Data-Driven Work Cultures: Cision’s Chelsea Mirkin On How To Effectively Leverage Data To Take Your Company To The Next Level

An Interview With Fotis Georgiadis

Connect Outputs to Outcomes: Data savvy organizations know to consider more than just outputs, or activity metrics. In the earned media world these outputs include volume, reach, sentiment and share of voice metrics. While these traditional KPIs remain an important part of any measurement program, leading communications teams go several steps further, connecting earned, owned and paid media outputs with metrics and datasets which indicate a specific behavioral or attitudinal outcome.

As part of our series about “How To Effectively Leverage Data To Take Your Company To The Next Level”, I had the pleasure of interviewing Chelsea Mirkin.

As the head of the Cision Insights Global Analysis, Chelsea oversees a team of 600 analysts, managers and directors in the delivery of research-based consulting to enhance corporate and brand reputation. The work she and her team provide fuels the world’s most admired organizations with actionable insights and strategic guidance to inform communications and marketing strategy. Prior to her role on the leadership team at Cision, Chelsea served as a senior research practitioner and consultant at PRIME Research, specializing in the design, execution, oversight and evolution of global research-based consulting programs across a variety of sectors.

Thank you so much for joining us in this interview series. Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?

After graduating from the University of Michigan, I took on a data entry job for a small German start-up in a field I was not aware existed at the time — PR measurement. It turned out to be a great decision. I worked my way up from data analyst in 2005 to leading the US Operation by 2015 and watched the organization grow from a team of 5 to a team of 150 in the US. It was a blast to be part of such explosive growth and afforded me opportunities to get in front of senior-level, data-driven communications executives at major Fortune 100 organizations very early on in my career. I am thankful to have had wonderful mentors throughout my career who trusted me, believed in me, and taught me how to translate data into actionable insights.

Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lessons or ‘take aways’ you learned from that?

I can’t think of a great example of one specific funny mistake, but when I first started out one of the core ways in which our performance was measured was our efficiency in conducting content analysis. In other words, we were measured on how many articles could we “code” per hour. I was consistently at the bottom of the list. Being a competitive athlete all of my life, I found this underperformance to be extremely embarrassing. More than 15 years later, my manager has pointed out my strong preference to be “extremely thorough,” which I had never properly considered as a core tenant of my working style until now. The same quality that impacted my coding inefficiency has both propelled my success as well as held me back at various points in my career. For instance, this “perfectionist” mindset comes in very handy when you have been asked to interrogate the fidelity of the data in a report a customer is delivering to the board, but it can be a hindrance when you are trying to make decisions at speed. My learning: Sometimes 75% certainty or effort is “good enough.” There can be diminishing returns attached to that extra 25%. There are so many applications for this in the data world. For instance, we so often have to counsel clients facing budget restrictions that they can make the same decisions based on a sample of 2,000 articles that they can on a sample of 10,000 — so long as they choose the most impactful media outlets. Speed and accuracy/thoroughness are often a balancing act — in the data world, and in the working world — and I have learned that perfection can sometimes be a hindrance to progress.

Is there a particular book, podcast, or film that made a significant impact on you? Can you share a story or explain why it resonated with you so much?

My deep appreciation for data as a tool to guide informed decision-making extends from my professional life into my personal one. As a mother of two kids under five, I have very much leaned on the work of Emily Oster, an Economist and author of books which leverage data to address common topics and questions that arise during pregnancy and parenthood. For me, her books have been the antidote to mom guilt and helped me ground my parental decision-making in sound research. And when I am not thinking about work or my small people, you can find me falling asleep 20 minutes into watching the latest binge-worthy Netflix show.

Are you working on any new, exciting projects now? How do you think that might help people?

My team and I, together with our customers, have been very focused on connecting media outputs to reputational and business outcomes. With communicators’ roles and the media landscape rapidly changing and evolving, data-driven consultants need to work harder to bring the pieces together. Most communications and marketing teams are swimming in data, and very often, this data does not link back in a material way to behavioral, reputational, or business shifts.

At Cision, we are trying to answer questions like “Which messages and campaigns have the potential to drive increased purchase consideration amongst intended audiences?” and “How can a company pivot and focus resources on the journalists and influencers that are most likely to reach these audiences?”. It is exciting to have the talent on our team and enthusiasm and support from top clients pushing us to dive further into this space. We are confident that this new product offering will help many communications organizations struggling to connect their function to the broader business conversation. Communications professionals have historically been at a disadvantage in the boardroom, but we believe that this does not need to be the case.

