Turning Data into Storytelling

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Robin Robinson

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Beyond communications skills, creating a good data story requires research.

Nobody wants to listen to a boring story. And for some, data can be boring, or at best, confusing. Telling an enthralling story takes a certain skill, and when the topic is a mound of eye-glazing data and analysis, it becomes even more difficult to spin a tale that will capture and hold someone’s attention and allow them to understand the takeaways. That’s what a good data story should do.

For those analytically-minded folks whose job it is to collect and analyze data, telling a data story can be a struggle. Analysts are not always equipped with the creative ability to produce an emotive story around their findings. This is a big problem for brands, because effectively communicating data is critical in today’s information-overloaded marketplace.

Our experts tell us that the same elements that are important in all storytelling are also important in data storytelling, however, not necessarily in the same order. For example, in data storytelling, it is crucial to understand who the audience is before constructing the story.

Also, visualization and word choice are key to expressing the right details, and the idiom “what’s in it for me” or WIIFM is imperative to create value to the audience. It takes a special talent to be able to bridge between telling a business story and telling a data story; the best data storytellers are often those with experience in both data science and business.

“Great data storytellers are rare because they have a refined ability to translate issues articulated by business leaders into an analytics plan for data scientists,” says Robert Gabruk, managing director at 81qd.

“Additionally, these skilled storytellers excel at doing the reverse: they can translate the insights from data and analytics into content that can be understood by business leaders. By virtue of this, the best translators are often those with experience in both data science and business.

Moreover, their success is often a function of their ability to empathize with their audience and apply metaphors, analogies, and anecdotes that bring the data to life for optimal relevance.”

Peter Chobanian, director, marketing analytics at Ogilvy Health, says as an analyst, he works in various data collection platforms that collect millions of different data points. “And as an analyst, I need context to make my story relevant and meaningful to someone,” he says.

Since people relate more easily to people than they do numbers, data needs to be presented in a narrative that resonates with the audience. The most compelling data stories will combine data and analytics, and include an account about the data that involves people. No matter how great the data are, if the audience can’t relate, the data won’t compel them to act.

While it might be tempting, Mr. Chobanian cautions against using all the data that’s available. The data needs to be pared down to just the most crucial elements needed to tell the story.

When preparing to create a powerful data story, Mr. Chobanian says he carefully explores several points of view to fully determine what the foundation should be; for example, why is the story being told, what problem is it trying to solve, what needs to be accomplished, who is the key audience, and what action will listeners most likely take after hearing the insights.

“Once all my insights are collected, I try narrowing the data down to present only a handful of the most relevant insights to tell the higher-impact story,” he says. “I include only the absolute essential material and keep the deep-dive information in the appendix, or per follow-up request.”

Mr. Gabruk refers to this exercise as using the SCQA principle: situation, complications, questions, and answers. It is important to craft a compelling introduction to the story by applying the logical framework of the SCQA principle and the Minto Pyramid Principle, to increase the likelihood of the audience being able to retain and absorb the data provided, he says. For example, start with the answer to the problem first at the top of the pyramid, then group and summarize your supporting arguments and logically order your supporting ideas. The Minto Pyramid Principle has been around since Barbara Minto invented it while working at McKinsey more than 40 years ago. Incidentally, Minto workshops and classes are still being taught today.

“The Minto method often guides my approach to data storytelling: the principle predicates that ideas and thinking are more likely to be understood and received when organized and presented as a pyramid under a single point,” Mr. Gabruk says. “But a good data story is a function of recognizing the key targets’ roles, expectations, and experiences, as well as how the story can impact their interests and positions, or how it can potentially be met with resistance.”

Along with knowing the audience, providing the proper context is also important. According to Vince Budd, managing partner, Leaderboard Branding, data can be strongly compelling in context, and he recommends asking these questions when considering whether the data is contextually relevant: does the audience understand the challenge that needs to be solved?; does the audience understand how the data is connected to solving the problem?; what hurdles or assumptions might the audience have that could hinder the story?; what can help make the story more relevant to the audience?

