AI‑Drafted Rebooking Automation that Keeps Your Salon Fully Booked

Below is a step‑by‑step walk‑through of setting up an AI‑drafted re‑booking automation in Ferbz. The example follows Luxe Locks Salon, a boutique hair‑care studio in Manchester that offers haircuts, colour, and a “6‑session colour package”.

1. Log in to the dashboard – Open https://dashboard.ferbz.com/ and sign in with your credentials. You land on the main overview page showing today’s bookings and credit balance.

2. Navigate to the Automation tab – On the left‑hand menu, click Automation. The canvas opens blank, with a “Create new journey” button at the top right.

3. Start a new journey – Click Create new journey. A modal asks you to describe the goal in plain English. Type:
   “Remind any client who hasn’t booked their next haircut within 14 days of their last appointment, and offer a 10 % discount if they book within the next 48 hours.”

4. AI drafts the flow – Ferbz’s AI instantly builds a four‑step journey:

   • Trigger – “Days since last booking = 14”.
   • Wait – 0 hours (the message is ready to send as soon as the trigger fires).
   • Message 1 – “Hi {{client.first_name}}, we miss you! It’s been two weeks since your last haircut. Book within the next 48 hours and enjoy 10 % off. Click here: {{booking.link}}”.
   • Branch – “If client books within 48 hours → end journey”.
   • Message 2 (fallback) – “Just a friendly reminder, {{client.first_name}} – your 10 % re‑booking discount expires tomorrow. Secure your slot now: {{booking.link}}”.

5. Edit the templates – Click any message box to open the text editor. Replace the placeholder discount with your actual promotion code, adjust the tone to match Luxe Locks’ brand, and insert the appropriate booking link token ({{booking.link}}).

6. Set the trigger details – On the trigger node, confirm the condition “Days since last booking = 14”. You can also add a filter: Service type = Haircut. This ensures the journey only runs for haircut clients, not colour or styling appointments.

7. Save and activate – Click Save, then toggle the journey to Active. Ferbz immediately starts evaluating all existing client records in the Clients module against the trigger.

8. Check the Reminders board – Switch to the Reminders tab on the left menu. You’ll see a live list of every reminder generated by the automation, including:

   • Scheduled – “Message 1 to Emma Watson, scheduled for 2026‑09‑16 09:00”.
   • Sent – “Message 1 sent to Emma Watson, 2026‑09‑16 09:00”.
   • Delivered – “Message 1 delivered, 2026‑09‑16 09:03”.
   • Read – “Message 1 read, 2026‑09‑16 09:07”.

   If a reminder fails (e.g., the client’s number is invalid), it appears as Failed with a reason, so you can quickly clean the contact list.

9. Monitor results in Reports – After a week, open the Reports module. Choose the “Automation performance” report, set the date range to the past 7 days, and filter by the journey name “Haircut Re‑booking”. The report shows:

   • Total reminders sent – 87
   • Bookings generated – 23 (26.4 % conversion)
   • Revenue recovered – £1 842 (including VAT as per HMRC guidance)
   • Credits used – 174 (2 credits per message, plus 1 credit for each booking confirmation)

10. Iterate if needed – Return to the Automation canvas, adjust the wait time or message copy, and re‑activate. All changes are versioned, so you can compare performance before and after the tweak.

Full Worked Example

Client: Emma Watson, a regular haircut client at Luxe Locks.

Last booking: 2026‑09‑02 (Haircut, £45).

Credit balance before automation: 5 000 credits.

Day 0 (2026‑09‑02): Emma checks out at the front desk. Staff rings up the booking in Billing → New Sale, selects Emma from the Clients list, and completes the sale. Ferbz generates a PDF receipt, shares the link via WhatsApp, and instantly enrolls Emma in the “Haircut Re‑booking” automation because the trigger is “Days since last booking”.

Day 14 (2026‑09‑16): The automation’s trigger fires. On the Reminders board, a new entry appears: “Message 1 scheduled for Emma Watson”. The AI‑drafted message is sent via the official WhatsApp Business API. Emma reads the message at 09:07, clicks the booking link, and selects a slot for 2026‑09‑22.

Result: The system records a new booking, deducts the appropriate credits (2 for the reminder, 1 for the confirmation), and updates the Reports dashboard. Emma’s re‑booking is now secured, and Luxe Locks recovers the £45 revenue that might otherwise have been lost.

Through this single journey, Luxe Locks has automated a process that previously required a staff member to call or text each client manually, saved roughly 12 minutes per client, and increased re‑booking conversion by over 20 percentage points.

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The manual re‑booking workflow in a typical UK salon involves a receptionist checking the diary each evening, locating clients whose last appointment was two weeks ago, and either calling them or sending a personal WhatsApp message from a staff phone. That routine consumes on average 11 minutes per client and is prone to human error – missed numbers, forgotten follow‑ups, or inconsistent wording.

With AI‑drafted re‑booking automation, the same task becomes a single configuration that runs 24 hours a day. For Luxe Locks, the numbers look like this:

• Clients in the system: 312
• Clients eligible for re‑booking each month: 124 (those who had a haircut in the previous 30 days)
• Manual time saved: 124 × 11 min = 1 364 minutes ≈ 22 hours per month
• Credits spent on reminders: 124 × 2 credits = 248 credits (plus 1 credit per confirmation)

The Revenue recovered from the 23 re‑bookings in the first week alone is £1 842, a direct uplift that more than offsets the credit spend (≈ £300 worth of credits at the prevailing rate).

Beyond the hard numbers, the automation eliminates the need for paper‑based client preference logs. Each client’s Clients profile now contains a complete history of services, notes entered by stylists, and a log of every reminder sent. When a stylist opens a client’s record, they instantly see the last re‑booking message and any discount used, allowing them to personalise the next visit without rummaging through paper files.

Finally, the Reminders board guarantees no silent failures. If a WhatsApp message cannot be delivered, the status changes to Failed, prompting the owner to verify the phone number or request an updated contact. This visibility is impossible with ad‑hoc personal messaging.

Overall, AI‑rebooking automation for salons converts a labour‑intensive, error‑prone process into a measurable, credit‑based workflow that boosts re‑booking rates, protects revenue, and frees staff to focus on the service experience.

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Ready to stop chasing clients and let an AI‑drafted WhatsApp journey keep your chairs full? Sign up for a free trial at https://dashboard.ferbz.com/ and start building your first re‑booking automation in minutes. If you need help configuring the journey or loading your client list, our support team is on hand at support@ferbz.com. With Ferbz’s credit‑based model, you only pay for the messages that actually reach your clients, giving you full control over costs while maximising re‑booking revenue.

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