Behavioral Science – Part 2: Sometimes It Is What You Don’t Do That Makes Things Better

If you read my first Behavioral Science blog post: An Intro to Behavioral Science/Nonconscious Measurement, welcome back. If you didn’t, let’s quickly catch you up by reviewing the key takeaways. In my introductory post, we learned that…

  • Behavioral Science seeks to better understand human behavior, and nonconscious measurement is the practice(s) by which one goes about collecting subconscious data from the human mind.
  • These practices are necessary because there is a contradiction in traditional market research approaches in that they are often set up to yield mostly System 2 (slow, conscious) responses from consumers, yet, when those same consumers are making decisions in real life they more so rely on System 1 (fast, unconscious, automatic) decision-making.
  • To combat this contradiction, researchers increasingly need to examine the way they approach study design; by incorporating Behavioral Science principles they can create a more holistic understanding of consumer behaviors.
  • There are varying “levels,” or degrees of sophistication, to which you can begin incorporating Behavioral Science into your research design and processes:
    • Level 1: Stop doing things we know are unreliable.

    • Level 2: Start consciously designing questions to yield more nonconscious responses.

    • Level 3: Start researching and incorporating validated behavioral science-influenced techniques.

We’re going to dig a bit deeper into “level 1” behavioral science in this post, let’s get started.

Level 1: Stop doing things we know are unreliable.

Despite sitting at the lower end of the spectrum in terms of sophistication, “level 1” behavioral science is my favorite level because it makes respondents happy, and you can begin doing it immediately. Sound too good to be true? It’s not. Stopping bad behaviors in the design phase is the easiest, and possibly the most effective, thing you can do to start incorporating behavioral science principles into your research.

What, exactly, are bad behaviors in the design phase of research? Here are three that researchers need to be more mindful of avoiding when designing research activities:

  1. Creating (very) long surveys. What defines “long,” or “very long,” is a matter of debate, but generally speaking, I recommend keeping your survey length under 15 minutes to set yourself up for receiving the most reliable, highly engaged responses from participants.
  2. Asking similar/boring questions. It’s important that you ask a variety of question types within your survey to keep respondents engaged. Most researchers are cognizant of the number of open-ends asked, but not nearly as many are keeping tabs on how often other question types are being employed. Mix it up, to keep respondents engaged.
  3. Asking difficult-to-answer questions. For example, how many times have you _____ in the past year? Answering a question such as this can be very frustrating from a respondent’s point of view and will lead to over-thinking and guessing, which is exactly what behavioral science/nonconscious measurement tries to diminish.

The common pushback I hear with regards to the bad behaviors above is that they’re often unavoidable when designing research against a client’s brief or strategic imperatives. In the sense of traditional market research, which is very much focused on one-off studies, I’d tend to agree, but at Maru/Matchbox we’re anything but traditional. That’s why we strive to create ongoing research engagements through an integrated platform solution, which takes research past the theoretical “one night stand” and into a committed, two-way relationship between your business and your highest-value target groups. The development of such an initiative leaves no room for excuses, as research activities can easily be broken up into iterative learning streams (decreasing length). We use a wide variety of highly visual, interactive question types (reducing boredom), and in-depth profiling facilitates asking only those questions that are recent (decreasing reliance on memory), which makes respondents more likely to participate in future research. It’s time to respect how the people think, and to stop asking questions in ways that don’t work.

In my next post, I’ll be expanding on “level 2” behavioral science, so stay tuned.

Other posts in this series:

An Intro to Behavioral Science/Nonconscious Measurement

Behavioral Science – Part 3: Conscious Design Yields Unconscious Responses

Behavioral Science – Part 4: Validated Techniques & Their Use Cases

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