Here you’ll find a description of the conditions that will define the future of communications, and several tips on how to excel. This article is part of our special Future of Measurement issue.
The rock star of the future of communications will not be a wordsmith, a former journalist, a master of event planning or—god forbid—a “people person.” She or he will be a data-driven Cassandra.
For those of you who weren’t forced to take Greek mythology back in third grade, Cassandra was a hot young lady that Apollo set his eyes on. In order to lure her into his bed, Apollo gave her the power of prophesy. But then she refused his offer, so he spat a curse into her mouth that ensured that no one would ever believe what she foretold. Today “Cassandra” is shorthand for someone whose accurate prophecies are not initially believed by those around them.
Data enables you to predict and design the future.
Those of us with research and data at our finger tips have the Cassandra-like ability to see into the future. Unlike Cassandra, however, we can make people believe us. Depending on how good our research is and how well we tell the story.
In earlier times, data was too hard to collect, so most PR people based their recommendations on experience and gut instinct. Today, best-in-class organizations have years of PR, social media, and digital data that they use to determine the best ways to launch a product, deflect a crisis, or get a message across.
In each of the following examples data is used to predict and design an improved future:
- Several of my clients study their goal conversions in Adobe Omniture and/or Google Analytics to plan for their next quarter. They look at the monetary value and engagement rates and establish a cost/benefit ratio of every event, initiative, and press release to set priorities for the following quarter. (See my video on how to set up goal conversions in Google Analytics.)
- Another client established that her media quality index (here’s how you can design your own) correlated highly with goal conversions. She then analyzed her monthly scores for each reporter and media outlet, and then assessed the internal efforts that went into improving that score for each outlet. As a result, her department could target journalists more effectively, and overall media quality and messaging steadily improved. Not surprisingly, she recently leveraged those results into a big new job.
- Yet another client tracks a customized “Trust Index” for every event they do to determine which are most likely to increase trust in the organization. Thanks to that data, they spend less money on ineffective events and steadily increase trust in the organization.
That’s what a PR star looks like today, and that’s what the future of communications will look like as well. The reason is simple. Data is getting more accessible and plentiful. But, remember, it’s all meaningless unless you do three things with it:
- Analyze it in depth to find the insights.
- Use those insights to make changes to improve your processes.
- Tie the results of those improvements to the bottom line.
So how do you get to be a PR star of the future?
First, learn your way around data. While a data analytics degree might help, it isn’t necessary. (Frequent readers might recall that I have a degree in History and Asian Studies. The last and only class I ever took that involved statistics was Psych 101.) You do need some basic stats chops. But what is far more essential is a working knowledge of your business and mission: how it makes money, how it defines success, who buys your products, and what motivates the target audiences. It’s by using your data to combine and contrast these business details that you will gain insights.
Second, you must be persistent. Alan Kelly is a good example. Over a decade ago he used a ton of data to develop his Playmaker Systems theory of influence strategy. Although his system is directly applicable to PR, most of us were skeptical when it first came out. It seemed a far-fetched notion. But now, a few years later, it turns out he’s on the money most of the time.
Persistence is especially important with today’s general attitude attitude towards news and data. It’s a distrustful time. Data and science and bad news are frequently dismissed as “fake news.” You’ve got to make sure your data and analysis are solid, and then stand up for them.
Finally, embrace failure to find insight. Too often, PR and marketing folks people don’t want to talk about bad news. But that’s often where the most important insights are.
When I audit the metrics for my clients I always review past reports. Surprise surprise—everything is 90% wonderful. The people who produce such perennially glowing reports do not have a sunny future. That’s because leadership today has grown increasingly skeptical; too many reports show all the chart lines going up and to the right.
If you think your data should make you “look good” or always support your arguments, then you are badly mistaken. The purpose of data is to drive better decision-making and improve the performance of your organization. So, the first thing you need to do is sort your data from worst to best.
For instance, if you’re reviewing survey research data, then look at the detractors: those that don’t agree with your messages or the ones that rate you the worst. That’s where you’ll find the opportunities for improvement.
Future of communications case study: Examine the worst to get the best out of your data.
I recently had a client for which the first take on their survey results was much in line with industry benchmarks. However, the Cassandra in me wasn’t comfortable. I felt a disconnect between those results and what we’d heard from focus groups.
So, I dug deep into the data, looking past the obvious variables of gender and age, and studied the crosstabs of variables like “length of time with the company,” “how do you define leader,” and “job function.” My inkling was that I would find some sort of brewing catastrophe. Probably among the fastest growing cohort, the millennials.
But I was wrong. It turned out that employees who had worked at the company the longest were the most skeptical of leadership’s messages. And millennials, who had recently joined the company and gone through orientation, were totally on board with management’s priorities. My catastrophe hunch was on the mark, though: several very senior leaders had zero credibility with their staffs.
So I cut all the “happy news” slides out of my presentation, and turned it into a 5-minute elevator pitch that ranked results from worst to best. The point was not how much data I had (and yes, I started out with 105 different slides and crosstabs). The value in all that data came from tossing out 85% of it and focusing on the numbers that really mattered.
That’s the sort of persistent, embrace-the-worst data winnowing that will be required of the stars of the future of communications. See you in the future.
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The image at the top is a detail of the painting “Cassandra” by Evelyn de Morgan.
