Front-Desk Analytics
See which patient calls move forward and which still need staff
Review call intent, appointment outcomes, follow-up status, and handoffs so owners and office managers can see where patient opportunities stop.
- Calls answeredtrending up+9% vs July1,284Every call, by time of day and reason.
- Visits bookedtrending up+7% vs July306Requests that entered the schedule.
- Recall visits completedtrending up+12% vs July92Outreach that ended in a visit.
- Handoffs to staffsteady by designBy design141Routed to a person, with context.
Illustrative sample values, not live practice data. EigenH AI reports operational records for your practice — it does not promise these numbers, and revenue impact stays yours to model.
Measurement by agent
Every agent is measured the same way — intent, action, outcome, next step — but each one reports the records that matter to its workflow. Open an agent to see its board.
- AI Appointment Agent Keep every chair full How it's measured
- AI Follow-up Agent Bring patients back How it's measured
- AI Insurance Agent Verify coverage before the visit How it's measured
- AI Reputation Agent Turn great care into reviews Coming soon How it's measured
- AI Payment Agent Collect payments without chasing Coming soon How it's measured
Follow the patient opportunity to an outcome
Thirty answered calls may produce appointments, reschedules, questions for staff, or no completed action. A useful dashboard separates those outcomes — every handled conversation becomes an operational record with four parts.
- 01
Intent
Why the patient called: a new appointment, a change, a cancellation, recall, billing, or the office itself.
- 02
Action
What EigenH AI did within the approved rules — a completed administrative action, or information captured for staff.
- 03
Outcome
Scheduled, changed, stopped, or needs review. Clear labels keep activity from being confused with progress.
- 04
Next step
If the workflow is not complete, the team knows who needs attention and why.
What the practice can review
The exact fields depend on the approved workflow and product configuration — these are the views the record system is built around.
-
Call volume
Every answered call, by time of day and reason.
-
Appointment outcomes
Scheduled, changed, cancelled, or handed to staff.
-
After-hours and overflow
Demand that arrives when nobody can answer the phone.
-
Missed calls in follow-up
Missed calls added to a worked outreach queue.
-
Recall and outreach status
Where each approved workflow stands, patient by patient.
-
Incomplete and unresolved work
Requests that could not be completed — and what still needs a person.
Your numbers stay honest
EigenH AI does not turn every answered call into a revenue claim, and website analytics never capture patient information. Operational records are the product; the financial assumptions applied to them stay yours.
Security and privacy questions belong in the Security & Compliance review on the trust page.
-
No revenue promises
Outcome records, never recovered-revenue estimates presented as fact.
-
No PII in marketing analytics
No patient data, health details, phone numbers, insurance IDs, or free text — ever.
-
Methodology before proof
Public outcome numbers require a defined methodology and customer approval first.
-
Configuration decides the fields
Available views, search, and scope depend on the approved workflow and permissions.
Find where the front desk needs support
Call patterns reveal demand the schedule alone does not show:
-
After-hours requests
Appointment demand arriving while the office is closed.
-
Peak-hour pressure
The periods when staff cannot answer every call.
-
Exception-prone visit types
The visit types that create frequent staff exceptions.
-
Cancellations without follow-up
Openings left behind when plans change.
-
Recall lists that stall
Outreach with low response or unresolved questions.
These patterns help the practice adjust rules, staffing, and follow-up. They do not prove a financial result on their own.
Frequently Asked Questions
Available review and search fields depend on the product configuration and user permissions. We confirm the approved view during implementation.