We analysed 125,000 receipts from a multi-specialty medical centre over three years: who drives revenue, how much the clinic loses on patients who never come back, and which triggers bring them back.
Working a clinic's patient base starts with exporting receipts from the clinic management system and scoring each patient on the three RFM dimensions: days since the last visit, number of visits and total spend. In our analysis of a multi-specialty medical centre for 2023–2025, with 44,000 patients and 125,000 receipts, 52% of patients came once and brought 20% of revenue, while the 30% with three or more visits brought 66%. The chance of winning a patient back falls from 42% after 30 days without a visit to 34% after 90 days and 18% after a year, so the decisive window for reactivation is the first 90 days. In practice the clinic gets daily lists from its system: new patients on day 3, regulars after a 60-day pause, lapsed patients on day 90, high-value patients with no visit for over a year. Each list has a set channel (call or message), reason to get in touch and discount. Cross-selling runs separately: a patient who saw the ENT doctor but skipped the lab tests gets a call between day 3 and day 21.
Almost every clinic that comes to us for marketing asks for more new patients. We ask for an export from their clinic management system. It almost always holds thousands of people who came once, paid and never returned. The clinic has already paid to acquire them.
Below is the analysis of one such base: a multi-specialty medical centre, a branch of a regional chain in Russia, with data for 2023–2025. The base holds 44,000 unique patients and 125,000 receipts. From these numbers we built a trigger system that tells front-desk staff every day whom to call, whom to message and with what reason. The method works for any clinic with a management system or an accounting export. Amounts are in Russian roubles.
The analysis needs commercial data only: the patient’s phone number, the date of each visit, the receipt amount, the services provided and the department. Medical records and diagnoses are not needed.
From these fields we calculate five measures for each patient:
| Measure | How it is calculated | Why it matters |
|---|---|---|
| Recency | Days since the last visit | Shows whether the patient has gone cold |
| Frequency | Number of distinct visits | Separates one-time patients from regulars |
| Monetary | Total revenue from the patient for the period | Finds the most valuable patients |
| Last service and department | From the last receipt | Gives a reason to call and a cross-sell |
| First receipt amount | From the first receipt | Predicts whether a new patient returns |
RFM analysis splits customers by three dimensions: how recently they last visited (Recency), how often they come (Frequency) and how much they have spent (Monetary). The combination of the three scores gives a segment, and the segment gives a playbook.
Fewer than half. Of 44,000 patients, 48% came a second time, 30% a third time, 15% a fifth time and fewer than 5% a tenth time. This is a retention curve by visit number, and its steepest drop sits between the first and the second visit.
The trend is worse. This clinic’s conversion from the first visit to the second fell from 69% in 2023 to 32% in 2025. Advertising kept bringing new patients, and the clinic increasingly saw them exactly once.
Frequent visitors bring the revenue. One-time patients were 52% of the base and brought 20% of revenue. Patients with three or more visits were 30% of the base and brought 66%. This is the Pareto principle, but in a clinic it depends more on frequency than on receipt size.
| Visit frequency | Share of patients | Share of revenue | Revenue per patient | Average receipt |
|---|---|---|---|---|
| 1 visit | 52% | 20% | RUB 1,800 | RUB 1,800 |
| 2 visits | 18% | 14% | RUB 3,700 | RUB 1,850 |
| 3–4 visits | 15% | 20% | RUB 6,200 | RUB 1,800 |
| 5–8 visits | 9% | 20% | RUB 10,300 | RUB 1,700 |
| 9–15 visits | 4% | 14% | RUB 17,900 | RUB 1,600 |
| 16+ visits | 2% | 13% | RUB 34,000 | RUB 1,400 |
Look at the last column. The most loyal patients have a lower average receipt than one-time patients: RUB 1,400 against RUB 1,800. A regular patient comes for lab tests, follow-up appointments and procedures, each of them inexpensive. A patient with 16 or more visits brings the clinic almost 19 times more than a one-time patient. That is why a discount that gets a patient to come a second time almost always pays for itself.
The chance of winning a patient back shrinks with every month of silence. We measured what share of patients returned after a pause of a given length:
| Days without a visit | Probability of return |
|---|---|
| 30 | 42% |
| 60 | 38% |
| 90 | 34% |
| 120 | 32% |
| 180 | 28% |
| 365 | 18% |
| 730 | 7% |
Every 30 days of inactivity takes 3–5 percentage points. We call the 90-day mark the critical window: before it the patient still remembers the clinic and the doctor, after it a return takes more effort and a larger discount. After two years without a visit, 7% of patients come back.
We expected patients with an expensive first visit to return best. The first-receipt data showed something else: after a first receipt of RUB 1,500–2,500, 41% of patients came back; after a receipt under RUB 800, 52%; after a receipt of RUB 4,000 or more, 54%.
The explanation is simple. A cheap visit is usually part of a course of treatment that continues. An expensive visit is one the patient remembers and values. A mid-range receipt often means a one-off consultation after which the patient did not see a reason to come back. So in our system new patients with a first receipt of RUB 1,500–2,500 get a call on day 3, even though their spend does not stand out.
