In today’s rapidly evolving market, businesses can no longer afford to operate on assumptions. Success lies in listening — deeply, strategically and systematically — to the Voice of the Customer (VoC). VoC represents the captured insights, expectations, preferences and aversions of customers. It offers a powerful, data-backed perspective on what matters most to end users and why. In the consulting and business analysis landscape, VoC analysis is not merely a tool but a strategic compass, guiding organizations toward sustainable value creation, customer-centricity and innovation.

The need for VoC: bridging gaps with insight

Every product, service, or strategy begins with a fundamental question: What does the customer need? In the world of scientific research, where precision and efficiency are paramount, the tools scientists use, whether it's a Laboratory Information Management System (LIMS), an Electronic Lab Notebook (ELN), or a custom data analytics platform, must do more than just function. They must fit seamlessly into the workflows of those who rely on them daily. And that’s where the Voice of the Customer (VoC) becomes not just valuable, but essential.

• VoC allows organizations to:
  • Uncover and address inefficiencies in current offerings.
  • Identify hidden problems and improve customer experience.
  • Drive process improvements and innovation.
  • Fine-tune strategies with evidence-backed feedback.

Over the years, we've seen firsthand how meaningful engagement with end users: scientists, lab technicians and R&D teams, can transform the trajectory of a software development project.

One example that stands out involved the development of a next-generation ELN platform. Early conversations with lab users revealed that while existing tools captured data effectively, they often disrupted the natural flow of experimentation. Users struggled with clunky interfaces, redundant data entry and poor integration with analytical tools. By listening closely to these frustrations, the need was clear: prioritize intuitive design and interoperability. The result was a solution that felt like an extension of the lab bench rather than a digital hurdle.

VoC as a strategic asset

The true power of VoC lies in its ability to transform anecdotal feedback into actionable intelligence. For consultants and analysts, it forms the very foundation of business cases, root cause analysis, and change management strategies. VoC bridges the external market reality with internal decision-making.

It’s also a risk mitigator. Before large investments are made in product development, strategy pivots, or operational revamps, VoC serves as a planning, ideation, conceptualization and validation tool. Does the customer really want this change? Will it solve their pain point—or create a new one?

Imagine you're a scientist working in a fast-paced research environment. You’re juggling multiple experiments, managing complex datasets and navigating a patchwork of digital tools that don’t always talk to each other. Then comes news of a major upgrade to your internal bioinformatics platform—complete with AI features and a shiny new UI. It sounds promising, but will it actually make your work easier?

This is where the Voice of the Customer becomes more than a buzzword. When organizations take the time to listen—to really understand what scientists and lab users need—they often uncover a different set of priorities. It’s not always about AI or aesthetics. It’s about performance, interoperability and integration with lab instruments. The ability to move seamlessly from data capture to analysis without breaking your workflow.

In many cases, what starts as a vision for cutting-edge innovation evolves into something more grounded—and more impactful—once users are brought into the conversation. Investments shift from surface-level enhancements to backend improvements that actually support the way science happens in the real world.

So, the next time a new tool is announced or a platform is being reimagined, it’s worth asking: Was this built with your voice in the room?

Let’s explore practical approaches for obtaining Voice of the Customer input

Direct and indirect techniques: a two-pronged strategy

VoC analysis can be broadly categorized into direct and indirect techniques.

Direct techniques

• 1. Customer interviews
  • One-on-one sessions offering deep insight into individual customer needs and sentiments. In a lab setting, these interviews often uncover workflow bottlenecks or unmet needs that aren’t visible in usage data alone—like how long it takes to log a sample or retrieve historical experiment data.
• 2. Group discussions or focus groups
  • Encouraging collective brainstorming, identifying patterns and validating assumptions. When scientists from different departments come together, these sessions often reveal cross-functional challenges—such as inconsistent data formats or integration gaps between LIMS and ELN systems.
• 3. Surveys and questionnaires
  • Useful for quantitative analysis and large-scale feedback collection. For example, a quick survey across R&D teams can highlight which software features are most valued—or most frustrating—during assay development or data review.

Indirect techniques

• 1. Reviewing client feedback
  • Existing reviews, complaints, or testimonials provide unfiltered insights. Feedback from lab users—whether shared during audits, post-implementation reviews, or even informal chats—often points to recurring usability issues or overlooked features.
• 2. Query support notes
  • Technical or customer support logs often highlight recurrent issues or confusion points. Support tickets from scientists struggling with data exports or system timeouts can reveal where documentation is lacking or where the UI needs simplification.
• 3. Analytical methods
  • Studying product usage patterns, churn rates, or Net Promoter Score (NPS) trends. Usage analytics might show that certain modules in a LIMS are rarely used—not because they’re unnecessary, but because they’re too complex or poorly integrated into daily lab routines.
• 4. Competitor benchmarking
  • Understanding how customer needs are being met (or missed) by competitors. Scientists often compare tools informally. Benchmarking helps identify where your platform falls short—or excels—in real-world lab environments, such as faster data processing or better instrument compatibility.

In practice, every direct technique is followed by indirect validation and vice versa — an approach that brings objectivity and holistic clarity to VoC data.

Multi-channel listening: the complex yet crucial framework

Effective VoC analysis doesn’t happen in silos. It’s a multi-channel, multi-stakeholder process that brings together insights from:

• Sales and marketing: Understanding expectations from early customer interactions.
• Technical SMEs and consultants: Interpreting feasibility and technical alignments.
• R&D and product development: Infusing customer feedback into design and innovation cycles.
• Market strategy teams: Using VoC to shape pricing, positioning and competitive messaging.

VoC is not just a customer service tool, it is a cross-functional strategic component. When aligned well, it informs long-term growth strategies and fosters market differentiation. It reflects not just innovation, but the collective voice of its users. Built around real workflows, it encourages strong user adoption and delivers immediate impact.

Implementation: a stepwise approach

What works well is a structured VoC roadmap:

• 1. Define objectives: What exactly do we want to learn from the customer?
• 2. Select techniques: A mix of direct and indirect methods based on industry and scale.
• 3. Data collection: Across departments, platforms and touchpoints.
• 4. Analysis & theming: Identifying patterns, pain points and opportunities.
• 5. Strategic integration: Feeding insights into design, delivery and strategy teams.
• 6. Validation and feedback loops: Recheck, retune and reaffirm with the customer.

Listening with purpose

In the consulting domain, success isn’t just about knowing more — it’s about knowing what truly matters and having deep technical knowledge of the domain. VoC empowers organizations to do exactly that. It transforms ambiguity into clarity, assumptions into facts, and ideas into impact.