Field notes
What we think is breaking, before the industry admits it.
A point of view on where pharma marketing is exposed: AI search, the MLR bottleneck, message fidelity across channels, and the content supply chain. No recaps of last year. The shift that is happening now, and what to do about it.
- generative engine optimization pharma9 min read
GEO is the new SEO, and pharma is the least prepared industry for it
Generative engine optimization in pharma is not a 2027 problem. HCPs and patients are asking AI, visibility now means Share of Answer, and regulated brands are exposed.
GEOAI searchShare of AnswerAEOpharma marketingRead - AI off-label pharma9 min read
Your approved message is already off-label in the machine answer
AI off-label pharma exposure is real and invisible. When HCPs ask ChatGPT or Perplexity about your drug, the model paraphrases your label and reads off-label. Here is the mechanism.
AI off-labelGenAI compliancepharma regulatoryanswer enginespharma marketingRead - MLR review bottleneck9 min read
MLR was always the bottleneck. AI did not fix it. It made it worse.
GenAI lets pharma make 5 to 10x more content, but the MLR review bottleneck cannot scale to match. The fix is a pre-check before review, not faster review.
MLR reviewcontent velocityAI MLR reviewVeeva PromoMatspharma marketingRead - omnichannel pharma9 min read
Omnichannel measured reach. It never checked whether the machine got the message right
Omnichannel pharma optimized impressions and share of voice but never message fidelity. As HCPs move to AI answers, reach is vanity. Fidelity is the goal.
omnichannelmessage fidelitypharma KPIscontent measurementpharma marketingRead - pharma content supply chain9 min read
The pharma content supply chain was built for a world that is ending
The pharma content supply chain was built to feed human channels. In an AI-answer world, claim fidelity and content reuse become the metrics that matter.
content supply chainmodular contentcontent reuseMLRVeeva PromoMatsRead
See it on your brand
Stop reading about the gap. Watch it close.
Bring an asset and a brand. We will pre-check the asset against the label and show how the machine answers about the brand today.