How much more compelling would your brand storytelling be if data were the focus of your content strategy?
In a recent article published here on CMI, Colleen Jones asked the question, “Can digital branded content ever be taken seriously — even as seriously as journalism?”
Without a doubt journalism has had a huge head start when it comes to creating stories that capture hearts and minds. Part of that success comes from using research data (polls, surveys and feedback) to understand what readers find valuable, particularly as it relates to the issues and problems they face.
Do content marketers have the same research opportunities? Of course they do. In fact, if more content marketers were to use publicly available data the way journalists do then branded content would offer new angles, insights, and more value to stories that affect people’s lives.
But the good news, as Colleen explains, is that, “Americans are quite open to brands being credible sources of web content.” One way for brands to increase content credibility is to introduce trustworthy third-party data as part of their stories. Credible stories are rooted in something that’s real, not just your ideas. So for example data, research and numbers can be the foundation of the story, while your ideas and opinions add perspective to the story.
Currently, there are mountains of data available, on the internet and elsewhere, that organizations can use to develop credible stories that are infused with insight, relevance, and inspiration. So how can your brand learn to create data-driven stories? Here is a six-point process for brand storytelling that you can use to get started:
#1. Keep your audience top of mind
Great data-driven stories start with great questions — specifically, questions that are relevant to your audience and customers, such as what are their nagging questions, or what are their greatest business challenges? If the questions you come up with have quantifiable dimension, chances are they will make for a good data-driven story.
For example, let’s say you’re in the health care space, and you know your audience is concerned with finding accurate, reliable health information online. One story you can consider creating would be a piece on how patients use online health care records in your city, and how often they access this information. The specific question your content might address here would look like this: “Why consumer demand of health IT outstrips supply.”
#2. Find the data
Once you have defined a question on which to base your content, you need to determine the available data records you can incorporate to answer that question. To do this, you will need to think about the process you will use to collect, filter, and visualize data in order to create deeper insights that will inform your story.
Collect: At first when you’re looking for data on a particular topic or issue, you may not know where to look, or if that data even exists.
However, if the problem has a measurable component, there’s a good chance of finding adequate data (on the internet) to generate an insightful answer. Finding adequate data to support your answer is important because you don’t want to jump into a data-driven story that cannot be executed.
Using the health care example above, you would need to find data that shows how many patients have asked for their health records online, how many doctors or facilities have the technology to furnish such requests, how many have actually done so, etc. Here are some good places to start looking for this data:
- Public data sites, e.g., government databases or state agency databases
- General lists, such as the Journalists Toolbox or Freebase — an interesting Google subsidiary that provides entity graphs of people, places, and things
- Q&A sites, such as Get the Data or Quora — a site where you can post your data-related questions (including where to find data on a particular issue)
#3. Vet your data source, and filter your findings
Don’t forget that the goal of using data is to increase your content’s credibility and to validate your brand’s storytelling. That said, make sure that the source of your data is also credible. Use sources that are reputable and well known for research data; for example, Forrester Research and Pew Research.
Generally speaking, academic journals, university sites, studies, and research reports from professional institutes are good sources of data, while most blogs (unless they’re very authoritative) are not.
Filtering data is like interviewing a real source. You ask specific questions in order to get the answers you’re looking for. Same thing with data — what question do you want the data to answer?
Let’s say you’re writing a story about hospital closures in your county. The data-backed statements you will make will involve the number of hospitals registered, how much it costs to keep them running, sources of funding including how many people with health insurance, etc. So the minimum data you would need to filter is number of hospitals, cost, revenue, number of insured, etc.
#4. Choose a visual representation
Our attention-deficient generation gravitates toward visual content. So once you have found adequate data, and have determined which of the available data will best address your initial question and strengthen your story, you then have to think about how you will represent it visually for your audience’s consumption. For example, bar charts, pie charts, infographics, and mappings are all simple methods of data visualization, so you will need to decide which format will work best for the data you are using.
For example, check out this innovative visual from GE Healthcare, which captures ”Who’s talking about breast cancer” on Twitter.
Remember that the more interesting the visualization, the more time and attention consumers will give it. Be sure to keep your visualizations simple — you don’t want to make your audience have to work hard to figure what your graph is all about. Try several different visuals and see what appeals to your audience, then stick with that format.
#5. Shape the story
Using data is about adding as much value to your content as possible. It’s about saying something that hasn’t been said before. As you begin to shape your story, try to use an original approach and be sure to add a unique and meaningful perspective.
More often than not, a successful data-driven story will require the collaboration of analytical-types (to gather, analyze, filter and visualize data) and creative types to unearth a compelling story that’s just waiting to be told.
#6. Get some feedback before launching
When you’re finished, show your story to an outsider who has absolutely no connection to the project. Ask them what they think. Does it make sense? Is it interesting, or just confusing? Take that constructive feedback and use it to peel away the layers that don’t add value to the story.
You may have to simplify the data or the visual, or find different words to tell the story (or, God-forbid, all of the above!). This may take more time, but it’s important — it could mean winning the hearts and minds of your audience, or losing them altogether.
Over to you: Has your organization experimented with data-driven stories? How did you approach the project? Please share your ideas in the comment box below.
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