Most teams still rely on engaging familiar names when strategizing. These are experts who headline conferences, publish frequently, and are on everyone’s list. This approach makes sense on paper; these experts are credible and easy to defend internally. But many teams are facing similar issues: despite working with high-profile experts, real impact is limited, highlighting the gaps in traditional key opinion leader profiling 

The root cause of this problem is simple: visibility is being treated as a proxy for influence. But in today’s dynamic landscape, being seen often does not equate to real decision-making power. The experts who are actually shaping conversations are quieter, less public, and embedded in trusted networks that rarely appear in rankings, something often overlooked by conventional methods for identifying key opinion leaders. 

This is where KOL influence mapping becomes a critical need. Instead of asking who is most visible, it asks who is most visible, it asks who is listened to, and who connects with others to change direction. It views influence as dynamic, situational, and networked, supported by in-depth HCP influence analytics rather than surface-level metrics. 

In the sections below, we will unpack how influence really works, where traditional KOL models fall short, and how to identify experts who actually shape outcomes using more data-driven KOL identification. 

Influence as Contextual, Not Universal 

One of the biggest mistakes in any medical affairs KOL strategy is the search for a single, all-purpose expert who can be everywhere and handle everything. But influence depends on the situation. But an expert who carries weight in the first may be irrelevant in the next. 

The voices that shape early policy discussions are rarely the ones that drive day-to-day adoption. An academic who influences guidelines may have little impact on prescribing behaviour, an insight that is only gathered through detailed pharma expert mapping. 

Audience matters just as much. Experts are received differently by different groups. Peer credibility does not automatically translate to regulatory trust. Media visibility can help shape the public narrative but may weaken credibility within scientific circles. And patient trust often sits with entirely different figures rather than institutional authority. Gathering pharma thought leader insights, thus, becomes an impossible task. 

Treating influence as transferable across audiences leads to predictable figures, the right experts speaking to the wrong room. 

The implication is clear: there is no universal KOL hierarchy. Influence is situational and appears at specific moments, with specific audiences, and in specific contexts. So, mapping it requires moving away from static rankings towards a more flexible view. 

From Podiums to Power Networks 

Real influence today doesn’t flow outward from podiums. It circulates within networks that are hardly visible in the limelight. But these groups shape how people think long before marketing efforts are initialized, making KOL engagement prioritization far more complex than what list-based approaches can handle. 

Peer-to-peer influence matters even more. Clinicians trust other clinicians who face the same constraints. Policymakers listen to peers who understand political nuances. Researchers are influenced by the thinkers whose ideas they cite. These exchanges carry significant weight. 

What makes these networks powerful is trust. They listen more closely when advice comes from someone who understands their reality. Influence is, therefore, not about persuasion but credibility built over time. This is why visibility-based strategies struggle. They focus on who can amplify a message and not on who shapes thinking. 

Practical Framework for Identifying Experts Who Matter: Using konectar 

Finding the right experts is not about putting together longer lists or refining rankings. It requires a structured way to see how influence actually moves. konectar is built for exactly this: mapping real influence, not surface visibility. 

Step 1

Start with a goal, not an expert. Before looking at names, define the goal. Is it to shape early thinking, support adoption, or influence policy? Planning a goal helps anchor the identification process in reality.  

Step 2
Rather than scanning public profiles, map how experts are connected. By visualizing who sits at the center of a trusted network, teams can efficiently tier experts and make engagement plans. 

Step 3
Distinguish between experts who can broadcast messages and those who shape opinions. This step helps identify experts whose views are acted on and not just heard. Assess when each expert matters most to help guide decision-making. 

Step 4
Use the mapping to inform action. Prioritize relationships, tailor engagement style, and align outreach with how each expert operates within the ecosystem. Influence mapping only creates value when it informs what teams actually do. 

Conclusion: From Knowing Names to Understanding Influence 

Influence today is harder to see, shifts fast, and is more contextual than most influence strategies allow for. The experts who matter most are not always most visible. This is why static lists, annual updates, and visibility-based rankings are falling short. 

A structured approach to KOL influence mapping changes the equation. It replaces assumptions with clarity, helping teams engage smarter and focus efforts where they can genuinely shape outcomes. 

Move beyond guesswork and legacy KOL models with konectar. The AI-powered healthcare management platform can bring structure to the influence mapping process. Explore the functionalities of konectar here or book a live demo for a walkthrough of konectar capabilities here.