Innovation often starts in the wrong place. Too many companies lead with features, technology or speed instead of focusing on who they are building for. In my last article, I touched on why keeping the customer at the heart of every decision matters when it comes to driving transformation across a company. That principle becomes even more important in product innovation.
Throughout my career, I’ve seen innovation efforts fall short because they didn’t begin with a clear understanding of the customer and the full context of their journeys. Those experiences have taught me valuable lessons and changed how I approach product development, how I listen to customers and how I align teams around what we are actually trying to solve for.
Throughout my tenure in the payments space, I’ve seen three key misconceptions about customer-centric innovation. It’s time we dispel these myths.
Myth #1: B2B, B2C and partnerships are separate categories
For years, the popular approach to product innovation was solution-first thinking. Companies would build the product they thought the market needed, release it and then discover who it would (and wouldn’t) work for. When their customer base encountered roadblocks or new needs, the company would tack on new capabilities ad hoc. B2B, B2C and partnerships were treated as distinct innovation categories.
This approach put the cart before the horse and created unnecessary complexity. Separating the three key customer groups led to disconnected innovation strategies that were reactive rather than intentional.
Today, successful companies look at the full picture of who they serve, not just the individual using the interface. They embrace a holistic, customer-first methodology from the start.
In payments, we speak about three key stakeholders: the entity sending the payment, the entity receiving the payment and the payment facilitator connecting them. Solve for only one of the three and you will miss important dependencies.
To make better product decisions, it’s essential to understand the entire ecosystem. Achieving this deep understanding requires patience and a commitment to genuinely listening to customer needs.
We applied this approach at CSG Forte as we looked to expand our services for the healthcare sector, an area notorious for its outdated payment systems. We wanted to make sure we were solving real-world challenges that providers and payers faced. To do so, we engaged directly with actual practitioners, treating them not just as sources for referrals, but as true collaborators in the solution-design process.
After numerous conversations, we unearthed a key pain point: healthcare providers need a consolidated business view, not fragmented point solutions. Their existing tools (POS, practice management, payment and insurance systems) didn’t connect, forcing staff to reconcile multiple, isolated systems.
This feedback changed the entire trajectory of our innovation, partnership and product creation process. We needed to create a one-stop payment platform that integrated the POS device with existing practice management tools and streamlined insurance payments through partnerships. The result was a unified environment to manage all consumer, co-pay, insurance, balance-due and HSA/FSA payments.
In-depth input from physicians was essential, but it was only one part of the equation. Their feedback mattered most when paired with the realities of patients, staff, insurers and the underlying payment rails. Only by seeing how all of these pieces fit together could we make decisions that served the entire ecosystem rather than optimizing for a single group.
Myth #2: You can gather customer feedback with a simple survey
In reality, feedback without structure can create as many problems as it solves.
I learned this the hard way. At a previous company, we conducted a customer survey to understand the needs of our core stakeholders. The survey responses indicated that merchant customers wanted a specific product add-on to accelerate invoice creation. The request made sense and we assumed the demand was broad enough to justify development. However, it failed to see widespread adoption.
What we missed was the nuance. Although the survey was well-intentioned, its small sample size and poorly formulated questions inadvertently skewed customer responses.
This oversight stemmed from a communication breakdown between siloed teams. Each group prioritized its own mandate rather than the complete, end-to-end context. As a result, crucial insights and feedback were lost in translation due to varying interpretations, leading to misdirected resources toward features that later had to be scrapped and rebuilt.
That experience taught me that cross-functional alignment is a prerequisite for meaningful innovation. Research, product and engineering need a shared view of the problem, hypothesis and target customer. They all must be in the same boat, rowing in the same direction, checking and balancing each other’s ideas along the way. And in the end, whoever owns delivery of the feature must close the loop with the customer and confirm: “Is this what you meant? Is this what you need? Will you actually use this?”
Skipping this last step is what derails product innovation for many companies. Most teams run in a straight line. The missing closed-loop feedback mechanism means errors in understanding are never corrected and unnecessary or low-value features get shipped.
I see this constantly in the fraud space. After a fraud incident, teams are (understandably) quick to tighten thresholds to prevent a repeat occurrence. The problem is that in the absence of the closed-loop feedback, the rules stay in place long after patterns change or new fixes become available.
Over time, outdated rules pile up. Customers experience unnecessary friction and teams struggle to understand why certain transactions are being flagged. There is no systematic review, no cleanup process and no clear way to evaluate what rules should remain.
This is where customer-centricity becomes a discipline. You have to be willing to revisit decisions, eliminate outdated mechanisms and stay grounded in how choices impact your customer.
Myth #3: Hype is inherently overrated
Oversight and structure become even more important when companies try to balance hype with pragmatism. I’ve seen teams jump on trends in hopes of positioning themselves as early innovators. I’ve also seen teams take too narrow a view of what technology can enable, missing opportunities that could better reflect the needs of the customer.
The truth is, there is no right answer. Hype can lead to unexpected wins. Pragmatism can anchor strategy. The job of leadership is to recognize the value in both and leverage them with intention. Build with a clear understanding of future needs, but never lose sight of what will best serve the customer today.
Nothing illustrates this tension better than AI.
AI is particularly beneficial in situations demanding complex, tailored outputs to enhance the user experience. For example:
- Security and fraud: Companies increasingly depend on AI to counter the AI-driven tactics of fraudsters, who use advanced models to mimic customer behavior and bypass traditional controls. AI can spot abnormal activity much faster than a human and adjust thresholds in real time. Combined with customer insights and behavioral context, it reduces false positives and keeps the experience smooth for legitimate users.
- Hyper-personalization: In the automotive industry, AI-powered infotainment and driver display systems learn from the driver’s habits to create better experiences. For example, as I approach my car in the morning, it recognizes my keys, automatically suggests the fastest route to my workplace and plays my favorite morning news podcast — all without any manual input. That feeling of being understood makes consumers loyal to the brand.
- Customer service automation: AI can help brands respond to customer needs in multiple languages and handle complicated questions in real time, easing the burden on support teams while improving overall response quality. CSG research shows that consumers want customer service AI to use clear, helpful language (51%), resolve issues on the first attempt (58%) and transfer seamlessly to humans (62%) when necessary — particularly when it comes to high-stress scenarios like a declined payment, delayed order or service disruption.
- Behavioral monitoring: Real-time behavioral monitoring and adaptive feedback loops behind the scenes can catch subtle issues early and tailor experiences dynamically. Payment method recommendations, checkout guidance and even channel selection can be personalized based on past activity, which is hugely impactful in driving customer loyalty.
But when teams get swept up in the hype and lose sight of the full experience, over-indexing on AI can sacrifice other aspects of development and design.
It’s important to be intentional about where AI does and doesn’t belong. In some products, using AI simply wouldn’t add value. For example, we had considered — and scrapped — an AI use case to generate tailored financial reports. In this context, regulatory compliance and timing matter far more than personalization, so AI would have created complexity without addressing the customers’ most pressing needs. At the end of the day, the innovations that work are the ones that simplify the customer’s experience.
Challenging myths in innovation
Leaders must challenge the myths that derail product innovation and ensure every product, process and policy decision ladders back to a clear understanding of the voice of the customer.
Customer-centricity is a mindset that guides how teams operate and a framework that shapes how they make decisions. We should balance ambition with discipline. We should stay open to hype without losing clarity about what customers actually need. Future-proofing a business has never been about predicting every change but rather staying rooted in the people we serve. When everyone shares the same goals and the same definition of success, innovation becomes coherent and connected.
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