Pharmacies · Sales rep training
An AI roleplay trainer for pharmacy sales reps, built in GoHighLevel
Reps get better at prescriber calls by making them, and the first few tries are rarely the ones you want a real office to hear. We built a voice trainer in GoHighLevel (GHL) for a pharmacy's sales team: the agent plays the prescriber, the rep picks the scenario and how hard it should be, and each practice call ends with a recap.
The job
A prescriber who picks up every time
How one practice session runs, from the first question to the recap.
The trainer we built handled real practice calls from the pharmacy's reps. Nobody on the other end was a doctor. The voice agent took that part, so a rep could run the same conversation again and again until it came out the way they wanted.
It asks first. Each session opens with a readiness question before the exercise begins. The rep is never dropped into the middle of a scenario, and decides when it begins.
A menu, not a script. Next the trainer offers a menu of practice scenarios. One of them is the sales call itself: a cold call to a prescriber's office. The menu also offered simulated prior authorization escalations and coverage-denial conversations, along with simulated intake, benefits and counseling conversations. Every one of them is a rehearsal. None is a real patient workflow, and no real patient record sits behind any of them.
Difficulty and persona. The rep chooses how difficult the conversation should be, so a new rep can start gently and an experienced one can ask for real pushback. Persona details are optional: a rep who wants a particular kind of call can describe it before starting.
The prescriber's side. From then on, the agent answers as the prescriber. The rep talks to it the way they would talk to the office they plan to call next week, and the conversation runs from there.
The recap. Every practice call produced a recap notification, and those recaps were the record of the practice. HighLevel keeps this under the agent's post-call settings: notifications, workflows, summaries, and whether the AI's call summary is also saved to the contact's notes. With that last option off, HighLevel's help center says the summary still stays in the Voice AI call logs.
What it does not do. The trainer has no memory. It does not recognize a rep from one session to the next and does not learn where each rep is weak. Adaptive coaching, and training linked to each rep's results, stayed a proposal. It ran in our own HighLevel account rather than the pharmacy's, and it holds no protected health information.
What we set up
What goes into the trainer
Each piece is in the plan document before it is built.
- A HighLevel Voice AI agent that answers as a prescriber
- A readiness question at the start of every session
- A menu of practice scenarios, led by a cold call to a prescriber's office
- Simulated prior authorization escalation and coverage-denial scenarios
- Simulated intake, benefits and counseling conversations
- A difficulty choice the rep makes before each call
- Optional persona details the rep can add
- A recap notification after every practice call
- A prompt and knowledge base with no protected health information in either
How a setup runs
How the trainer gets built
A 1:1 with Rob
Rob asks which calls your reps dread most, who should read the recaps, and what your AI use policy lets an agent hold.
The prescriber on paper
The agent's prompt, the scenario menu and what each recap reports are written out word for word in a plan document for your approval.
Build and rehearse
We build the agent in HighLevel's Voice AI and make test calls through every scenario before a rep ever starts.
A QA report
The handover report shows each scenario answering as written, with screenshots of the agent's settings and a sample recap.
Changes after launch
A new scenario, a harder prescriber or a different recap: each request gets a verdict first, a fix inside the agreed scope or new scope.
What you bring
What we need from your sales lead
The calls your reps make
The kinds of prescriber office conversations your reps have, and where those calls tend to go wrong.
Your objections and answers
The pushback your reps hear and the answers you want them to give, in your own words, with no patient details in them.
Your AI use policy
What your pharmacy allows an AI tool to hold, so the trainer is built inside that line from the start.
Who reads the recaps
The manager or trainer who should get the recap after each practice call.
Where it stops
The trainer is for practice only. It holds no patient information, never files or chases a real authorization, does not remember reps between sessions, and does not score reps against sales results.
Services used
The setups the trainer runs on
HighLevel Voice AI agents
Inbound and outbound voice agents on HighLevel's own builder, with transfers, booking and the consent rules outbound calling needs.
See Voice AI agentsHighLevel AI Employee setup
Chat and voice agents plus the knowledge base behind them, planned word for word and tested before launch.
See AI Employee setupQuestions
What pharmacy sales leads ask about the trainer
What does a practice session sound like?
Can a manager see how a practice call went?
Does the trainer remember each rep?
Is any patient data involved?
Can reps practice prior authorization and coverage-denial calls?
Who you talk to
Rob Eason
Rob runs HLAI Experts and takes the 1:1 calls himself.
He is a HighLevel Certified Admin with the second-most reviews in HighLevel's Certified Admin Directory worldwide, all of them 5 out of 5.
He won HighLevel's Top New Subaccounts via AI Employee award in its 2025 Summer of AI Awards and taught HighLevel's official masterclass on its AI Employee.
Before HighLevel, he co-owned a 60-employee financial services firm and sold his share.
On the call he looks at your account, not a script.
5/5 across 83 reviews in HighLevel's Certified Admin DirectoryHear how a prescriber roleplay would work for your team
In 30 minutes Rob walks through the calls your reps find hardest and what a HighLevel voice trainer would and would not hold.