The Echo Chamber at Work

Posted by: Jessica Cornick, PhD
  • April 25, 2017
  • 1

The Internet, in its infancy, was truly the “World Wide Web,” a place where all users had equal exposure to information. Now, thanks to digital advancements such as Facebook’s Newsfeed algorithms, social media filters, and ad blockers (to name only a few), our global network is looking more and more like a series of custom-built small towns. This phenomenon shows the power of confirmation bias – aka, our propensity to seek out and selectively pay attention to information that confirms our beliefs.

Talk of digital echo chambers and filter bubbles has risen since our recent election, but the thought bubble doesn’t only exist in political discourse, and it’s not all Facebook’s fault. We see confirmation bias at play in broader swaths of our culture – even at work, where “cultural fit” is an increasingly essential recruitment metric. Living inside the bubble of one’s own beliefs among like-minded peers is safe and nice, but when we don’t challenge ourselves, we miss critical information and our thoughts stagnate. Information passed around the group becomes ingrained in the group culture and becomes dogmatic.

As researchers and insights professionals, our job is to illuminate the path to good decision-making. Recognizing and addressing the nature of such biases is key to our role. Here are four ways to combat our own echo chambers:

Challenge Preconceived Notions

At the beginning of each project, look deeply into the common lore and knowledge within your organization, questioning the conventional wisdom about the brand or products and where they originated. Dive deep on these assumptions and revise, remove, and refresh as needed. Don’t be afraid to ask tough questions like, “When did we develop this idea?” “What data do we have to support this claim and when was it collected?” “Is it time to rethink this idea based on the current customer climate and market?” This approach breaks the confirmation bias cycle and encourages the collection of fresh empirical evidence.

Walk Alongside Your Customer

Do you have an ivory tower problem? You and your colleagues spend 40+ hours per week thinking deeply about your brand and category and know every facet of every product and marketing campaign. Somewhere along the way, you may have started over-estimating how much your customers think about their product-related decisions. While you may have true brand advocates, the vast majority of customers don’t spend as much time as you do thinking about your products. Take time to get better insight into how your customers engage with your brand and how much time and energy they spend deciding to buy your products.

Poke Those Pain Points

While it’s reassuring to hear about what your customers enjoy, learning how they struggle with your products and packaging can inspire new products or modifications to existing offerings. Take a fresh look by integrating insights. Use experimental, observational, and deep listening datasets to paint a holistic picture of your customer and their unmet needs.

Change Your Analytical Lens

I’m sure, like most companies, you have that one study that you’ve been running for years now, collecting and analyzing data in the same way. How would your competitor interpret the same data differently? Taking the competitor’s perspective will prompt you to look for different signs of success and illuminate areas of weakness. When the next wave of your survey data becomes available, review the current list of analyses and reports. Replace stagnant metrics with fresh options.

No matter how hard you work to stay open-minded, unbiased, and informed, confirmation bias is natural. Our digital and social world increasingly validates, supports, and feeds our own biases. Combatting them requires conscious effort and a commitment to challenging “common knowledge.” Using these approaches will help you step outside of your corporate echo chamber and find opportunities for growth and change.

1 Comment
  • Sean Folan
    June 30, 2017
    Funny how we take so much time to capture the implicit biases that our consumers/customers bring to their decision-making, but don't do the same to ensure our own implicit biases don't overly impact our evaluation of the data we collect!

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