PR Technology, Data and Insights

Igniting a Positive Return on Your Communications Investment

Mark Weiner

• Publisher: Kogan Page
• Year: 2021
• ISBN:
  9781398600416
• Edition: 1
• Topic: Commerce
• Subtopic: Relations publiques

Data, technology and insights have forever changed the public relations and corporate communications function. Failure to adapt is more a matter of willingness than inability. Now, technology, data and insights inform more meaningful objectives and elevate performance evaluation. The result is a positive return on PR investment, reduced reputational risk and optimal efficiency. By ignoring these essential assets, PR professionals risk losing executive attention and organizational investment. While "building buzz" or "breaking through the media clutter" may have been adequate measures of success in the past, the top executives who fund and evaluate corporate communications expect much more, including a quantifiable and positive return on PR investment.Leaders assume that corporate communications and PR professionals already understand the fundamentals of business, and they expect an ability to contextualize PR objectives, outputs and outcomes in the language of business. PR Technology, Data and Insights helps communications professionals understand the purpose-built technologies, data assets and actionable insights available to them while sharing best practices to apply these assets for improved PR performance over time, versus objectives and against competitors.Using case studies from industries as varied as financial services, technology, travel, automotive and more, along with best practice examples from Adobe, Mastercard, Southwest, Ford and other world class organizations, PR Technology, Data and Insights shows professional communicators how to optimize technology, lead with data, quantify PR's ability to convert public relations outputs to business outcomes, and deliver insights that empower executive decision-making.

PART ONE

Technology, Data, and Insights

01

Technology

I consider any technology that fosters better communication and engagement to be a form of public relations technology whether purposely built for public relations or not. From the printing press, telephone, and IBM Selectric typewriter to today’s artificial intelligence, technology helps modern communicators operate at the pace that business demands. At present, communicators access purpose-built tools to help them at every stage of the public relations continuum. These tools enable PR people to micro-target stakeholders, develop strategies, create and distribute content, execute campaigns, and evaluate performance in real time, with quality and in ways that contribute to meaningful business outcomes. In this chapter, I provide an overview of these technologies and shed light on how to manage them, along with useful guidance for PR technology decision-makers. Communications technology enables public relations professionals to accomplish their objectives more efficiently and more consistently by removing rote work. Free from time-consuming routine tasks, communicators enable themselves to expend more time and energy on the uniquely “human” aspects of the profession, such as creating and managing compelling campaigns, counseling clients and senior executives, and interacting with various stakeholders including journalists, influencers, policymakers, employees, and customers. At the same time that technology sparks efficiency in the completion of routine tasks, it still requires expert oversight to think about the application, to manage the technology, and to execute at the right time.

While communications technology quickly evolved, the day-to-day responsibilities for effective public relations haven’t changed: the need to manage stakeholder lists; the need to disseminate information; the need to monitor media; the need to understand our stakeholders… all these responsibilities live on. The technology of the past faded away but the essentials remain. Gone may be the days when PR technology meant your Rolodex for targeting; printing and mailing for release distribution; scissors for media monitoring; and tabulations of clip count, circulation, and advertising value equivalency for PR evaluation, but PR professionals continue to perform similar tasks today.

Most of the technologies we discuss in this chapter are purpose-built for the professional communicator, but two overarching trends affect much of business as we know it: Big Data and artificial intelligence. The terminology is quite common but the number of true PR applications are surprisingly rare. Through the lens of corporate communication, let’s briefly explore each development.

Big Data

Big Data is the name applied to advanced technology that enables extremely large datasets to be analyzed and applied to generate more holistic organization-wide decision-making. Big Data systems are the culmination of many small data streams, of which PR data is one (although often overlooked). As organizations seek answers to business questions related to customer demand, competitive intelligence, and community trends, news and social media deliver unique data which, when combined with other information, helps to achieve business solutions.

When Southwest Airlines, one of the world’s most admired airlines and Consumer Reports’ top carrier for on-time performance, faced declining results in 2015, the company introduced a multi-disciplinary task force including representatives (and data) from finance, customer service, and operations to explore what was happening, why it was happening, and what needed to be done about it. The communications team contributed PR data from traditional and social media sources that referenced flight delays, on-time, and early arrival. The PR data stream was married to a variety of other data streams, including the Department of Transportation rankings, weather data, customer complaints, and “number of minutes delay per passenger” data to assess performance. With the addition of PR’s input, the airline gained better context of its situation. Beyond the Big Data analysis the company’s internal communications reinforced the importance of individual contributions to improve on-time departure. Because of the integrated Big Data analysis and the programs enacted as a result (including internal communications initiatives), on-time performance rose five basis points and the carrier rose two places in the Department of Transportation rankings. The following text and illustrations tell the Southwest story from the Institute for Public Relations white paper entitled “The Big Data revolution.”¹

