We’ve used the expression data-driven PR for quite some time now, but haven’t clearly defined it. What does data-driven PR mean? How do you know whether your public relations efforts are data-driven or not? To be data-driven is to make decisions with data first and foremost. In this series, we’ll examine how to become a more data-driven PR professional.
Crafting the Data-Driven Pitch
In the previous post we proved this hypothesis true:
Trustworthy content is linked to more on the web.
How do we take this statement, as well as the supporting data, and transform it from a simple sentence to a data-driven pitch?
The Big Picture
Before we begin the pitch construction, we must understand what the broad story of our hypothesis is in three parts: why, what, and how.
Why is this hypothesis important to our intended audience? If we don’t understand why they should care about our hypothesis, no reporter will ever cover our story. Why will they care – will our pitch help them to save money? Make money? Make their lives better? Entertain them?
The second part is explaining what they need to know. In our hypothesis above, what is trust? What is an inbound link? What is the impact of trust on a website? What are the implications of focusing a marketing program on trust? We must relate the knowledge we need our audiences to have in order to fully believe the why.
The final part of our story is how. How did we arrive at these answers, which we explored in parts 2-7 in this series.
If we don’t have clear, audience-focused write-ups of the above why, what, and how, we need to stop to develop them. We can’t pitch without them.
Finding the Story Framework
Next, in order to create a pitch that resonates with our audience, we will use a framework, a narrative structure that presents our data, analysis, and insight in an orderly fashion. Simply throwing together a bunch of facts is a nearly guaranteed way to lose our audiences’ attention.
Where would we find such frameworks? We have dozens of different story structures built right into Microsoft PowerPoint. If you’ve never played with the Smart Art button, take a look at it. You will see dozens of ways to present information and structure it for easy understanding. We will look at three different structures today that lend themselves well to data-driven storytelling.
The first structure is ask/answer/assess. We begin with our question and prediction to leave this story. Starting with a question that maybe on the minds of our audiences is a great way to capture their attention. We want to incite a verbal or nonverbal response– I have that same exact question too! I also want to know the answer to that question!
The ask section is a paragraph or two. In the second section, the answer, we summarize our methodology for gathering data and the results of our initial analysis. We present how we proved or disproved our prediction. In the third section, assess, we showcase our refinements and what our pitch really means, what it’s all about.
Ask/answer/assess is best suited for data-driven pictures which are informative in nature, teaching someone. If we have asked a question and uncovered new insights, new information the market does not know, this structure is a great way to capture attention.
The second structure is called PEER, developed by Peta J. Abdul. PEER stands for point, explanation, example, recap. In the first section, we lead off with a point, the lead of the story. We start strong with a bold statement, what we want the audience to understand.
In the second section, explanation, we delve into the why, the what, and the how. This is where we present our question, the predictions we made, and how we gathered the data, our methodology. In the third section, example, we walk through our analysis and refinements that prove the point in section one. Finally, we recap the example, explanation and the point in reverse order.
PEER is a great framework not only for teaching but also persuasion. We make a bold claim and stake our pitch on that claim, then backing up with data. If our client wants to draw a line in the sand about their offering, PEER is the structure to use.
The third structure is a simplified version of Joseph Campbell’s Hero’s Journey. This is a true narrative, a true story from beginning to end of that we tell like a story, like an adventure. You know the Hero’s Journey from movies like Star Wars. The hero starts out with a problem of some kind, encounters conflict, and ultimately saves the day.
In our data-driven version of the Hero’s Journey, our reader is the hero. We start with the question and define the problem, then create dramatic conflict by making a prediction and then gathering and analyzing the data to show the prediction to be either true or false. Finally, we arrive at the refinement and resolution of the story. We expand the data or refine our analysis of it until we have a clear conclusion.
In our example from parts 2-7, we are using the Hero’s Journey. We started with a question, defined the problem, and made a prediction. It turns out our prediction was wrong! This creates a dramatic conflict. The way we resolved this conflict is by changing our hypothesis, refining it to look at our data differently.
Whatever we choose for a framework for story structure, the most important point is to remember that our data driven story must have a structure, a way for regular people to follow the data, follow the story, and ultimately understand the point we are trying to make. We must bear in mind that our average audience’s data processing abilities are limited to whatever chart of the day is on the cover of USA Today.
In the next and final post in this series, we’ll examine the process of pitching our data. How do we present it in a compelling way to the influencers, journalists, reporters, and publishers we want to reach?
Christopher S. Penn
Vice President, Marketing Technology