ASA is an AI sales assistant that GetOnCRM is building on Salesforce Agentforce for a pharmaceutical company. Reps ask questions in plain language inside the CRM and get governed answers drawn from call history, plans, profiling surveys and approved documents. It is in build, ahead of a rollout to about 1,000 reps in four markets.
Territory-based access · approved content · audit trail · tracked escalations
Field reps need quick answers before every physician interaction. In practice those answers were spread across several CRM screens and had to be pieced together by hand. That cost preparation time and made it easy to miss consent limits, open suggestions or plan gaps.
| Pain point | Business impact |
|---|---|
| Information spread across many screens | Reps spend time hunting for data before each call instead of planning the conversation. |
| Consent checked by hand | Risk of contacting a physician on a channel they had not agreed to. |
| Territory progress locked in exports | Cycle plan and target attainment needed spreadsheet work to read. |
| Policy and product answers hard to find | Reps searched separate documents for trial data, product information and process steps such as sample submission. |
| Manual escalation | Compliance concerns and medical follow-up requests relied on reps writing and sending notifications themselves. |
The rep asks in plain language.
No menus, no tab hunting.
ASA understands and routes.
It resolves the doctor, product or city, then picks a skill: call history, cycle plan, physician profile, product and policy, or escalation.
The skill pulls from trusted sources.
Salesforce Data Cloud for calls, plans, profiling and consent, and an approved document library for product and policy answers.
A governed answer returns.
Consent is checked, access follows the rep's own territory, and the conversation is traced.
| Use | Example questions | How it helps |
|---|---|---|
| Physician engagement and call history | Show me my calls with Dr. Ahmed this quarter. | Formatted summaries of face-to-face, remote, phone and virtual calls without searching CRM records. |
| Cycle plan and territory planning | How many calls do I have left this cycle? | Plan progress, coverage gaps and visit priorities without opening several dashboards. |
| Physician profiling insights | What did Dr. Silva say in the profiling survey? | Practice details from profiling surveys, ready before a visit. |
| Product, policy and FAQ knowledge | What is our policy on product sample requests? | Answers only from the company's approved, indexed documents, with the source named. |
| Compliance and medical team escalation | Flag a product concern Dr. Chen raised today. | Captured with conversation context and queued for the right team, with retries and audit tracking. |
Each question sets off the same background steps and the answer comes back in the same chat. The examples below are illustrative: names and figures are invented and sensitive details are masked (••••••).
| The rep asks | ASA answers (illustrative) |
|---|---|
| Prepare me for my call with Dr. Ahmed. | Last visit 12 days ago, in person. Discussed Product A and access. Suggestion: share the study update. Consent: email OK, SMS ••••••. |
| How many calls do I have left in this cycle? | 14 of 40 calls left. 6 target doctors not yet visited. Coverage gap in 2 areas, tier ••••••. Cycle closes in 9 working days. |
| What did Dr. Silva say in the profiling survey? | Group clinic with 3 doctors, mostly follow-up patients. Survey answers: •••••• (March). Linked to 4 calls on record. |
| What is our policy on product sample requests? | Plain-language answer from the approved policy library with the source named. If the library does not cover it, ASA says so. |
| Flag a product concern Dr. Chen raised today. | Concern captured with visit context. Details: ••••••. Sent to the medical team queue, status tracked. |
Sure of the match: it proceeds without interrupting the rep.
Fairly sure: it states what it assumed and lets the rep correct it.
Unsure: it asks the rep to confirm.
Several possible matches: it lists them and asks the rep to choose.
In pharma, how and when a physician is contacted is regulated, so ASA is being built consent-first. These controls are design intent for a project in build, and the client’s compliance team reviews the final wording.
We will capture a baseline before go-live and report against it afterwards. Planned measures include pre-call preparation time per physician, weekly active reps, questions answered per week, answer accuracy judged in review, suggestions acted on, escalations captured and delivered, and rep satisfaction. No results are claimed on this page. They will be published after go-live.
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