• Background: Southwest Airlines integrated its communications data stream to solve a big business challenge. As one of the top domestic carriers of passengers and their bags in the United States, Southwest Airlines has a history of more than 40 years as an efficiency machine. For many years, it held the top spot in the U.S. Department of Transportation Monthly Air Travel Consumer Report as the best on-time domestic airline. Several years ago, those statistics began to slip, as the airline was working to bring together the schedules of Southwest and its newly acquired subsidiary, AirTran Airways. The airline also pivoted to a more long-haul scheduled airline with a greater number of connecting itineraries, all of which created a more complex operating environment. As a result, Southwest struggled with on-time performance (OTP). It is important to note there is a direct correlation between poor OTP and customer complaints, and a low net promoter score. Using a Big Data strategy, the business improved its OTP, a result of new programs and procedures in place to help improve turn times, originator flights, etc, along with diligence and dedication by Southwest employees.
• Strategy: An enterprise-wide effort began with many moving parts to attempt to improve the airline’s operational performance. Initiatives like “Start Strong” were implemented to ensure the first flights left on time, thereby creating a better operational day. The communications team was asked to participate in the enterprise effort and contribute data to a comprehensive view of operation for a holistic view of on-time performance. Then, a cross-functional team analyzed the data to assess trends more accurately with the traveling audience (i.e. complaints, customer service calls, refunds etc).
• Execution/Implementation: Southwest’s ops recovery team pulls information monthly from various teams and departments to get a holistic view of business performance and OTP, specifically in the areas of operations, customers, and finance. As part of the monthly ops recovery team report, under the customer umbrella, the communications team supplied data and insight on news coverage and real-time social conversation (sentiment, topics, and volume) that mentioned OTP directly, or, as customers often reference it, “flight delay,” “on time,” or “late flight.”
• Effectiveness of assignment: The communications data included the number of news and social media mentions daily, daily sentiment, sample comments, and examples of news coverage. The communications analysis drew attention to major news announcements on a given day, like Department of Transportation rankings, or an event that may impact on-time performance (weather, or ancillary service issues, such as an air traffic control tower shutdowns). This data was married with the number of customer complaints recorded by the customer relations department, as well as the actual arrival delay in minutes per passenger. The resulting data analysis gave the team a surgical view of how external factors could be affecting OTP, and helped reiterate that poor OTP will drive an increase in customer calls and inquiries via the telephone and social channels. Just as important, poor OPT linked directly to downturns in the airline’s Net Promoter Score. The business implemented several new programs and procedures to help combat some of the cause and effect results of sluggish on-time performance. Initial results, based on stats from the Department of Transportation, showed Southwest’s on-time performance rate rose to 72.5 percent, or eighth place when compared to other airlines. This was a significant improvement over June 2014, when OTP was 67.6 percent and tenth place overall.

Artificial Intelligence

In 1950, at the dawn of computerization, the late Alan Turing, British mathematician and logician, first referenced “thinking machines.” The term artificial intelligence came six years later when computer scientist John McCarthy coined the phrase and referenced efforts to develop computer programs that could think and solve problems as well as humans could. While the promise of artificial intelligence for public relations generates great optimism in areas related to audience targeting, media list development, content creation, media monitoring, analysis, and evaluation, verifiable case studies are rare. At the time of writing, thorough research related to the impact of AI on public relations produced few references, most of which referenced marketing promises and mentions of what’s in store for the future. After asking a panel of PR research experts who comprise the membership of the Institute for Public Relations Measurement Commission, the response was clear: lots of excitement but very few verifiable case studies. But even if we found only a few cases, it’s worth discussing the current and future states.

Analytics software entrepreneur and former CCO/CMO Mark Stouse is the CEO and founder of Proof Analytics. On October 28, 2020, we spoke about AI’s utility for PR: “A key attribute of AI is that it ‘thinks for itself’ after having been trained. Through this lens, most of what we see in marketing and communications analytics today is not artificial intelligence at all, but various levels of automation and augmented intelligence.” He continued, “There’s very little that the communications profession can derive from AI at this time, other than basic targeting, given that the profession has done so little with the sort of linear and non-linear regression analytics commonly used to train artificial intelligence and machine learning.” Until the profession commits fully to developing these solutions, it’s clear that AI will continue to be more aspirational than practical for most PR and communications applications.

One peer-reviewed example of artificial intelligence applied to corporate communications came from another expert, PR research pioneer Katie Paine (“never wrong, just early”), who responded with a case study of how she worked with analytics company Fullintel and Texas A&M University professor W. Timothy Coombs to test the ability of an artificial intelligence system to identify crises and recommend responses. Their results show very high accuracy and effective response recommendation. Here’s their story.²

In a 2019 presentation to the International Public Relations Research Conference (IPRRC), the guru of crisis response, Professor W. Timothy Coombs, and his co-author, Elina R. Tachkova, argued that the “preventable crisis” (i.e., one that an organization brings upon itself caused by human error or management misconduct) requires a very different response than disastrous events caused naturally. They suggested that while a lot of research exists to support recommended responses for other types of crisis, there was no research-supported effective response for self-inflicted crises.

At her annual Summit on the Future of Measurement, Paine challenged several media measurement vendors to prove Dr. Coombs wrong by using AI to identify the best response. Gaugarin Oliver, CEO of Fullintel, offered to take up that challenge and the two met with Professor Coombs to map out a research project to present at the upcoming IPRRC 2020. The research would test the hypothesis that AI could be used to help organizations determine the best response to a self-inflicted crisis. An effective response was defined as “the shortest time to neutrality”—the time it took for negative media coverage to be reduced to neutral. The process began by collecting many thousands of articles of traditional media coverage on three recent crises caused by human error and management misconduct (the Boeing 737 Max, the demise of WeWork, and an accidental toddler death). The researchers then applied definitions of different types of responses from Professor Coombs’ Situational Crisis Communications Theory (SCCT). Fullintel taught its machine-learning technology how to identify a crisis, how to classify the type of crisis, and how to identify different responses which included options such as attack the accuser, denial, scapegoat, excuse, justify, apologize, compensate, and no comment.

The next step was to calculate the length of time it took to move negative news coverage to neutral. The algorithm then identified the most effective response that produced the shortest time to neutrality. The research revealed that the shortest time to neutrality was the result of an organization issuing an apology or providing information, and the longest time to neutrality was denial and scapegoating the victim. To test the validity of the findings, the researchers compare...