In an era defined by the overflow of information, the modern enterprise is no longer merely a provider of goods or services; it is a repository of vast, untapped narrative potential. Almost every contemporary corporation, from multinational conglomerates to niche startups, collects data as a fundamental part of its operations. While these metrics are traditionally utilized to streamline logistics, optimize sales funnels, and monitor financial health, a growing cohort of public relations professionals is discovering that these same figures can serve as the foundation for high-impact storytelling. By shifting the focus from internal business intelligence to external cultural insights, companies are transforming raw numbers into headlines that capture the attention of major news outlets and the general public alike.
The transition from data collection to data storytelling requires a fundamental shift in perspective. According to Will DeGirolamo, who spearheads B2B and enterprise communications at Yelp, every organization possesses unique data points that can be leveraged for media outreach. Whether the information pertains to transaction histories, platform usage patterns, or broader consumer behavior, there is almost always a story hidden within the spreadsheets. However, the challenge for communication teams lies in identifying which data points resonate with the current cultural zeitgeist and how to present them in a way that provides genuine value to journalists and readers.
The Human Element: Moving Beyond the Spreadsheet
The primary hurdle in data-driven PR is a fundamental misunderstanding of what constitutes a "story." Michael Kaye, the head of communications and partnerships for a diverse portfolio of brands at Match Group—the parent company of dating giants such as Tinder, Hinge, and OkCupid—argues that the biggest mistake brands make is assuming that data itself is the narrative. In reality, data is merely the evidence; the story is the human behavior that the data reveals. For a journalist, a statistic about a million users is less interesting than a statistic that explains how those million users are changing the way they interact with the world.
Kaye emphasizes that the most successful data stories are those that shed light on cultural shifts or explain existing social conversations. A poignant example occurred in 2019 at OkCupid. By analyzing user responses to in-app questions, the communications team noticed a significant uptick in how climate change influenced dating compatibility. Users were increasingly prioritizing environmental alignment when choosing potential partners. This insight was not just a corporate metric; it was a reflection of a broader societal shift toward environmental consciousness among younger generations.
The resulting media coverage was extensive and enduring. The story was picked up by outlets ranging from The Hill to The Guardian, with more than 500 articles eventually referencing OkCupid’s findings. Notably, the data remained relevant for years, with journalists still requesting interviews and updates as late as 2023. This longevity underscores a critical rule in data storytelling: when a brand provides data that acts as a window into human psychology or social trends, it transcends the traditional news cycle and becomes a part of the cultural record.
Establishing Authority Through Consistency and Longevity
While one-off data points can lead to viral moments, the most significant long-term benefits come from establishing an ongoing series of data-driven reports. This strategy allows a brand to move from being a "one-hit wonder" to becoming a definitive authority in its sector. By consistently releasing data on a specific schedule, companies create an "appointment" for journalists, who begin to anticipate the findings and rely on them for their own seasonal or annual reporting.
Yelp has successfully implemented this strategy with its "Fastest Growing Brands" and "Most Loved Brands" reports. Now entering their third year of publication, these reports are based on the aggregate activity of millions of users across the Yelp platform. According to DeGirolamo, these two reports alone have generated over 100 earned media articles. More importantly, they have functioned as a "proof of concept" for the media. Reporters now recognize Yelp as a reliable source for consumer trend data, leading to a steady stream of inbound requests throughout the year. When a journalist is working on a story about small business health or retail trends, they are now more likely to reach out to Yelp for supporting data.
Similarly, Match Group is preparing to launch its 15th annual "Singles in America" study. This longitudinal approach provides a unique advantage: the ability to track changes over time. By looking at 15 years of data on sex, dating, and relationships, Match can provide insights that no other company can replicate. This proprietary nature is the "gold standard" of earned media. When a company owns a dataset that is exclusive and covers a significant duration, it becomes an indispensable resource for researchers and reporters.
The Evolution of the PR Role: From Messenger to Data Analyst
The integration of data into the PR workflow is also changing the necessary skill sets for communication professionals. There is a growing debate within the industry regarding the level of technical proficiency required for modern PR pros. Julianne Rowe, senior director of communications at Yelp, suggests that while not every communicator needs to be a data scientist, they must be "data-literate" and highly collaborative. The role of the PR expert, in this view, is to act as the bridge between the data science team and the media. They must ask the right questions to uncover the "why" behind the "what" and understand which insights will actually resonate with an audience.
However, Michael Kaye of Match Group advocates for a more hands-on approach. He argues that every communications professional should strive to become a data expert in their own right. Kaye, who did not have a technical background before joining Match, sought training from his company’s data science team to learn how to use the tools and platforms required to extract insights himself. This self-sufficiency allows for a faster turnaround and ensures that the person identifying the story is the same person who understands the nuances of the data.
The rationale behind this shift is practical. Data science teams are often overwhelmed with requests related to product development, financial forecasting, and user acquisition. They may not have the time or the journalistic instinct to comb through datasets looking for PR "hooks." When communications teams take the lead in data exploration—supported by the technical oversight of data scientists—they can move with greater agility and find stories that might otherwise be overlooked.
Strategic Implementation: A Chronology of Data Storytelling
To successfully turn company data into content, organizations typically follow a structured timeline that moves from raw collection to public dissemination:
- Identification of Variables: Comms teams work with data analysts to identify which internal metrics align with current news trends (e.g., inflation, remote work, social movements).
- Hypothesis Testing: The team looks at the data to see if it supports a specific narrative. For example, "Are people spending more on experiences than goods this quarter?"
- Contextualization: The data is compared against external benchmarks or historical internal data to determine if the finding is statistically significant or culturally relevant.
- Simplification and Visualization: Raw data sheets are converted into "clean," easy-to-read charts and infographics that journalists can easily embed in their stories.
- Pitching and Distribution: The story is pitched not as a brand advertisement, but as a "cultural insight" or "economic indicator," with the brand positioned as the credible source.
Broader Implications and the Future of Corporate Transparency
The trend toward data-driven storytelling reflects a broader shift in the relationship between corporations and the public. In a "post-truth" era, audiences and journalists are increasingly skeptical of traditional corporate messaging and "spin." Data provides a level of objectivity and transparency that traditional press releases lack. When a company says, "We are the best," it is an opinion. When a company says, "Our data shows a 40% increase in user interest in sustainable products," it is a fact-based observation that contributes to a larger economic or social understanding.
Furthermore, this approach has significant implications for Search Engine Optimization (SEO) and brand longevity. Unlike traditional news which may have a short shelf life, data reports often become "evergreen" content. They are cited in academic papers, white papers, and follow-up news stories for years, creating a continuous stream of backlinks and brand mentions that bolster a company’s digital authority.
As artificial intelligence and machine learning continue to make data analysis more accessible, the barrier to entry for data storytelling will continue to lower. However, the human element—the ability to find the "heart" within the "hard numbers"—will remain the most critical factor. The companies that succeed will be those that treat their data not just as a tool for internal efficiency, but as a public service that helps the world understand itself a little bit better. By following the lead of innovators at Yelp and Match Group, PR professionals can move beyond the role of mere messengers and become essential contributors to the global cultural conversation.
