obama, then 50%-23% = 27% who approved of the leadership but not the direction. If not all 23% who thought the country was on the right track also approved of Obama, then even more than 27% have a “disconnect”.
WHAT INSIGHTS CAN BE GAINED?
Does the data above provide any real insights? Is anything new learned? Are we any closer to understanding what the voter is actually thinking and how to connect with them? This data is simply too thin. Assumptions drawn from thin data can and do lead to dangerous and ineffective strategies.