What 2016 Presidential Election Polling Failure Tells Us About Consumer Decision Making
…And Why Traditional CDTs Don’t Work
In the days since the election, there’s plenty of chatter in the market research community – and in the world, really – about whether or not traditional polling is the best approach. Nate Silver and many other traditional pollsters were wrong about the 2016 presidential election. While Silver gave president-elect Trump a reasonable chance of winning the election at about 35%, others estimated Trump had as little as a 1% chance of winning. It was expected to be Clinton by a landslide based on many traditional polls.
There is a definite buzz in the air regarding American University professor, Allan Lichtman, who called the election correctly using a more non-traditional predictive approach that relies more on the big picture than on polling. (Lichtman uses a series of 13 “key” true/false questions that are based on pass/fail decision rules. An answer of “true” favors the reelection of the party holding the White House. If six or more of the 13 keys are false, the incumbent party loses.) Lichtman’s prediction of a Trump win maintained his record of correctly predicting every presidential election since 1984. For future elections, we may well see a shift away from confidence in traditional polls-based predictions like Silver’s and more emphasis placed on less traditional but more holistic diagnostic approaches like Lichtman’s.
Trust Issues with Traditional Methods
At Decision Insight, we faced a conundrum between traditional and non-traditional research approaches over a decade ago when our clients asked for our point of view regarding Consumer Decision Trees (or CDTs). Most clients had employed traditional research approaches that relied on historical sales data – and many found those approaches falling short. Traditional CDTs weren’t shopper-driven, couldn’t accommodate innovation, and didn’t answer a lot of “why” questions. It was becoming clear that there was misplaced trust in these traditional research methods. Like election polling research, there was becoming significant mistrust in CDT methodology and in their ability to help predict real-world outcomes. The time was right to develop a new and better “non-traditional” research methodology that could shore up many of the CDT shortcomings clients were concerned about.
In short, we set aside the more traditional research approaches and developed a more holistic non-traditional approach that better takes into account the broader consumer picture. Here is what Decision Insight CDT research entails today:
- A uniquely shopper-centric methodology thoroughly grounded in shopper behavior and attitudes – and the context of the retail environment.
- Forward-looking recommendations inclusive of innovation rather than simply a historical analysis of prior purchasing.
- Direct measurements of substitutability and product consideration sets rather than statistical inferences from paired purchases or loyalty to pre-defined attributes.
- Both quantitative and qualitative learning – yielding rich category structures with supporting interviews, quotes, and text analytics that resonate with both internal teams and retail partners.
- And, most importantly, we are highly focused on our clients’ activation of results – not merely research reports. Unlike traditional researchers, the DI team is actively engaged in the interpretation of findings and hypothesis generation that leads to tangible solutions that are regarded highly in retail.
The rest, as they say, is history. Unlike 2016 election polling research, failure in shopper research is less dramatic and less visible. Changing our Decision Tree methodology at DI was not a mandate based on dramatic fails. On the contrary, we changed CDT methodology because we just believed there was a better way. Nearly a decade ago we made a decision that quality market decisions could not be made without quality market research. Since that time we’ve conducted enhanced CDTs for many of the largest CPG brands and manufacturers in the world – and we continue to innovate and improve our approach, year after year. If you believe traditional CDT methodology is falling short, our non-traditional approach might be the right approach for you.
Please email us to learn more about our Consumer Decision Trees.
Alex Sodek is Chief Research Officer at Decision Insight. He can be reached via email firstname.lastname@example.org or call (816) 437-9834.