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Digital transformation in financial services has accelerated dramatically, placing new pressure on analytics teams to deliver faster insights and more meaningful guidance. In this conversation, digital analytics pioneer Sharon Flynn shares how to build data fluency across the business, tackle implementation challenges, and create value at scale through empathy, governance, and agile thinking.
With over 15 years of experience in analytics across media and financial services, Sharon Flynn has seen firsthand that success with data is not just technical. It is cultural. The moments she is most proud of are not tied to dashboards or models, but when teams begin to explore data independently and confidently—when insights become second nature.
Helping teams shift from feeling intimidated by analytics to integrating it into everyday decision-making is, in her view, the true sign of progress. For financial services in particular, it means enabling colleagues who may have never touched a reporting tool to find clarity in their customer data and understand how their choices affect performance.
This cultural shift does not happen by accident. It requires analysts to lead with empathy, understand creative mindsets, and position data not as a limiter, but as a powerful enabler.
In today’s cloud-first environments, it is easy to collect everything and decide later what matters. But Sharon emphasizes the importance of focusing on insights rather than complexity. Her mantra is clear: “We do insights here—we don’t do math.”
A lengthy PowerPoint filled with complex visualizations may impress, but it does not always inform. A strong insight should be human-readable. It should clarify what worked, what did not, and what the next best action is. Simplicity is not a lack of depth—it is clarity of purpose.
This mindset helps organizations avoid analysis paralysis and reinforces the idea that analytics is not just a reporting function. It is a strategic partner.
Sharon points to two common but under-discussed challenges in marketing and digital analytics.
1. Oversimplifying the analyst’s role
While democratizing access to insights is important, it is a mistake to equate that with simplification of the analyst’s role. Good analysts bring years of experience in data modeling, governance, and tool mastery. That expertise is critical, especially in large organizations with complex infrastructures.
Tools like Google Analytics and Adobe Analytics are powerful—but without subject matter experts guiding implementation, usage, and interpretation, their potential is lost. Organizations must understand that while access can be broad, stewardship must be deep.
2. Treating implementation as a one-time project
Another misconception is that analytics implementation is a one-time task. In reality, it is a continuous operational activity. Tools change, tags break, new channels emerge, and customer behavior shifts.
Sharon stresses that scaling analytics only works when governance is embedded and experts are connected to both the data collection point and the distribution point. That is where long-term value is created, and that is how analytics investments generate ROI.
One of the biggest challenges financial institutions face is adapting to the rapid shift in customer behavior. Many customers who were previously branch-first are now forced into digital channels. This changes how organizations must think about funnels, behaviors, and digital design.
Sharon highlights that digital teams are being asked to do much more than they were pre-pandemic. The traditional separation between public-facing marketing websites and secure customer portals is blurring. Now, the digital experience must reflect the trust and reassurance that once existed in physical branches.
Understanding this new reality requires behavioral data, empathetic design, and agile strategy. It also demands that marketing, analytics, and digital product teams collaborate in new ways.
In a fast-changing environment, agility is not a buzzword—it is a necessity. Sharon advocates for what she calls strategic triage: breaking work into manageable parts, placing emphasis on upfront planning, and being humble enough to iterate after launch.
This approach helps teams act fast without overpromising, ensures testing is grounded in behavioral insights, and allows organizations to make data-informed decisions even when certainty is scarce.
It also underscores the emotional dimension of digital experiences. Financial customers are often under stress. While data cannot replace human connection, it can help organizations walk in their customers’ digital footsteps—and design more caring, responsive experiences.
Sharon sees several shifts on the horizon.
First, teams will consolidate. Roles and tools will align more tightly around solving core problems—understanding acquisition, engagement, and outcomes.
Second, organizations must prepare for a future with less reliance on cookies. Whether through stricter regulations or platform-level changes, the rules of targeting and personalization are already evolving. Companies that depend too heavily on third-party data will need to rethink their models and prioritize first-party trust.
Finally, digital analytics will require new thinking. Teams will need to be comfortable moving the kitchen while cooking, as Sharon puts it—changing their stack, their structure, and their processes while still delivering day-to-day results. Success will depend not on picking the right tool, but on asking the right questions.
Digital analytics in financial services is no longer a back-office function. It is now front and center in shaping customer experience, product development, and digital transformation. Sharon Flynn’s perspective serves as a reminder that great analytics work is equal parts technical rigor and cultural empathy.
To drive value, teams need to demystify data, focus on insight over output, and build scalable processes around trusted expertise. The organizations that succeed will not be the ones that move the fastest—but the ones that move with purpose, humility, and a clear understanding of their customers’ evolving needs.
Collecting large amounts of data is easy, but generating actionable insights requires clarity and context. Focusing on insights ensures analytics drives decisions rather than overwhelming teams with information.
Empathy helps teams design digital experiences that reflect the needs and emotions of customers, especially during periods of stress. It ensures that data is used not just to optimize performance, but to create meaningful, human-centered interactions.
Analytics implementation is never truly complete. Tools evolve, customer journeys change, and reporting needs shift. Treating implementation as continuous ensures long-term data accuracy and value.
By breaking down internal silos, aligning marketing and product teams, and using behavioral data to understand emerging segments. Organizations must rethink how websites, apps, and support functions serve different types of users.
Organizations will consolidate analytics teams, shift toward first-party data strategies, and prepare for a post-cookie environment. Success will depend on adaptability, trust, and clear alignment between tools, teams, and goals.