“Facts usually tell a story when they matter to the listener,” Mr. Budd says. “Often, the trouble with facts is that the listener ends up asking ‘why does this matter?’” We try to create consistent and impactful stories centered around understanding the listener, communicating clearly and with a natural progression, and focusing on the elements of the story that make it unique and memorable.”

Audience Comes First in Data Storytelling

Above all else, fully understanding the audience is the first criteria an analyst needs to be able to weave a compelling data story.

“The important anchor of all great storytelling is an innate understanding of the audience,” Mr. Gabruk says. “The most critical elements in a powerful and insightful data story are respecting the audience and understanding the WIIFM, which is central to data storytelling application. The story is not about what you want to say, but what the audience will gain from it. Their need to know is paramount, not your need to inform.”

This becomes more difficult when the audience is highly diverse, which can occur often. Unlike segmented messaging that is developed for a certain customer target, data storytelling often addresses a broad range of stakeholders.

“Once we understand our audiences, we segment them by journey type, preferred communications platform, and the content type that is most impactful to them,” Mr. Budd says. “Then we analyze our content to ensure we’re delivering the most effective communication at the right time. The stories must use language the audience understands because without a common footing of language, no story can be understood.”

Use Your Words, Carefully

Not only do you have to use common language and vocabulary, but you must also use — or not use — words very carefully when telling a data story.

“Being mindful of the words we use is paramount to crafting a compelling data story,” Mr. Gabruk says. “With data storytelling, there is an inherent assumption of fact-based content and objective quantitative evidence, in contrast to opinion-based conjecture and insights. This is why word choice and word omission are critical.”

For example, he says, the word “significant” has a specific meaning in the data and analytics world, and someone hearing the word “significant” could easily assume that the results are statistically validated, while its use may have been intended only to convey the idea that a result was notable.

Word omission can also lead to misunderstanding or misconstruing data if the author is not careful. Mr. Gabruk provides a real life example: “I once had a client who based his brand positioning and messaging on a key driver analysis conducted by another company,” he says. “We conducted our own key driver analysis and found far fewer and different key drivers. Perplexed, the client asked the previous vendor for more information about the data. What the vendor had neglected to tell them was that the results were based on a correlation analysis, which did not determine causation, and those correlations, while positive, were of little value for many of the drivers. It was an ‘uh oh’ moment for the client; they had invested millions of dollars in a message platform that was not strongly supported by data.”

After addressing audience context, the next key element is audience caring, Mr. Budd says. “Once the foundation is laid through context, the focus shifts toward getting the audience to care,” he says. “Caring doesn’t have to be a deep emotional connection — it can be a brilliant insight, an abundance of potential, or an important and hard-hitting fact. Whatever it may be, the element of audience caring leads to a more impactful and memorable story.”

Data Visualization is Imperative

Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data. Data visualization is critical to optimizing storytelling because it makes data, whether simple or complex, easier for the human brain to understand.

“People in our culture are visual, being drawn to art, color, and motion,” Mr. Chobanian says. “People are less likely interested in reading through excel spreadsheets and text heavy narratives.”

He refers to data visualization as a type of artform used to quickly get a point across to people. For example, using colors in a geographic chart like red or green help people quickly identify if sales have increased or decreased within seconds, when compared with reading through text. “Mix matching multiple data points and using visualizations, such as color, size, and position, you can showcase monthly sales in specific regions associated with inventory in seconds,” he says.

Mr. Gabruk agrees that audiences are more likely to remember and react emotionally to compelling visualizations than to written words. “For example, I once used a single graphic to represent a complicated analysis, and that was all it took to communicate the entire story,” he says. “Five years later, my team used a very similar graphic with the same company. After the meeting, the client team complained to their director that we had stolen their graphic. The director, who had been at the initial meeting five years before, explained to them that they had taken what was actually our graphic as their own. Apparently, the graphic was so compelling, the client had been using it in many of its presentations.”

Data visualization is also helpful in clarifying the understanding and context of a story or emphasizing its current or potential impact. In Mr. Budd’s experience, data visualization is most effective when it adds to the context or audience caring.