Thank you for all that. Let’s now turn to the main focus of our discussion about empowering organizations to be more “data-driven.” My work centers on the value of data visualization and data collaboration at all levels of an organization, so I’m particularly passionate about this topic. For the benefit of our readers, can you help explain what exactly it means to be data-driven? On a practical level, what does it look like to use data to make decisions?

In simple terms, organizations use data to accomplish one or both of the following objectives — to prove value or to improve performance. We have worked with many clients who look to data to validate a hypothesis or to tell a success story (prove value). When the data disagrees with the gut feeling or does not tell a positive story, some individuals and teams can be quick to dismiss the data and discredit its integrity. On a foundational level, being data-driven requires an openness to leveraging data proactively, and buying-in to the fact that data should be used directionally and iteratively. Companies who do this well feature data as a central part of daily, weekly, monthly, and quarterly team meetings where planning occurs, ideas are discussed, and successes and failures are examined in a safe, transparent, and honest way.

Which companies can most benefit from tools that empower data collaboration?

While any organization stands to benefit from shared data collaboration workspaces — especially in today’s hybrid work environment — I have found that companies who have many different stakeholders and who need to collaborate across multiple business units, markets, and languages are most in need of these types of solutions. Empowering these teams to speak the same data language and to centralize planning and evaluation around a single source of truth is powerful, and unlocks greater opportunity for best practice sharing. We have helped so many teams move from a fractured, regional data ecosystem to a global, central dataset grounded in consistent methodology, common key metrics frameworks and, ultimately, a shared vision of “what good looks like.”

We’d love to hear about your experiences using data to drive decisions. In your experience, how has data analytics and data collaboration helped improve operations, processes, and customer experiences? We’d love to hear some stories if possible.

We spend roughly one-third of our lives at work, so it is only natural that with so much time and energy invested, it can become an emotionally-charged environment. My favorite thing about data is that it can immediately neutralize emotion. We once had a CEO client who was adamant that a specific top financial publication was biased toward their company. This client was refusing to engage or take interviews and asked a colleague to confront the outlet and its top beat journalist. The colleague knew this would lead to missed opportunities and diminished credibility. They commissioned our organization to study the presence of systematic bias in media coverage in this specific outlet, in relation to other top US financial sites. Through a combination of a journalist survey and content analysis, we were able to definitively prove that there was no discernable bias in the coverage. After being presented with the findings, the CEO reversed their position, saving the colleague from a potentially damaging confrontation with this top publication.

Has the shift towards becoming more data-driven been challenging for some teams or organizations from your vantage point? What are the challenges? How can organizations solve these challenges?

There is a common phrase tied to teams or organizations who are reluctant to adopt data into their way of working: FOFO, or “fear of finding out.” We have actually had Chief Communication Officers tell us that they would rather forgo being a proven success than run the risk of being a proven failure. Organizations need to reorient their culture and their teams around the idea of failing safely — and then be ready to measure and report back on what is working/not working, iterate, and adjust.

Ok. Thank you. Here is the primary question of our discussion. Based on your experience and success, what are “Four Ways a Company Can Effectively Leverage Data to Take It To The Next Level”? Please share a story or an example for each.

In my years of working with leading communications functions at F1000 organizations across all markets and industries, I have noticed that the teams who effectively measure the impact of PR and communications share the following four attributes in common:

  • Leverage a smart combination of Tools, Talent, and Technology to Drive Actionable Insights: There are no shortage of tools or data available. The right talent will know not only how to use these tools effectively to drive toward the most meaningful outputs, but also how to provide guidance to transform the data into meaningful, tactical advice that can be leveraged to improve outcomes. Ideally, the talent deployed understands the function they are supporting, as well as the industry the company operates within. With many of our most sophisticated customers we employ an “embedded consultant” model where our resource is tasked to sit in on all internal meetings in order to anticipate research-driven needs. These resources commonly leverage social media monitoring platforms, where they vet and flag topics rising in interest or importance to facilitate crisis-mitigation as well as opportunity identification. In one such instance, we helped a popular credit card brand detect a surge of acceptance issues arising with specific types of merchants (in this case taxis and convenience stores in NYC) before the issue rose to critical levels. The brand was able to respond quickly with further support and education dispersed through their merchant network to mitigate the issue and reduce complaints.
  • Develop Key Performance Indicators (KPIs) that Align with Overall Business Objectives: Leading data-driven teams know the importance of aligning on a shared definition of success with key stakeholders — both within and outside their direct functional responsibility. When we started working with a major enterprise technology company in 2018, the objectives focused purely on driving a market-leading share of voice in earned media. The problem with this approach was two fold 1) Metrics drive behavior, and departmental leaders focused purely on quantity of media coverage vs. quality 2) Because the results were so singularly-focused, and because the goal was not reasonable given historical performance, it was impossible to demonstrate the effectiveness and value of the department’s contributions to the overall business objectives. The result? The department was finding itself fighting to justify budget. We counseled the organization to shift its focus to achieving higher key message penetration in core media we determined to be most effective in reaching target audiences, which aligned well with the company’s intentional shift to be known for it’s newer and more innovative products. The result is that this drove more focused and thoughtful behavior across the teams, and more control over the department’s ability to demonstrate success at the ELT-level. It also allowed us to streamline our measurement program, focusing less on clip-counting, and more on deep measurement in target media. With the repurposed funds, we were able to expand upon the measurement program and we are now connecting the media outputs to the changes in awareness and behavior resulting from the team’s efforts, bringing the department even closer to demonstrating the impact of it’s efforts in shifting the more tangible reputational and business outcomes, and helping secure a flat budget heading into a year where many face budget cuts.
  • Connect Outputs to Outcomes: Data savvy organizations know to consider more than just outputs, or activity metrics. In the earned media world these outputs include volume, reach, sentiment and share of voice metrics. While these traditional KPIs remain an important part of any measurement program, leading communications teams go several steps further, connecting earned, owned and paid media outputs with metrics and datasets which indicate a specific behavioral or attitudinal outcome. This capability unlocks so much potential to optimize for improved performance. At a leading B2B tech company, for instance, we’ve connected earned media data to website visits and software downloads to uncover the specific media outlets most likely to generate interest amongst core target audiences (CIOs and CTOs). Leveraging this data, we were able to help the company narrow their 3,000-title publication list to the 150 that had the highest penetration amongst these C-Suite executives. This more narrow focus helped the company “do more with less” and drove improved results for a fraction of the cost.
  • Use Their Measurement Solution to Prove value AND Improve Performance. One final element that sets data-driven organizations apart is that they think of measurement not only as a report card that proves value, but as an ongoing tool to improve performance over time. They bring in research and data not only at the end of a campaign, event or initiative, but at the beginning to inform strategy as well as in the middle to make adjustments along the way. With one banking customer we were advising, we were asked to research the way in which a data breach was being discussed in organic social conversations prior to articulating a response to the incident. Why? Because the company rightly anticipated this same phrasing being used by their customers when leveraging search engines to research the impact of the breach. They were able to “SEO” their own press release response, ensuring it rose to the top of search engine results, and therefore improving upon likelihood that their indented messaging would rise to the top for those seeking additional detail. The result was a significant reduction in critical commentary when compared to prior incidents, and a much shorter reputational recovery period — sentiment leveled off to normal levels within 24 hours (vs. the 48+ hours observed previously).

The name of this series is “Data-Driven Work Cultures”. Changing a culture is hard. What would you suggest is needed to change a work culture to become more Data Driven?

Change starts from the top. We rarely see data-driven teams succeed without a supportive executive-level team member setting the tone for the organization, and aligning teams around a set of measurable objectives which are meaningful (connected to business goals that resonate and have buy-in from the CEO down to the individuals on the team) and reasonable (achievable, rooted in historical trends).

The future of work has recently become very fluid. Based on your experience, how do you think the needs for data will evolve and change over the next five years?

I expect that the demand for the convergence of datasets from all areas of the business will only continue to accelerate. In our part of the world, we’re seeing this appetite emerge across communications and marketing teams in the form of omnichannel measurement. The lines between earned, owned and paid are becoming increasingly blurred, forcing communications and marketing professionals (and the consultants who support them) to become fluent in the language of data across all of these channels in order to provide actionable insight.

Does your organization have any exciting goals for the near future? What challenges will you need to tackle to reach them? How do you think data analytics can best help you to achieve these goals?

We are fully poised to support our customers through the evolution I’ve just discussed above. Not only are we looking at meaningful and statistically significant ways to connect outputs to outcomes on behalf of our customers, but we’re leaning in on the data-as-a-service (DaaS) model to empower our customers to have more flexibility and agility to plug our data into their own BI environments. We are also investing heavily in upskilling our teams to be fluent in all data languages across all channels to allow us to consult our customers more holistically in this converging space.

How can our readers further follow your work?

You can follow me on my personal LinkedIn page, and the work of my team on Cision’s official social channels: LinkedIn, Facebook, Twitter, Instagram, and our resources page.

Thank you so much for sharing these important insights. We wish you continued success and good health!


Data-Driven Work Cultures: Cision’s Chelsea Mirkin On How To Effectively Leverage Data To Take Your… was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.

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