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

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.