Have you ever wondered who your respondents are and what motivates them to devote their time to you? In the digital era of the research industry and the growing popularity of online research, it is worth asking yourself the above question. Knowledge about respondents allows you to understand their perspective as a key participant in the research process and build a valuable relationship with them.

Data from the latest report “Respondent, Consumer, Citizen” prepared by SoftArchitect and Herstories indicate that respondents regularly participating in market research are people who are engaged, socially responsible, aware of their own role in the research process and the impact they have on the decisions of marketing managers. By completing surveys regularly, they feel like partners with a research agency.

Respondent communication in a “Research 4.0” world

Improving the quality of collected data, improving the efficiency of business operations, and appropriate design and management of

Advertising must interpret a person’s media consumption and engage/convince them to change or reinforce the behavior – all in a few seconds. Storytelling principles have been used for years to help advertisers succeed and win in this competitive environment. There have been 10,000’s studies on advertising effectiveness and we hope this article will validate those findings and provide heuristics for the rest of us.

We started by exposing 1,410 consumers to 400+ ads and collected over five billion data points using a medical-grade EEG (electroencephalogram) system consisting of 32 sensors tracking neurological activity. These sensors collect data 500 times a second to capture activity across key regions of the brain as consumers were exposed to the advertisements.

Our findings were:

Validation (further evidence to what we already know)

• TVCs that used a storytelling approach had a 20% greater brand cut-through as compared to TVCs without a storytelling narrative.

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Author’s Note: I’ve always been interested in biases. A poster of The Cognitive Bias Codex hangs in one of our home offices; and, I’ve bookmarked and often look at that interactive wiki to learn more. Just like I looked to two industry experts to learn more about bias in research for this article: Jeff Henning and Ray Poynter. Many thanks to you both for serving GreenBook as expert sources. We value your contribution to this piece, just as we value our readers.

Have you ever asked a question while assuming you already knew the answer? That’s a simple example of a bias. As humans, we inadvertently experience bias in every aspect of our lives. Our personal biases influence the lens through which we look at the world. And while some biases are innocuous, some are harmful; and, bias in market research can have a negative effect on the findings.

We marketing researchers can create quite complex data systems that start to push the limits of formulas in stat textbooks to determine confidence intervals.

RIM weighting

Using RIM weighting (also called Raking and Iterative Proportional fitting) is the start. There is a formula for that that tells you the effective sample size you are working with for stat testing purposes which is always less that the nominal number of interviews (how much less depends on the variance in the weights across respondents).

Now layer in weighting top box purchase intent twice as heavily as second box. And let’s consider differences in differences in that index, such as test vs. control across two advertising treatments. Is the lift from one tactic significantly greater than the lift in another tactic, exposed minus unexposed? You are going beyond simple formulas at this point to determine if a difference you are seeing in the