Conquer the “Statistic Scaries” and Optimize Data-Driven Storytelling

While many writers avoid math at all costs, an ability to parse the data is a crucial storytelling skillset.

Katherine Grubaugh
Vice President

First published in PR Daily, a news site that delivers news, advice, and opinions on the public relations, marketing, social media, and media worlds. Reprinted here with permission.

As the world has continued to change rapidly, reporters are looking for by-the-moment data, broken down by cohort or demographic—hyper-specific insights that tie to whatever story they’re writing today, whether it’s credit card debt held by millennials in North Carolina, sentiment on climate change by political affiliation, or years to save for a down payment on a home in Denver, Colorado.

But spreadsheets, crosstabs and weighted averages can seem daunting if not an outright nightmare for some comms professionals. The good news is, if your company or your client has a dedicated data team, researcher or analyst, they can help you navigate the wonderful world of data and provide insights that you can frame up a story that reporters will jump at.

Here are some tips to help you conquer the “statistic scaries.”

1. Work with your data team, not against them.

Alongside your legal counsel, your data team is ultimately responsible for ensuring every piece of number- or insight-based information released publicly is factually accurate and substantiated. It’s a tall task to be 100% correct, 100% of the time—so do your data team a favor, and avoid overusing the question we’ve all asked a dozen times: “Can I say this?”

Take the time to learn what insights are available and readily accessible for your data team. When the available data set analyzes what type of fruit juice your customers are buying and you ask for insights on the milk purchasing behaviors of millennials in upstate New York, don’t be surprised when your email goes unanswered. Understand what is or isn’t bound by customer/partner NDAs, what’s publicly shareable from a data privacy perspective, and what’s an absolute “no” from a legal standpoint.

An hour-long conversation with your data analyst can help you understand what questions can be queried, what their preferred format for requests are (memo-request, bulleted email or quick Slack message) and what a realistic time frame is to turn a request around. Then respect those wishes.
Make friends with your data team, and enjoy a fruitful relationship.

2. They’re just numbers; they won’t bite.

There’s a reason the debate over data privacy is raging: data is powerful.

Data helps us understand the world around us; it can provide concrete proof of something we had a feeling about, and insight into something we didn’t know anything about. Don’t let lingering apprehension from your high school statistics class, or the fact that you never quite understood what a pivot table is for, stop you from digging into a multi-tab spreadsheet.

Make copies of the original and create clean data tables that give you the information you need in a format that works for you. Consider creating a separate tab in your spreadsheet for different demographic breakdowns—for most survey projects, that’ll mean a tab for responses by gender, by age bracket and by location. Creating easily viewable spreadsheets will help your insights shine through more clearly, and be much less overwhelming. Bonus: when you get to start pitching, you’ll have clean and digestible tables to screengrab for reporters looking for “the raw data.”

3. Let the data lead the dance.

Whether you’re working with a researcher, or sifting through Excel sheets on your own, the worst thing you can do is focus on a single hypothesis and ignore what the data has to say. There are many ways to slice the data, if you take the time to look.

If you’re working with your data team, the most important question to ask is what they find interesting or surprising. I once went into a conversation with a data analyst seeking insights on customer purchase behavior of athletic gear and came out with a stat on huge spikes in Lyft/Uber transactions in the hours right before and after the SuperBowl. The “what’s interesting” question is a gold mine; trust me.

If you’re digging through crosstabs—which, by the way, is just a fancy way to say the relationship between two or more numbers—identify a potentially interesting thread, and see it through to the end. When one thread dead ends, start tugging at a different one. Don’t stop once you’ve found one interesting storyline. Go back to the beginning again and exhaust your threads. It’s never a bad thing to have multiple options to choose from, and if you find a story that doesn’t align with your business model (it might provide an interesting counter narrative, but… ) you can also elect not to publish that story at the end.

4. Double-check your work, and triple-check your numbers.

With multiple tabs, spreadsheets and documents open, there’s always the potential for copy/paste issues, rounding errors or reporting inaccuracies—the things of your data teams’ nightmares. The moment a reporter, investor or influencer finds an error in your data report, the entire thing starts to unravel, and a single “oops” can quickly undermine the story and your credibility.

Take the time—every time—to double-check your work, triple-check your numbers, and have someone with fresh eyes fact check your report, press release or pitch before you hit send.