Tips for Translating Research Data Into a Story

Storytelling has been abuzz in the business sector for a while now and big names are embracing the importance of honing these skills among their executives. There is an evolution under way for how to deliver insight, and with it comes a higher expectation for captivating storytelling as a vessel for delivering research insights.

Stories can provide both stopping power and staying power with the ability to get people to sit up and listen as well as a better understanding and a higher likelihood of being memorable. A great story can convey something powerful in a really concise way, helping people with increasingly busy schedules and competing priorities focus on and connect to the insights quickly and with impact—something I’m calling a “compact story” or what you might think of as the executive summary, key findings or elevator pitch.

Human beings are already primed to do this, people are communicating and consuming news in sound bites and tweets. Last year, social media outpaced print newspapers in the US as a news source.

Your Audience Expects a Story

The expectation is there, so why is it so hard for many of us to live up to it? Well, great storytelling principles often fight against some of our natural instincts as researchers. For example, researchers need to have a keen eye for detail and need to dig in and know the data or interviews like the back of our hand… but in storytelling, these qualities put us “too in the weeds,” leading researchers to provide too many juicy data details instead of distilling them.

Researchers are programmed to seek answers but not necessarily trained on how to effectively share them. I think of it like that class many took in undergrad, “English for non-English majors”—we need to learn how to tell a great story despite coming from a variety of non-writing backgrounds.

To get to a great, compact story, you have to both go low (dig deep) and go high (elevate the findings).

Dig Deep: Repurpose a Familiar Research Staple—Moderating

Moderators tend to be great storytellers—it’s their job to push for the “why” and “so what,” to probe respondents until a fuller picture emerges. This is the same thing we need to do with our data, findings and insights—both quantitatively and qualitatively. If you think of each piece of data as a response that needs to be laddered up to a core business objective, you will start down a path that begins to resemble storytelling. For every key data point, ask why. When you understand why, ask what does this mean.

Consider a simple example. Let’s say your business objective is to understand how to get customers to buy more pens. First, you must understand the current pen-buying situation.

• Your data say that 50% of all customers are buying pens today. So, you ask, “Why not 100%?”
• You wonder, “What is different between the group that buys pens and the group that doesn’t? Are some types of customers more likely than others to buy pens?”
• Then you cut the data by those buying vs. those not buying pens and discover that those who buy pens are 40- to 65-year-olds and that 18- to 39-year-olds aren’t buying pens at all!
• You ponder, “Hmm, what is it about those 40- to 65-year-old folks that makes them more likely to buy pens?”
• More digging ensues—you ask yourself, “Who are these people? What else makes them different?”
• Dig, dig, dig, you see that 40- to 65-year-olds rely less on a smartphone compared to younger customers. “Well that makes sense,” you think.
• You push a little harder there, in the younger customers’ open-ends. They tell you they’re faster at typing than writing by hand. Ah-ha, they don’t see a need for pens. You need to help your client understand how to position pens for the younger generation!
• So, does this mean 40- to 65-year-olds don’t use smartphones, they just use pens? Probably not.
  
• You learn that many in this age cohort also own smartphones and buy pens “Why only in this age group do customers both use smartphones and buy pens?”
• Their open-ends reveal that they find handwriting to be nostalgic and more natural and provide a human touch. This helps explain their difference in purchase behavior despite some similarities (smartphone use) with the younger group.

Rinse and repeat for your next key finding. Of course, this is a silly, oversimplified example, but this probing technique can help ensure you’re squeezing every last drop of context and insight possible before building your recommendations.

Elevate Findings: Complete Context ≠ Completely Dense

Everyone has their own style of writing reports, but one thing to consider when landing on your own approach is the way that people digest information these days. Few take the time to leisurely read news articles at the breakfast table anymore; tweets and news feeds satisfy the instant gratification that our fast-paced society craves. The same idea should be applied to your market research storytelling. I often hear, “let’s put the key findings at the back of the report so they have to listen to the rest before we give them what they want.” But why can’t we have both? A news-feed-like summary can whet their appetite and also act as a guide as your story unfolds with more context in the pages to follow.

Using the example above:

Too dense: Fifty percent of customers are buying pens today, with 75% of customers 40 to 65 years old purchasing pens versus 25% of customers 18  to 39 years old. Customers 18 to 39 years old are also significantly more likely than older customers to own a smartphone (90% vs. 67%, respectively) and report that they are unlikely to buy pens because they are faster at typing than writing, unaided.

We’ve all read (and written) findings like that, right? And then had to reread them a couple of times to figure out what all that text is trying to say.

Elevated: 18- to 39-year-olds are less likely to buy pens, citing efficiency of typing over handwriting.

The latter text doesn’t provide every proof point, but it does provide the necessary information to understand the finding.

Beware of Pitfalls

It can be helpful to recognize some common mistakes when trying to tell a story with market research findings:

• Using left-brain processes for a right-brain task. There is no right approach or step-by-step process to craft a story—your creative process looks a little different and that’s OK. In this case, it’s the outcome that counts, not how you get there.
• Getting bogged down with details. It’s tempting to quote each data point or respondent quote especially after spending so much time “in the weeds” understanding it. There is a place for these proof points, but it’s not in your story—it’s in the supporting points, or better yet, in detailed findings.
• Lack of context. The best use of a researcher’s curiosity in storytelling is to ask “why” even when you’ve answered the “what.” Anticipating the questions readers will have is critical to telling a complete story.
• Leaving your audience hanging. Every story must have an ending. When we deliver something that doesn’t provide a “so what,” we haven’t ended the story.

Pull It All Together

Once you have a deep understanding of the whys behind your whats, you have to establish a narrative to deliver your insights—arranging the key finding “tweets” into a story flow. To borrow another qualitative technique, I think of this step like a card-sort or Frankenstein exercise. If you have all of your key findings laid out in front of you, what order makes the most sense? What parts fit together and what parts may be missing? Even better is to pair your findings with evocative visuals and the respondent’s voice—but that’s a different topic for another blog! Until then, keeping these tips in mind may help you tell a compelling story next time around! Do you have any go-to storytelling methods or preferences?