„Denticon already reports new patients by office.“
It reports patients first seen at each office. It cannot tell an acquired patient from a won one, or say which campaign produced either.
Für Denticon
Export collections from Denticon, upload the leads behind them, and rank sources on the patients the group actually won — office by office.
CloseRev reads a Denticon export of collected payments — the patient's phone or email, the amount, the date and the office — and matches it against the campaigns, calls and bookings that produced the first appointment. Dental groups on a shared database grow two ways, by winning new patients and by acquiring practices that bring patients with them, and an honest report has to tell those apart before it credits any marketing. Collections with no traceable lead are reported as Direct / Unknown.
Zuletzt am 25. September 2026 anhand der eigenen Dokumentation von Denticon geprüft.
Die Lücke
The group's new-patient number jumps every time it buys a practice, and the marketing report takes the credit.
Was verkauft wurde, an wen und für wie viel.
Der Klick, das Keyword, der Anruf und was jedes davon gekostet hat.
Die Datei
Drei Dinge tragen die Zuordnung: wer, wie viel und wann. Alles andere ist optional und ändert nur, wie sich der Bericht aufschlüsseln lässt.
On the patient record in the shared database, which is what lets one patient be recognised across offices.
Payments received from patients and insurers together.
When and where the patient was first seen. Both are needed to tell a new patient from an inherited one.
When each office joined the group. Patients first seen before that date came with the practice.
Schritt für Schritt
Geschrieben für alle, die Denticon im Nachbar-Tab geöffnet haben. Berichtsnamen unterscheiden sich je nach Edition, deshalb sagt jeder Schritt, wonach Sie suchen.
One row per payment with a contact detail, the amount, the date and the office.
It is how an acquired practice's existing patients are kept out of the new-patient count.
Brand campaigns run for the whole group, local campaigns per office, and the central call centre's booking records.
Treatment plans complete over months, and recall is where the second year's revenue sits.
The join runs on the phone and the email, normalised, with results per office and for the group.
Was zurückkommt
Umsatz nach Kanal, die Zahl der Verkäufe hinter jedem Wert und eine ehrliche Kategorie für alles, was niemand zuordnen konnte. Beispielzahlen aus dem durchgerechneten Beispiel der Seite Zahnarztpraxen – nicht aus einem Denticon-Konto.
| Kanal | Anteil | Verkäufe | Umsatz |
|---|---|---|---|
| Google Ads | 38 | $124,800 | |
| Meta Ads | 31 | $54,800 | |
| E‑Mail-Marketing | 14 | $27,400 | |
| Direkt / Unbekannt | 46 | $97,400 |
Nicht zugeordnete Verkäufe bleiben unter Direkt / Unbekannt. Sie werden nie auf die bezahlten Kanäle verteilt, damit die Summe besser aussieht.
Das Argument
When a group buys a practice, the practice's existing patients move into the group's database. In a naive report they appear as new patients in the month the practice joined.
Every campaign running that month then looks extraordinary, and the group's marketing is credited with growth it bought rather than won.
The fix is to record when each office joined and treat patients first seen before that date as inherited, whatever their record's created date says.
Reported apart, the group sees two honest numbers: how many patients marketing won, and how many came with acquisitions.
For a group growing by acquisition, the first number is the one that shows whether the marketing works at all.
A group typically runs some marketing centrally for all its offices and lets offices, or regions, run their own.
Credited together, a brand campaign's patients get attributed to whichever office they happened to book at, and a local campaign's results get blended into the group's.
Keeping the campaign's level on the lead file lets the report show central spend against the patients it produced across every office, and local spend against its own office.
That is the split a group's budget is actually set on, so it is the one the report produces.
It also settles a recurring argument inside groups: whether the central marketing team is producing patients for the offices or taking credit for what the offices would have won locally. With both levels on the lead file, the answer is a number rather than a debate.
Many groups book appointments through a central team rather than each office's front desk, and that team's records hold the caller, the date and often how they heard about the group.
Those records are the most complete lead file a group has, and they are frequently never joined to the collections that followed.
Exporting them alongside collections gives revenue per booking by source, across every office the call centre serves.
It also shows which offices convert the bookings the centre sends, which is an operations finding rather than a marketing one.
A patient who moves house or switches to an office nearer work is still one patient, and a shared database recognises them as one.
A report that counts patients per office without that recognition would count the move as a new patient at the second office.
Matching on the patient, not the office, keeps them attached to the source that first produced them, with the offices they visited recorded beside it.
It is one of the practical advantages of a group on a single database, and it makes the group's attribution cleaner than a collection of separate practices could produce.
Berechtigte Fragen
It reports patients first seen at each office. It cannot tell an acquired patient from a won one, or say which campaign produced either.
Then separating inherited patients is what makes the marketing figure honest, and it may be much smaller than it looks.
It tracks bookings. Joining them to collections is what says which sources produced revenue.
No. It reads a file you exported, so your charts, schedules and database stay where they are.
Collected payments with a patient contact detail, the amount, the date and the office.
Patients first seen before the office joined the group are treated as inherited, not as marketing wins.
Because a record's created date is the day it entered the database, which for an acquired practice is the day of the acquisition.
Yes, where the lead file records which level ran the campaign.
Yes, and they are usually the most complete lead file a group has.
Yes, and by region where the export carries one.
They stay one patient, credited to the source that first produced them, with their offices recorded.
A year or more, so treatment plans complete and recall appears.
Any new patient's collections with no traceable source.
A contact detail, an amount, a date and an office. No charts, no procedure codes, no insurance identifiers, no images. Encrypted in transit and at rest and deleted with the import.
Collections per new patient by source and by office, inherited patients reported apart, central and local spend separated, and everything unmatched kept visible.
Nach Branche
Wie der Bericht aussieht, sobald der Export drin ist – für jede Branche eigens geschrieben.
Andere Systeme
Mehrere Systeme im Einsatz oder im Vergleich? Die Methode ist dieselbe, die Spalten sind es nicht.
Denticon und die anderen Produktnamen und Logos auf dieser Seite gehören ihren Inhabern und dienen nur dazu, die Software zu kennzeichnen, aus der eine Datei stammt. CloseRev ist mit ihnen nicht verbunden oder von ihnen empfohlen und verbindet sich mit keinem davon: CloseRev liest eine Datei, die Sie exportieren.
Heute starten
Nichts in Denticon zu installieren, kein API-Schlüssel, und Sie müssen bisher nichts getrackt haben. Das Vorjahr funktioniert so gut wie dieser Monat.