IT

HCP PROFILING & MEDICAL PERSONAS

Not lists of doctors. Models of behaviour.

For years HCP profiling stopped at three variables: specialisation, geography, prescribing potential. Merqurio applies AI to its proprietary engagement data to build personas that describe how the physician informs themselves, what activates them and what role they play in their professional network.

The point is not to know who the physician is. It is to know how they decide, and how to reach them accordingly.

From demographic segmentation to behavioural segmentation.

Traditional segmentation classifies HCPs with static criteria: discipline, location, prescription decile. These are useful, but they describe the physician as they were, not how they behave.

Engagement data — opens, clicks, content consumed, preferred channels, response times, event participation — tells a different and more actionable story. AI applied to this data produces dynamic segmentations: behavioural clusters that update over time instead of crystallising into a static record.

The question is no longer "which specialty do they belong to?". It is "how do they inform themselves, what engages them, where are they reachable and with what message?".

What Merqurio does

Merqurio builds Medical Personas® from proprietary data of real behaviour, not from marketing assumptions.

Predictive behavioural segmentation

Algorithms applied to the proprietary HCP database and engagement data build segmentations more advanced than traditional criteria: digital behaviours, response history, therapeutic interests, level of involvement, potential role in professional networks. The goal is to move from "which doctors to reach" to "which doctors really matter, why they matter and how to activate them".

Building Medical Personas®

Each persona is not a demographic profile, but a model of behaviour: how they inform themselves, on which channels, how often, in response to which content. Personas become the basis for calibrating the message, channel and timing of every activity.

Identifying KOLs and emerging KOLs

AI supports the identification of opinion leaders, emerging profiles and clinical communities, integrating proprietary data, digital interactions, surveys, scientific content and qualified external sources. This makes it possible to read the market dynamically: not only who is recognised today, but who could become relevant tomorrow.

When it helps

When your segments don't explain behaviours

If two doctors in the same decile respond in opposite ways, demographic segmentation is no longer enough.

When you are calibrating message and channel

Behavioural personas tell you not only whom to reach, but with what and where.

When you are preparing a launch

Identifying priority clusters and high-influence profiles in advance reduces dispersion and the cost of error.

When you want to identify emerging KOLs

Before they become evident to the whole market.

Assets

Anyone can segment a purchased database. Not everyone can segment one built on 30 years of real interactions.

Merqurio has over 250,000 doctors registered on the DottNet database and millions of digital and remote interactions. Profiling does not start from bought data, but from observed behaviour: real engagement, not declared.

The difference is not having the doctors' records. It is understanding how they behave.

The difference is not segmenting. It is segmenting on real behavioural data.

Do you want personas that describe how your HCPs really decide, not how you imagine them? Let's talk.

Tell us your case →