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4 minute read
A rep opens the pre-call brief before a visit. It says the oncologist has opened two emails about a dosing update, visited the safety page last week, and is likely to want to discuss switching patients from a competitor. The rep walks in prepared. Afterward, the call note records that dosing and switching were covered.
Was it a better conversation for the physician? The brief and the call note can't say. Both were written from the brand's side of the room, and that gap matters for anyone responsible for pharma sales force effectiveness.
This post looks at what pre-call intelligence shows, what it misses, and how brand teams can measure whether it is working.
What is pre-call intelligence?
Pre-call intelligence is the briefing a pharma sales rep receives before an HCP visit. It is built from CRM history and engagement data, and it predicts what the physician is likely to want to discuss. AI tools now generate many of these briefs, often as part of a broader next best action program.
What pre-call intelligence is built to do
Pre-call planning helps a rep decide which messages to lead with, which content the HCP has already seen, and which questions might come up. Next best action engines apply the same logic across channels. They trigger an email, a call, or a piece of content based on each HCP's own behavior rather than a fixed calendar, so no two physicians see the same sequence.
For field teams with limited time in front of each physician, that targeting has real value. The open question is what it changes for the HCP on the other side of the call.
Why the call note can't show whether the call was better
A pre-call brief predicts interest from behavior. A call note records what the rep says was covered. Both are the brand's account of the interaction. Neither captures the physician's view: whether the call felt relevant, which messages they remember, or whether it answered the question they brought into the room.
A rep can follow the brief exactly and still miss what the physician wanted to talk about. As rep access tightens, each call carries more weight, and a well-documented call that misses the physician's real question is an expensive miss.
Predicted interest and stated interest are different measures
Behavioral signals show what an HCP opened, clicked, or downloaded. They can't show what the HCP wanted to ask and didn't find. A physician who opened a dosing email may have done it to confirm what they already knew, while their real concern sits somewhere the brand's content never reached.
The only way to separate predicted interest from stated interest is to ask the physician. That is the HCP's side of the conversation, and it sits outside the CRM loop by design.
Get all five questions. Pre-call intelligence is one of five gaps in how pharma measures omnichannel HCP engagement. Download the full whitepaper to see the other four and what answering each one takes.
How to measure whether pre-call planning is improving rep conversations
Measuring pre-call intelligence means reading the call from the HCP's side and comparing it against what the brand already records. Five steps make that practical:
- Ask HCPs about the call soon after it happens. Capture whether the call felt relevant, which messages they recall unprompted and when prompted, and how prepared the rep seemed.
- Compare recall against the call note. The note shows which messages the rep delivered. Recall shows which ones landed. The difference between the two is where pre-call planning has room to improve.
- Compare segments, or before and after a rollout. Read HCP-reported relevance and recall for calls made with and without the brief, or before and after pre-call AI is introduced.
- Include the HCPs who rarely engage. Briefs built on engagement data are thinnest for physicians who don't open, click, or visit. Models trained on engagers inherit the same blind spot, so the sample needs to cover the full target list.
- Track it wave over wave. Repeating the read lets teams adjust brief logic and message choice within weeks, instead of waiting for prescription data that arrives months later.
This is the approach behind promotional effectiveness tracking: surveying HCPs after rep interactions so call quality is read from the physician's side, alongside the activity data the brand already holds.
What the dashboard sees, and what the HCP's view adds
|
Moment |
CRM and engagement data |
HCP-reported research |
|
Before the call |
AI brief predicting topics from behavior |
What the HCP wanted to discuss |
|
During the call |
Rep note of messages covered |
Which messages the HCP recalls |
|
After the call |
Next triggered email or action |
Whether the call felt relevant and prepared |
|
Over time |
Engagement trend for engaged HCPs |
Recall and relevance across the full target list |
One of five questions your promotion dashboard wasn't built to answer
Pre-call intelligence is the first of five measurement gaps covered in the whitepaper. The other four follow the same pattern: what the dashboard sees, against what only the HCP's view can answer.
- What is your competitor saying to the same HCPs?
- What did HCPs see outside your channels?
- Did engagement change belief and intent to prescribe?
- Are you reaching the HCPs who don't engage?
Take the next step
Is your pre-call intelligence improving the conversation, or only the paperwork? Five Questions Your Promotion Dashboard Wasn't Built to Answer by Chitra Alagarsamy, ZoomRx, sets out the five questions to settle before your next promotional budget moves, and what answering each one takes.
If rep conversations are the gap you want to close first, Explore Promotional Effectiveness Tracking (PET)
Reads rep interactions from the physician's side: message recall right after the call and again at later touchpoints, plus how prepared the rep seemed.
See how promotion connects to prescribing
Links promotional activity to prescribing outcomes across rep and omnichannel promotion.
Frequently asked questions