A conversation exploring the real-world application of analytics in banking
As bank and credit union leaders build strategies for the next level of institutional growth, the role of analytics is intensifying. The growth conversation is no longer about what to measure, but how to act on data. Industrywide, there is a more active environment, with M&A banking transactions on the rebound and values increasing 25% year-over-year, according to PwC. Even more, there were $15.1B in U.S. bank deals announced in the first two months of 2026. Against this backdrop, institutions are rethinking their physical footprints and brand identities to respond to consolidation and shifting customer expectations.
In this next phase of data-led growth, analytics becomes less about dashboards and more about decision-making, with financial institutions navigating complexity and prioritizing investments. This shift is redefining how growth is measured and managed across the organization. The need to align an institution’s physical presence, market opportunity, and human behavior creates markers for how brands position themselves to build sustainable growth. In a recent conversation, Nick Mentel shares how these dynamics are playing out in real-world strategy and how institutions can translate insight into action.
The first and most obvious factor is geographic overlap. In a perfect scenario, two financial institutions complement each other with strong brand equity in different areas without duplicating physical presence. But often, that’s not the case.
When you do see overlap, the evaluation becomes more nuanced. It’s not just about distance; it’s about whether those locations serve the same audience and whether they align with the acquiring institution’s strategy. A suburban-focused credit union, for example, may struggle to integrate branches in dense urban cores if the demographics and customer expectations are fundamentally different.
There’s also a scalability consideration. If an acquisition introduces too many branches or too much complexity at once, it can overwhelm the network. That’s where analytics helps define thresholds around what’s manageable, what’s strategic, and what creates long-term value.
That’s where the balance of quantitative and qualitative analysis really comes into play. On the quantitative side, we’re looking at core performance metrics – households, account volumes, cross-sell rates, transaction volumes, and overall financial efficiency. We’re also evaluating cost structures, including staffing and occupancy.
But numbers alone don’t tell the full story. Qualitative factors matter just as much. What’s the condition of the physical space? Does one location offer a better customer experience or stronger visibility? Are the product offerings aligned with the institution’s future direction? Ultimately, you’re rarely comparing two identical assets. Even branches a few blocks apart can have very different strengths. The goal is to understand both performance and potential and recognize when one of those locations likely won’t make the cut.
This is where analytics starts to intersect directly with strategy and design. It’s not a linear handoff, but a collaborative process. When we’re determining what type of branch a location should be – whether it’s a flagship, a neighborhood branch, or a convenience format – we’re using data to understand transaction volumes, deposit mix, and lending activity across different lines of business.
But that data has to align with the experience the financial institution wants to deliver. You might have a high-performing location, but if the physical layout is built entirely around transactions, it may not support advisory conversations or relationship-building. So, data informs the decision, but design brings it to life. The most effective networks are those where analytics, strategy, and experience are working together, not in silos.
Brand is a critical layer, but it’s often evaluated differently than performance metrics. Formal brand equity studies are typically handled by third-party partners, but we do conduct internal research, especially around naming overlap and market saturation. It’s not uncommon to see multiple institutions in the same region using similar naming conventions, which can dilute differentiation.
In M&A scenarios, brand decisions can become even more complex. You may have legacy equity tied to one name, while the acquiring institution is trying to unify under another. Understanding how those brands are perceived – and where confusion exists – is essential to making informed decisions.
One example is working with institutions that have undergone acquisitions and are now managing highly complex networks, sometimes across multiple states and lines of business. In those cases, a surface-level analysis isn’t enough. You have to understand each submarket, each branch, and how they contribute to the broader network. Clients often have deep institutional knowledge of their locations, and that context is incredibly valuable.
We’ve also worked on projects that go beyond traditional network optimization, like building performance scorecards for regional leadership. Instead of just comparing raw numbers, we’re evaluating performance relative to market opportunity. That creates a more accurate picture of how each region is truly performing.
It’s essential. There are always factors that don’t show up in the data. For example, a branch might underperform on paper, but it holds significant legacy value in the community. It may serve as a brand anchor or a “billboard” presence that reinforces trust and visibility. In those cases, the decision isn’t whether to close the branch – it’s how to optimize the branch. That’s why there’s no substitute for truly understanding the client and their network. Analytics can guide the conversation, but it doesn’t replace it.
One of the biggest is the continued rise of fintechs. They’ve proven they can gain traction, but they haven’t fully replaced traditional financial institutions – especially when it comes to building long-term, high-value relationships. That’s where banks and credit unions still have a clear advantage. The question is how they evolve to maintain it.
We’re also seeing convergence. Fintechs are exploring bank charters, while traditional institutions are integrating more digital capabilities to keep customers within their ecosystem. That dynamic is pushing everyone to rethink their value proposition. From an analytics perspective, the challenge and opportunity means staying grounded in the fundamentals: understanding your network, your markets, and your customers at a deep level. There’s no shortcut for that.
Analytics is only valuable if it leads to better decisions. It’s not about having more data – it’s about using that data to understand tradeoffs, prioritize investments, and align your network with where you’re going as an institution.
The most successful organizations are the ones that combine data with insight, strategy, and experience. That’s where analytics moves from being informative to transformative.
From data to decision-making, Adrenaline’s retail analytics services help banks and credit unions drive sustainable institutional growth. Contact us today to see how we can help your institution build a roadmap for branch network optimization.
Adrenaline is an end-to-end brand experience company serving the financial industry. We move brands and businesses ahead by delivering on every aspect of their experience across digital and physical channels, from strategy through implementation. Our multi-disciplinary team works with leadership to advise on purpose, position, culture, and retail growth strategies. We create brands people love and engage audiences from employees to customers with story-led design and insights-driven marketing; and we design and build transformative brand experiences across branch networks, leading the construction and implementation of physical spaces that drive business advantage and make the brand experience real.
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