Published 7/28/2015
Author: Renee Ho

Photo Credit: Jennifer Daniel, New York Times

Did you say you’d vote but (whoops!) never did?

“It’s not uncommon for 60 percent [of survey respondents] to report that they definitely plan to vote in an election in which only 40 percent will actually turn out,” explains Cliff Zukin, past president of the American Association for Public Opinion Research.

In his recent opinion piece for the New York Times, Zukin explains that pollsters have to guess who will vote. Organizations construct weak “likely voter” models to predict who will turn out to vote.

“…Polling slowly shifts from science to art,” explains Scott Keeter, director of survey research at Pew Research Center.



Behavioral economists like to say that is often an intention-action gap. Action are controlled by intentions, but not all intentions are carried out; some are abandoned altogether, while others are revised to fit changing circumstances (Icek Ajzen, 1985).

Similarly, one could say that there is a kind of “stated attitude-real attitude” gap(see stated versus revealed preference theory). Behavioral economics (among other social scientists) would agree that stated attitudes are often the product of social norms, power dynamics, and other biases.

Maybe I say I like your service

Because others say they do.
Because you’re my boss’ mom.
Because you are beautiful and smiled at me.
Because it would be rude of me to say otherwise.

In a recent trip to Mongolia, I observed a surveyor ask some herders if they liked a technology. Would you use the mapped, geospatial information?

“Yes, yes,” they nodded. “It can be very useful.”

I rudely interrupted and asked, “Can you please point to where you are located on this map?”

Most could not. Others, when they saw where another herder pointed, said, “Yes, yes. We are here.”

I’m not suggesting you do this. Embarrassing your constituents is not something to be proud of. It turns out that most Mongolian herders have an amazing spatial knowledge– just not typically translated into paper maps.

How, then, do we get feedback that is unbiased? How do we know that intention will lead to action?

For example, the Net Promoter System is a tool companies use to get customer feedback. It asks, “How likely are you to recommend [X company/product/service] to a friend or colleague?” using a 0 to 10 point scale.

Implicit in the question are two assumptions:

  1. That the feedback is unbiased.
  2. That the score you give is related to an actual behavior– you spend again with this company or you recommend it to a friend.

The first assumption seems to hold in the for-profit sector typically because consumers don’t fear any repercussions. The second assumption seems valid because the Net Promoter Score is shown to be correlated with a company’s future growth.

As organizations in the non-profit sector get perceptual feedback from their constituents, we need think carefully about ways to create a safe space for open feedback, ways to limit biases in responses.

Then, we need to systematically measure how this feedback translates into actual, observable behavior. If people tell us they will use our service or products, let’s make sure they actually do.

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