MobileComm · Staff reference
AI & Calendar Guides.
GoHighLevel implementation and appointment scheduling · Manager handoff
AI customer service action plan
Build a centralized first-line sales and service rep that turns inquiries into store visits, repair jobs, phone sales, or qualified human handoffs.
Respond immediately → understand the need → answer from approved information → collect details → recommend a store/action → capture the lead → follow up → escalate when needed.
Phase 1
Centralize communication
Connect Facebook Messenger, Instagram DMs, SMS, website chat, email, missed-call text-back, and lead forms. Test that every channel reaches GHL Conversations.
Phase 2
Build the knowledge base
Load verified store details, approved repair pricing, dated promotions, and policies/services. Include warranties, payments, data responsibility, activation, financing, returns, trade-ins, and accessories.
Phase 3
Build the AI rep
Use friendly, short, conversational replies. Be helpful and sales-oriented without being pushy.
Phase 4
Identify customer intent
Classify repair, phone purchase, sell/trade, technical support, store information, existing repair, and complaints. Escalate uncertain requests.
Phase 5
Repair conversations
Identify the exact device and repair, retrieve approved pricing, confirm a convenient store, and move toward a planned visit—not only a price quote.
Phase 6
Phone sales
Collect desired model, carrier/unlocked preference, budget, new/used preference, and store. Without real-time inventory, ask a store employee to confirm availability.
Phase 7
Human handoff
Immediately escalate angry customers, refunds, warranty disputes, repair status, unverified pricing, unusual repairs, commercial inquiries, legal threats, chargebacks, lost-data claims, and anything uncertain. Acknowledge concerns; never argue.
Phase 8
CRM pipeline
Create Mobilecomm Customer Leads: New Inquiry → AI Engaged → Qualified → Store Selected → Appointment / Expected Walk-In → Completed / Sold or Lost / No Response.
Phase 9
Capture customer data
Record name, phone, email, inquiry type, device, repair, quoted price, desired phone, preferred store, lead source, promotion, expected visit date, and AI/human status.
Phase 10
Missed-call automation
Text: “Hi, this is Mobilecomm. Sorry we missed your call. What can we help you with?” Then qualify the customer through SMS.
Phase 11
Social lead follow-up
Connect Facebook/Instagram lead campaigns and respond quickly with campaign-specific messaging. For repairs, ask for the device model.
Phase 12
Follow-up automation
Use light follow-ups for customers who stop responding, with a separate follow-up for qualified customers who do not visit. Avoid excessive messaging.
Phase 13
Test before autopilot
Start in suggestion/draft mode where available. Run approximately 100 real or simulated conversations across pricing, services, inventory, policies, disputes, and unusual questions. Document and correct incorrect responses.
Phase 14
Limited autopilot
Begin with hours, locations, basic repairs, approved prices, promotions, general services, and lead qualification. Keep sensitive, disputed, uncertain, and high-risk conversations with humans.
Phase 15
Management dashboard
Track conversations, AI response rate, handoffs, repair and sales leads, sources/stores, expected visits, completed jobs/sales, lost leads, response time, and conversion rate.
AI non-negotiable rules
- Never invent repair prices or inventory.
- Never promise a repair is complete or guarantee repair times unless authorized.
- Never make unauthorized discounts or create company policies.
- Never argue with customers or handle serious complaints without escalation.
- Never claim warranty coverage unless clearly supported.
- Never share another customer's device or repair information.
- When uncertain, ask a clarifying question or hand off to a Mobilecomm employee.
Manager's initial deliverables
- All communication channels connected and tested
- All locations and hours verified in the knowledge base
- Current repair pricing uploaded and verified
- Current promotions uploaded with dates where possible
- Policies and services uploaded
- AI instructions and human handoff rules completed
- CRM pipeline and customer fields created
- Missed-call and Facebook/Instagram lead workflows tested
- At least 100 AI test conversations completed
- Incorrect or questionable responses documented
- Corrections completed before autopilot activation
Success criteria
A 24/7 digital front desk and sales representative, with employees handling conversations requiring human judgment.
Primary KPI: How many customer inquiries became revenue?
Store calendar structure
Use one centralized HighLevel appointment system with a separate calendar for each store. The AI checks the selected store's calendar and offers only available slots.
| Store calendar | Suggested color | Purpose |
|---|---|---|
| Seneca | Green | Repair bookings |
| 13th | Blue | Repair bookings |
| Maize | Orange | Repair bookings |
| Harry / Oliver | Purple | Repair bookings |
| Woodlawn | Red | Repair bookings |
Calendar colors are suggestions. The source guide says “Harry / Oliver”; the current website lists “Harry & Rock.” Verify the correct store mapping before rollout.
Customer booking experience
- Identify the exact device and requested repair.
- Quote only approved pricing from the MobileComm knowledge base.
- Confirm the customer's preferred MobileComm store.
- Check that store's calendar and offer only available times.
- After the customer confirms a time, reserve it and send confirmation.
Manager configuration checklist
- In Calendars → Calendar Settings, create one calendar per store. Set hours, appointment duration, buffers, capacity, and assigned staff.
- In AI Agents → Conversation AI, open the Mobilecomm AI Rep.
- Under Bot Goals → Appointment Booking, configure booking and select multiple store calendars if supported by your agent type.
- Write clear calendar descriptions and require store preference confirmation before calendar selection.
- Test availability, bookings, rescheduling, cancellation, confirmation messages, and human handoff.
Appointment information
- Customer name and phone number
- Device make/model and requested service
- Approved quoted price, when available
- Selected store, appointment date and time
- Relevant notes and lead source
After-booking automations
- Send SMS confirmation with the date, time, and store address.
- Notify the selected store and central management.
- Send an appointment reminder.
- Update the CRM pipeline stage to Appointment Scheduled.
- Display the booking on the correct store calendar.
Confirmed appointment vs. expected walk-in
- Confirmed appointment
- Check real availability and reserve a slot when technician capacity or a specific start time must be protected.
- Expected walk-in
- Record the planned visit and alert the store without guaranteeing technician availability.
The guide recommends expected walk-ins for most standard inquiries and confirmed appointments for complex or longer services. Keep these clearly labeled in the CRM; management approval is required before applying this recommendation.
External calendar synchronization
Keep GoHighLevel as the master booking system for the proposed setup. Sync with Google Calendar or Outlook only where staff needs it. Test conflicts, duplicate events, and whether external busy times block HighLevel slots.
Go-live acceptance tests
- Each store offers valid available appointment times.
- The AI cannot double-book beyond configured capacity.
- Confirmations include the correct location and time zone.
- Appointment details reach the store and CRM.
- Rescheduling and cancellation work as intended.
- Walk-in language does not promise a guaranteed technician appointment.
- Human escalation works when the AI cannot verify availability.
HighLevel menu names and multi-calendar capabilities may vary by account, agent type, and product updates. Verify them in your account before rollout. The original PDFs are the source references.