Conference listening
Hear the entire conversation around a meeting, not just the parts your team walked into.
Shortlist it, send it over — we come back with the shape we'd actually recommend.
What conference listening actually is.
A structured read of everything being said around a meeting, rather than a clippings file. Clinician and society posts, the programme and abstract content, congress press, competitor announcements and the debate that follows them, brought into one taxonomy so themes can be counted rather than remembered.
It runs in three windows. Before, so the plan targets what the field is already arguing about. Live, so you can see during the days themselves what is actually landing and re-aim the team. After, for the settled read: which themes moved, who owned the conversation, and what your competitors got credit for.
- Pre-conference brief on the live debate and where to aim
- Daily live read during the meeting, with what changed
- Theme and sentiment analysis by topic and by voice
- Competitor share of voice and message traction
- Named voices driving each theme, with the source posts
- Written post-conference analysis and the tagged dataset
Add the pieces you'd want and we'll build a shortlist you can review, reorder and send over. No pricing wall, no commitment — we come back with what we'd actually recommend, including anything you don't need.
Approach, modules, delivery.
Move through the tabs to see how the work runs, what it's made of and what lands at the end.
Inputs
- The topics, therapy area and competitor set the listening is scoped to
- Named voices worth tracking: clinicians, societies, patient organisations, media
- The conference programme and abstract content for the meeting itself
- Any existing message framework, so traction can be read against intended messages
- The listening window: pre, live and post, agreed up front
Method
Public conversation is collected across the agreed window and sources, then de-duplicated and tagged against a single taxonomy so themes can be counted rather than recalled. Volume, sentiment and share of voice are read by topic, by voice and by competitor, and clustered into themes with the source posts retained so any claim can be opened. The pre-window read tells the plan where the argument already is. The live window is reported daily, so the team can be re-aimed while the meeting is still running. The post window gives the settled read: which themes moved, who owned them, what your competitors got credit for, and which of your intended messages actually travelled.
Assumptions
- Only public conversation is used, and it is handled within the platform terms and the applicable privacy and pharmacovigilance rules.
- Anything resembling an adverse event or product complaint is routed to your PV process, not analysed as sentiment.
- Named-voice analysis is about what was said publicly, not about profiling individuals.
Limitations
- Clinical conversation is unevenly public. Absence of volume on a topic is not evidence the topic does not matter.
- Share of voice measures visibility, not persuasion. It is read alongside the field's own account of the room.
- Automated sentiment on clinical language is directional; anything load-bearing is human-reviewed before it is reported.
Think this belongs in your scope?
Add it alongside anything else that fits, then send the shortlist over. We'll reply with the shape we'd recommend — sequence included, and the parts we think you can skip.
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