Ninety-nine percent of CFOs and CIOs at global organizations believe that analytics are important to their business, according to research by the Financial Times Group. The problem is that 75 percent say they have trouble using data to make decisions. Part of this challenge stems from a business setting in which data is vast and easily accessed but also disparate and lacking the contextual power of a narrative.

Sales professionals today are uniquely positioned to seize on this challenge when they learn to combine the persuasiveness of data with the familiarity of story structure in selling. Here, we break this process down into three parts: sourcing data, organizing data and developing a strong narrative around the data.

Sourcing Data That Compels

More decisions today arise from data. In fact, researchers from McKinsey and MIT found that “companies in the top third of their industry in the use of data-driven decision making were, on average, 5% more productive and 6% more profitable than their competitors.” Analytics buoy trust in solutions.

Moreover, the influential power of data is critical in a world where overcoming the status quo is an increasing challenge, as our research has found. In an increasingly risk-averse setting, solutions must satisfy a more rigorous review from numerous stakeholders. Using the right set of analytics helps satisfy this need.

Finding the right supporting data means asking incisive questions that reveal the customer’s needs. Incisive questions also reveal which measurements will offer the most authority when it comes to illustrating the upside of a solution. In this case, articulating the gains to be realized creates momentum toward a purchase.

Identifying the most relevant data requires the sales professional to:

  • Have a clear idea of the customer’s challenges
  • Understand how well the data communicates the gains offered by the solution
  • Source in-depth, relevant information that speaks to those challenges

Once the sales professional has asked the right questions, he or she can focus on the right data. “With too much information, people’s decisions make less and less sense,” explains Dr. Angelika Dimoka, the director of the Center for Neural Decision Making at Temple University.

Sales professionals must focus on concise, research-backed evidence to support the value of the solution. Strong statistical evidence shapes opinions. However, remember that statistics can backfire. Even if the customer agrees with your position, he or she may recoil if supportive information comes from a dubious source. This outcome is called the “Boomerang Effect.” Handling data carefully demonstrates the sales professional’s conscientiousness in analyzing information.

Interpreting the Data

Sales professionals must start with the end in mind. That is, they must not only consider what data they’ll bring to the table, but they must also ensure that they can provide a compelling analysis of that data. Data without interpretation is no more useful than a saw without a carpenter.

Sales professionals can identify the data that will focus and compel customers by considering iconic memory – the stage of memory that’s very short-term. Imagine standing in a field at night. Everything is dark, but then, a bolt of lightning illuminates everything for just one second. This fleeting image is like our iconic memory.

The data salespeople use is a lot like this flash of light. Therefore, it’s important to use visual cues to underscore the data and make the message and meaning clear. How do they do this? The answer is cognitive load.

Cognitive load theory asserts that learning falters when it demands too much working memory capacity. The Journal of Instructional Science has provided some guidelines for preventing three types of cognitive overload:

  • Intrinsic load is low when the concept can be learned in isolation. As some researchers have illustrated, learning a list of words exhibits low intrinsic load, whereas learning the syntax and grammatical rules that connect those words represents high intrinsic load. Sales professionals can use this concept by choosing data points that don’t require a complex foundation of preexisting knowledge.
  • Extraneous load refers to the medium used to convey an idea. Some concepts are made clear with visuals. Using descriptive language to explain how a propeller works, for example, demands a greater extraneous cognitive load than simply showing a picture or short animation.
  • Germane load is the degree to which an individual must interpret and classify the information. Salespeople should break up material into pieces so that the buyer can more effectively absorb the content and find its meaningful place among what he or she already knows.

Communicating the Data

While narratives differ across genres, each adheres to the same core structure. What’s important is that each stage of the story leads to the next. This flow is important in sales, because the rep needs the solution to fit seamlessly into the story. This skill alone will set a sales professional above the rest, because today, information is often dispersed without coherence, analysis or meaning. It comes fragmented, rarely coalescing into a whole.

To rise above this problem, sellers should use conventional story structure to tie their data together into a continuous presentation. In this structure, each piece relies on what came before it. If a seller moves back and forth among topics, the narrative will not make sense, and he or she will confuse the buyer. In other words, a story structure keeps listeners engaged because it moves. Therefore, sales professionals should not labor over one part, but they should make their point, and then move to the next piece. As Pulitzer Prize-winning playwright David Mamet explains, “Every scene should be able to answer three questions: ‘Who wants what from whom? What happens if they don’t get it? Why now?’”

This template is as relevant to the sales professional as it is to the playwright. In fact, economic professor Bruce Wydick shows that identifiable stories incite action more often than statistical stories. Data is necessary for legitimizing the solution, but story is necessary for promoting the solution.

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