Radar: fill the therapist time that would sit empty
Machine learning finds the open stretches of therapist time unlikely to sell and emails only as many guests as each opening needs. It never emails regulars, members or anyone with an appointment, and it is off until you switch it on, per spa and per department.
Radar: it fills the time that was going to sit empty.
Finds the openings unlikely to fill.
One model scores every open stretch of therapist time, 2 to 10 days out.
Picks the guests most likely to take them.
A second model scores every guest. Regulars are skipped. They'd come anyway.
Sends one email, at their hour.
It names a day and a time of day. If the time sold in the meantime, nothing goes out.
Two machine-learning models, retrained every month. Turn on a comparison group and one guest in fifty is skipped, so what the email did can be measured.
Radar never emails members, anyone already booked, anyone you emailed in the last 7 days, or the same guest twice in six months. It is off until you switch it on.
Launching with Day Spa Mail
Each dot is open massage time in the days ahead. The closer to the centre, the surer it is to go unsold. Sample data.
Riverside Spa to Marisol V. · 7 PM
An opening Tuesday or Wednesday afternoon
Sent at the hour this guest usually books.
Radar questions
Straight answers, before you get in touch.
Two machine-learning models, trained on your own spas' bookings and nobody else's. One scores each open stretch of therapist time for how likely it is to go unsold. The other scores each guest for how likely they are to book. Radar emails the guests who best fit the openings unlikely to fill, only as many as each opening needs, and, if you turn on a comparison group, skips one in fifty so the effect can be measured.
No. It never emails regulars, members, or anyone with an appointment, never the same guest twice in six months, and never more than about 6% of your list in a month. It is off until you switch it on, per spa and per department.
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