Matches each client to the stylist who'll delight them.
First visits are won or lost on the pairing. Stylist Match reads what a client has had done, what they've said, what they paid, and what they came back for — then reads your team the same way: who nails a balayage correction, who's fastest on a men's cut, who new clients rebook with. When a booking comes in, it recommends the pairing most likely to end in a rebook.
$99/mo added to any plan · See all pricing
Matching an incoming booking
Scoring every available stylist…
Amara T.
New client · booking online
Built from visit history, chair notes, spend, and what she told the agent while booking.
Nina
Curl specialist · colour correction
Jess
Balayage · lived-in colour
Theo
Precision cutting · men's
The agent books Amara with Nina and notes why. Your front desk can override it in one tap.
Visit history, service mix, spend band, notes from the chair, and what they say to your agent all feed the profile.
Specialties, rebook rates, ticket averages, and the client types each stylist quietly excels with.
The voice, chat, and Instagram agents all book into the recommended chair — with the reason attached.
Newer stylists get the clients they'll win, so the schedule fills evenly instead of everything landing on one person.
One side from client history and conversations, the other from how your stylists actually perform.
Every open slot with every available stylist gets a fit score, with the reasons written in plain English.
The client is booked with the stylist most likely to make them a regular — and your team sees why.
mya is the name salons usually bring up in this category. We wrote an honest side-by-side — what each one is built for, and where SalonAgent's advantage is that this capability shares a brain with the agent answering your phone.
Read SalonAgent vs myaThe questions salon owners ask us about this one.
It learns from what your salon already records — visit history, services, spend, chair notes, and conversations with your agent — plus how each stylist performs with different client types, measured by rebooking and ticket. Every recommendation comes with the reasons behind it, so your team can override it.