“By itself, a well-designed infographic, an informative chart, or a color-coded graph is not a full story,” Mr. Budd says. “We see so many examples of communications, especially data rich communications, that make broad assumptions about audience knowledge and a comfort level with technical language and savviness with data, charts, and references. Setting the stage for a story with clear context is critical to being given ‘permission’ to go deeper.”

As Mr. Gabruk said earlier, great data storytellers are rare, and data storytelling isn’t easy. However, when data and stories are used together, they resonate with audiences on both an intellectual and emotional level. As the world increasingly becomes more and more data-driven, data storytelling will become a more crucial tool to be used to explain complex concepts in a painless, quick way. By providing insights in a way that anyone can understand, data storytelling will help move ideas and products forward in a more efficient manner.

After all, it was the great storyteller Rudyard Kipling who said: “If history were taught in the form of stories, it would never be forgotten.” The same can be said for data.(PV)

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Steps for Using Data Visualization in Data Storytelling

When approaching a data visualization report or project, these proven steps can help deliver the right visualizations in the right context.

1. Identify the audience you’re delivering the data visualization to. Find out what questions they have, what you think this audience wants/needs to know, and what decision they will make with the data. We want to make sure people feel empowered to use the visualization and reference the data to take action.

2. While data visualization is important, choosing the right visuals in the right context is key. For example, a combo chart trending sales and purchases over time might be a better way of showcasing a spike in sales and purchases, when compared with a data table. If a stakeholder needs to see or report a specific number each month, a large scorecard widget or graphic might be a good option to quickly deliver and visualize this information.

3. Keep it simple. When people look at data visualization in tools or presentations, each visualization needs to be snackable, as not everyone wants to stare at a chart for minutes to understand what the data are telling them. Data need context and the visualization must quickly answer people’s specific questions.

4. Start basic and expand over time. The more visualizations you give to people, the less important each chart or data point will be. Gather specific questions you want answered, design charts or infographics to help answer those questions, and leave room for enhancing the dashboards over time.

Source: Peter Chobanian, Ogilvy Health

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The Minto Pyramid Principle: Structuring Tool for Data Storytelling

The Minto Pyramid Principle, also referred to as the McKinsey’s Pyramid Principle, is a tool used to process and structure large amounts of information to convey a story, message, or presentation without omitting important details. The principle is to cut to the chase in written texts or presentations. This ensures that the audience’s attention is captured and that a riveting story can be created that’s easy to remember and understand.

Source: Barbara Minto

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Marketing Research: The Key to Crafting Compelling Brand Stories

Esin Izat
Manager and Leader, Marketing Research Practice, Beghou Consulting
A compelling brand story can improve a therapy’s public perception, giving it a leg up in a competitive marketplace. Creating a compelling brand story requires in-depth understanding of target customers via marketing research. But, some life-sciences companies lack the necessary resources. When we recently surveyed orphan drug commercial leaders, 40% said they had limited resources to conduct marketing research studies. This is a problem because marketing research is one of the most effective ways for companies to map the competitive landscape and understand the attitudes of physicians, payers, and patients toward their therapies. Further, the findings of a marketing research study can help a company identify the best positioning in the marketplace for its therapy. For example, should it promote the therapy’s efficacy? Or should it tout the therapy’s mild side effects? A marketing research study can help provide the answers to these questions.

It’s crucial to get the brand story right. After all, everything from a go-to-market strategy to brand elements, such as color schemes and logos flow out of the brand story. It’s also important to understand that less is usually more when it comes to crafting a brand story. A therapy can’t be everything to everyone. Instead, the company needs to identify the few advantages that resonate most with its target audience and lead with those in its marketing efforts. Trying to be the best brand for everyone can dilute the brand story and its impact.

Marketing research remains important for a brand team, even after the therapy launches. The team should survey target customers about their experiences with and perceptions of the therapy. Using marketing research studies to keep a pulse on the perception of the drug in the marketplace can help the team make appropriate and timely adjustments to strategy.

Consumer products companies have long focused on developing compelling brand stories. It’s time for life-sciences companies to follow suit. A brand story that resonates with physicians and patients can position the therapy for success in a competitive market.

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