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Für Denticon

An acquired practice brings three thousand patients. None of them are marketing's.

Export collections from Denticon, upload the leads behind them, and rank sources on the patients the group actually won — office by office.

  • Kein API-Schlüssel
  • Nichts in Denticon zu installierenNichts zu installieren
  • Keine Karte nötigOhne Karte

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.

Denticon sieht

Was verkauft wurde, an wen und für wie viel.

keine gemeinsame Zeile
Ihr Anzeigenkonto sieht

Der Klick, das Keyword, der Anruf und was jedes davon gekostet hat.

Die Datei

Was im Export stehen muss.

Drei Dinge tragen die Zuordnung: wer, wie viel und wann. Alles andere ist optional und ändert nur, wie sich der Bericht aufschlüsseln lässt.

  1. Erforderlich

    Patient phone or email

    On the patient record in the shared database, which is what lets one patient be recognised across offices.

  2. Erforderlich

    Amount collected

    Payments received from patients and insurers together.

  3. Erforderlich

    First visit date and office

    When and where the patient was first seen. Both are needed to tell a new patient from an inherited one.

  4. Optional

    Office joined date

    When each office joined the group. Patients first seen before that date came with the practice.

Schritt für Schritt

So holen Sie die Datei aus Denticon.

Geschrieben für alle, die Denticon im Nachbar-Tab geöffnet haben. Berichtsnamen unterscheiden sich je nach Edition, deshalb sagt jeder Schritt, wonach Sie suchen.

  1. Export collections with patient, office and date

    One row per payment with a contact detail, the amount, the date and the office.

  2. List when each office joined the group

    It is how an acquired practice's existing patients are kept out of the new-patient count.

  3. Export central and local lead sources

    Brand campaigns run for the whole group, local campaigns per office, and the central call centre's booking records.

  4. Take a year or more

    Treatment plans complete over months, and recall is where the second year's revenue sits.

  5. Upload both

    The join runs on the phone and the email, normalised, with results per office and for the group.

Was zurückkommt

Die Seite, die Denticon Ihnen nicht zeigen kann.

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.

Einem Kanal zugeordnet$207,00068% von $304,400
Zugeordnete Verkäufe83 von 129nur hohe Konfidenz
Durchschn. Verkauf$2,340pro bezahltem Verkauf
KanalAnteilVerkäufeUmsatz
Google Ads38$124,800
Meta Ads31$54,800
E‑Mail-Marketing14$27,400
Direkt / Unbekannt46$97,400

Nicht zugeordnete Verkäufe bleiben unter Direkt / Unbekannt. Sie werden nie auf die bezahlten Kanäle verteilt, damit die Summe besser aussieht.

Das Argument

Was sich ändert, wenn patient und Anzeige in einer Zeile stehen.

An acquired practice's patients are not new patients

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.

Brand campaigns and local campaigns are paid for differently

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.

The central call centre is the lead file

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.

One patient, one database, however many offices

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

„Denticon kann das doch schon.“ Nicht ganz.

Sie sagen

„Denticon already reports new patients by office.“

Wir sagen

It reports patients first seen at each office. It cannot tell an acquired patient from a won one, or say which campaign produced either.

Sie sagen

„Our growth is mostly acquisitions.“

Wir sagen

Then separating inherited patients is what makes the marketing figure honest, and it may be much smaller than it looks.

Sie sagen

„Our call centre already tracks sources.“

Wir sagen

It tracks bookings. Joining them to collections is what says which sources produced revenue.

Fragen

Denticon im Detail.

Noch etwas? Fragen Sie uns, und ein Mensch antwortet.

No. It reads a file you exported, so your charts, schedules and database stay where they are.

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

Zwei Exporte, und Sie wissen es.

Nichts in Denticon zu installieren, kein API-Schlüssel, und Sie müssen bisher nichts getrackt haben. Das Vorjahr funktioniert so gut wie dieser Monat.