Consequently, “analytics,” “visualizations,” and “data stories” (a new narrative genre, according to Stanford researchers) represent our hyperlinked future.
But data has its limits. While its abundance is magnificent, data does not necessarily resonate with readers’ experiences. Data certainly educates, but it seldom motivates.
At MWS, we agree with analytics marketer Daniel Waisberg: people need narrative to synthesize data. Accordingly, we find that simple storytelling is crucial to connecting organizations with their audiences.
However, simple storytelling is not easy to create. This is particularly the case today, as readers are urged to “be suspicious of stories” and are increasingly skeptical of the overt branding storytelling can clumsily deliver.
An organization (whether or not it identifies as brand-driven) can contextualize its data by first explicitly identifying its audience and by then determining the golden ratio between data and narrative appropriate to that audience.
We augment the approach described by Jim Stikeleather (chief innovation officer at Dell). To do this, we consider an audience’s level of expertise on the subject matter and the level of detail with which they’ll likely engage.
For a business report to funders, we might identify our audience as managerial and use accessible success stories to frame data. For internal marketing campaigns, we might identify our audience as expert and create copy from historical research and internal interviews.
While readers want accessible information “in one chart,” our experience and research suggests that big data cannot communicate as compellingly nor motivate as meaningfully as a well-written story. It’s the difference between conveying this point with a chart and telling the story about why data benefits from narrative.