Predict appointment no-shows and cancellations
Most teams find out who will cancel when nobody answers the door. Customers often tell you sooner, in how they talk about the booking. EchoDepth reads that language and bands every booking low, medium or high risk, while there is still time to keep the slot.
One question tells you who will turn up
Ask what made them choose this appointment date, then listen to how they answer. Under two minutes on the five signals EchoDepth reads and what to do with each risk band.
Read the transcript
Every missed appointment costs a wasted visit, an empty slot, and often a customer you'll go on to lose.
Most teams only find out who will cancel when nobody answers the door. But customers often tell you sooner, in how they talk about the booking.
Ask one question: what made you choose this appointment date? Then listen to how they answer.
"I picked the Friday. I've booked the day off. I'll definitely be in." That's choice, ownership and a firm commitment.
"It was the only one they had, so I had to take it. Hopefully I can get the day off work, but I'll have to sort out the school run." No choice, hedging and two constraints.
EchoDepth reads five things in every answer - choice, commitment, ownership, constraints and emotion - and places each booking in a low, medium or high risk band.
The same language reaches beyond bookings, on calls and in emails. Resignation, hedging and decisions that feel imposed are early signals that a customer is drifting away.
So you can act before the slot is lost. Confirm, offer a better date, or reassure, starting with the high-risk group.
It's tested against your real cancellations and read across groups, never as a verdict on any one customer.
EchoDepth. See who's likely to cancel while there's still time to keep them. See what your customers feel.
Five things EchoDepth reads in every answer
Two customers can book the same slot and mean very different things. “I picked the Friday. I’ve booked the day off. I’ll definitely be in” is choice, ownership and a firm commitment. “It was the only one they had. Hopefully I can get the day off, but I’ll have to sort out the school run” is no choice, hedging and two constraints.
Choice
Did they pick this date, or take what was left? "I picked the Friday" is a different booking from "it was the only one they had".
Commitment
How firmly they say they will be there. "I'll definitely be in" against "hopefully".
Ownership
Whether they have already made it their plan - booked the day off, arranged cover - or are leaving it to chance.
Constraints
The obstacles they mention unprompted: getting time off work, the school run, travel. Each one is a reason the slot could be lost.
Emotion
Resignation, reluctance or a sense that the decision was imposed on them, as against confidence and intent.
Act before the slot is lost
Every booking lands in a band, so follow-up goes where it changes the outcome. Start with the high-risk group.
High risk
Call first. Confirm the appointment, offer a date that suits them better, or reassure them about what is holding them back.
Medium risk
A lighter touch: a reminder or a quick check that the time still works.
Low risk
Nothing extra. Spend the team's time where it changes the outcome.
Beyond the booking
The same language turns up on calls and in emails long after the appointment is made. Resignation, hedging and decisions that feel imposed are early signs that a customer is drifting away, whether they are about to miss a visit, cancel a service or not renew.
The model is tested against your real cancellations before you rely on it, and results are read across groups to prioritise follow-up, never as a verdict on any one customer. See governance for how consent and purpose limits are handled.
Common questions
Can AI predict appointment no-shows?
It can flag which bookings are more likely to fall through. EchoDepth reads how a customer talks about the booking - whether they chose the date, how firmly they commit, whether they own the arrangement, what constraints they mention and the emotion in the answer - and places each booking in a low, medium or high risk band. It gives your team a ranked list to follow up, not a certainty about any one person.
What signals suggest a customer will cancel?
No choice in the date ("it was the only one they had"), hedging ("hopefully"), constraints (time off work, the school run) and decisions that feel imposed. A firm answer sounds different: a chosen date, a plan already made, a clear commitment. The same patterns show up on calls and in emails beyond the booking itself.
What do we do with the risk bands?
Act before the slot is lost. Start with the high-risk group: confirm the appointment, offer a date that suits them better, or reassure them about whatever is holding them back. Medium-risk bookings can get a lighter touch, and low-risk bookings need nothing extra.
How do we know the bands are accurate for our customers?
The model is tested against your own historical cancellations and no-shows before you rely on it, so the bands reflect what actually happened in your bookings rather than a generic benchmark.
Is this profiling individual customers?
Results are read across groups to prioritise follow-up, never as a verdict on any one customer. The output is a prompt for a helpful call, not a decision about the customer. EchoDepth is UK-hosted and registered with the ICO (ZB915633).
How can you predict which customers will miss an appointment?
Ask the customer what made them choose the appointment date and listen to how they answer. EchoDepth reads five signals in the reply - choice, commitment, ownership, constraints and emotion - and places each booking in a low, medium or high risk band. Teams then confirm, offer a better date or reassure, starting with the high-risk group. The model is tested against the organisation’s own past cancellations and read across groups, not as a verdict on any one customer.
See who is likely to cancel
Send a sample of booking calls or messages alongside which ones went on to cancel, and we will show you how the bands line up with what happened.