Radiance Blog

Never trust an assumption

Recently, the Corona staff prepared for an online bulletin board, a research method we often use. Participants from our client’s target audience get into a private online community and respond to message or image testing questions through exercises like polls and photo critiques. Prior to the study, I looked at the stock photo images and told one of my Corona colleagues, “No one’s going to like this one”. There didn’t seem to be a center of focus, and compared to the other beautiful and high quality pictures, this one, in my opinion, fell short.

A couple of weeks later, after our online bulletin board was finished, and participants had given their various opinions, I looked at the responses for that same picture I disliked, expecting there to be criticism and distaste. The opposite happened; they loved it. In fact, it was the participants’ favorite photo. Despite my opinion, participants liked the fact that the home design photo was very “one with nature,” being surrounded by plant life. I was surprised. What about the other beautiful homes? The expensive designs? The happy families in the other photos? As we analyzed the feedback, our reporting reflected our findings – participants loved that photo, and my personal opinion never entered the equation.

As researchers, we check out biases at the door. In fact, we actively take steps to eliminate bias in our research. When we put together a sample of participants, we take the extra effort to make sure our audience is representative of who our client wants to hear from. When we put together a moderator’s guide for a focus group, we ask ourselves if the order of questions could unfairly affect the responses. When we write a report, we make sure what we’re writing doesn’t dilute or unfairly frame what we really heard. In many ways, we’re trying to eliminate ourselves as researchers from the process so that our client is hearing what their target audience is saying, not necessarily what we as researchers are thinking.

“So, then what does Corona think?”  Once we have a feedback from a research process with as little bias as possible and reliable findings, we then assist our clients with the implications of those findings and make recommendations to aid them in making their important decisions.  This is where we can give quite joyfully because we know our recommendations are built on objective and sound market research. We’re proud of the consulting work we do, but only after we conduct a research project where we feel we have minimized bias to all possible extents. These extra efforts make big differences for our clients, and our work helps them make the best business decisions they can.



One comment on “Never trust an assumption”

  1. This really helps show the importance of targeted consumer feedback. I wanted to pass the information below along from a 2012 survey with 800 marketers at Fortune 1000 companies. HBR did a write-up on it:

    “On average, marketers depend on data for just 11% of all customer-related decisions. In fact, when we asked marketers to think about the information they used to make a recent decision, they said that more than half of the information came from their previous experience or their intuition about customers. They put data last on their list — trailing conversations with managers and colleagues, expert advice and one-off customer interactions.”

    Your study proves why that 11% is much too small of a number!

Leave a Reply

Your email address will not be published. Required fields are marked *