Projectable Segmentation: From a Surveyed Sample of Hundreds to Mindset Based Targeting for every HCP

The Challenge

HCP segmentation in pharma usually takes one of two forms. Behavioural segmentation, built from claims and secondary data, covers the full physician universe and tells you who prescribes what. Attitudinal segmentation, built from primary research, explains the why behind prescribing but only for the sample that was surveyed. The structural gap is familiar to most insights teams: a PMR sample of 100 to 200 cannot directly inform a target universe of thousands, so the unsurveyed majority often gets targeted on volume alone. Two HCPs with identical prescribing patterns can sit in very different adoption mindsets and treating them the same is a risk that can be avoided, more so in launch situations.

In this engagement, that gap carried real consequences. Only a small share of target physicians was directly surveyed, yet a concentrated subset drove a disproportionate share of new start opportunity. Similar TRx and NRx masked distinct adoption mindsets, from early experimenters to evidence led conservatives. Field teams could identify who mattered by volume but not how to engage them early, and PMR and secondary analytics were running on separate timelines while integration was happening manually at the end only for message prioritization nationally. What was needed was an attitudinal segmentation that travelled with the full HCP universe and reached the field ready for action from day one.

ProcDNA's Solution

Projectable Segmentation Engine

ProcDNA developed segmentation which considers secondary data from the start, as part of the modelling delivering a scalable approach that extends attitudinal segment definitions from a limited PMR sample to the full target HCP universe, giving launch teams mindset-based segmentation at scale rather than a surveyed sample insight locked in a report

Universe Wide Segment Assignment

Every targetable HCP receives a segment, including physicians never touched by the survey, removing the gap between insight and deployable targeting

Attitudinal Insights Inherited at HCP Level

Each projected HCP carries their segment's messaging preferences, decision drivers, and information needs, making the output directly usable for engagement in a single exercise

Behavioral Validation

Built in projected segments are tested against real world prescribing patterns to confirm mindset groupings hold up in observed behavior, flagging areas where alignment weakens

CRM Ready Territory outputs

Outputs delivered as priority ranked targeting lists with segment labels and recommended message angles, formatted for direct CRM deployment and field usages

Quarterly Refresh

Segment assignments update as newer claims and secondary data gathers, aligning targets in a changing post launch market

Impact

Expanded Segmentation Coverage

Extended mindset-based segmentation from the surveyed sample to the full target HCP universe, making segmentation actionable at scale across use cases

Sharper Prioritization

Helped teams identify high priority physicians earlier by combining behavioural signals with likely adoption mindset

Field Activation from Day One

Enabled personalized message selection, and territory level targeting through CRM ready segment deployment at launch

Measurable Early Response

Priority segment HCPs showed roughly 2x higher trial rates in the first 90 days

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