The RFM scores combine into segments. The names follow the usual RFM convention, which makes them easy to match with reports and with the literature on cohort analysis.
| Segment | Who they are | In this base | What we do |
|---|---|---|---|
| New | 1 visit, within the last 30 days | Daily inflow | Call or SMS on day 3 |
| Hot list | 1 visit, 30–180 days ago | 4,600 people | Urgent win-back campaign |
| Champions | 4+ visits, last within 90 days, spend from RUB 4,000 | 7,800 people, 46% of revenue | Retain, call after a 60-day pause |
| Need Attention | Were active, 200 days since last visit | 5,200 people, 15% of revenue | Personal reason to return |
| Can’t Lose | Came often, then disappeared | 5,000 people, 11% of revenue | Call campaign, 20% discount |
| About to Sleep | At the 90-day mark | 1,600 people | SMS with a 15% discount |
| High-value at risk | Top 10% by spend, over RUB 11,000, no visit for over a year | 580 people, 600 days without a visit on average | Personal call, individual offer |
| Lost | Over a year without a visit, spend under RUB 11,000 | 4,600 people | Mass SMS with 30% discount, VK retargeting |
The Champions segment holds 7,800 people who brought 46% of revenue: RUB 12,500 and 11 visits per person on average. Separately we track 580 patients from the top 10% by spend who have not come for 600 days on average. Together they once spent more than RUB 9 million at the clinic. This is the first list we recommend working after the hot list of one-time patients.
We converted the findings into money. The calculation is simple: take the segment size, a realistic return rate from the same base and the revenue such a patient usually brings.
Revenue lost to the fall in repeat visits. A patient who came at least twice brought the clinic RUB 8,000 on average over the period, RUB 6,200 more than a single first visit. When second-visit conversion fell from 69% to 32%, the clinic began keeping 370 fewer patients out of every 1,000 new ones. That is RUB 2.3 million of missed revenue per 1,000 new patients. The medical centre took 14,000–15,000 new patients a year, so on the annual flow the gap exceeds RUB 30 million.
Potential of the segments the clinic can win back in the coming months:
| Segment | Size | Assumption | Potential |
|---|---|---|---|
| Hot list, one visit 30–180 days ago | 4,600 people | Win back 20–30%, one visit each at the median receipt of RUB 1,600 | RUB 1.5–2.2 million right away |
| Hot list, if those who return become regulars | The same 900–1,400 people | Behave like an average repeat patient: +RUB 6,200 on top of the first visit | RUB 6–9 million |
| High-value patients with no visit for over a year | 580 people, RUB 16,000 spend per person on average | Return at the natural 18% for this pause, 100 people | RUB 1.6 million |
| New patients with a first receipt of RUB 1,500–2,500 | Daily inflow | Lift return from 41% to the level of neighbouring groups, 52% | +11 repeat patients per 100 new ones |
For high-value patients we assumed the natural return rate, with no uplift for the call and the individual offer. In practice a personal call does better, but the lower bound is more useful for planning.
The Can’t Lose segment needs attention too. These 5,000 people used to come often and brought 11% of all revenue over three years. Every month without contact cuts the chance of winning them back by 3–5 percentage points.
Each segment becomes a trigger with a set day, channel and reason. The result is a customer journey map tied to a calendar.
| Day | Who | Channel | Reason |
|---|---|---|---|
| 3 | New patients with a first receipt of RUB 4,000+ | Call | A check-in on how they feel, on behalf of the doctor |
| 3 | New patients with a first receipt of RUB 1,500–2,500 | Call | 15% coupon for the next visit |
| 30 | New patients who did not rebook | SMS | Reminder, 15–20% coupon |
| 60 | Regulars on a pause | Champions: call, others: SMS | New service, 10% coupon |
| 90 | Can’t Lose and lapsed high-value patients | Call | “We have not seen you for a while”, 20% coupon |
| 90 | About to Sleep | SMS | 15% coupon |
| 120 | Everyone who did not respond | Final call | 25% coupon, personal letter |
| 365+ | High-value at risk | Personal call | Individual offer, 30% coupon |
| 365+ | Other lost patients | SMS and VK retargeting | 30% coupon |
The discount ladder rises with recency: the further a patient has drifted, the stronger the reason needs to be. A patient who visited a month ago needs a reminder and 10–15%. A patient who has been away for a year needs 30% and a personal approach.
A returning patient re-enters the active pool and passes the same checkpoints. A return is not retention: if the patient disappears again after 60 days, the next trigger fires.
In Russia an SMS or message with a coupon for a medical service counts as advertising. Under article 18 of the Advertising Law it may be sent only to people who gave prior consent to marketing messages, and article 24 requires advertising of medical services to carry a warning about contraindications and the need to consult a specialist. Consent is easiest to collect at booking or at the first visit.
General information, not legal advice for a specific case.The second source of money in the base is patients who started treatment and did not finish it. Here the trigger fires on the service rather than on recency: service A happened, service B did not follow.
In the clinic we analysed, ENT and the laboratory together brought 44% of revenue, so the first pairs were built around them:
| Pair | Call window | Export frequency | Channel |
|---|---|---|---|
| ENT → laboratory | Day 3–21 | Daily | Call for high-value patients, SMS for others |
| First ENT visit → ENT follow-up | Day 7–21 | Daily | Call |
| General practitioner → ultrasound | Day 7–45 | Twice a week | Call or SMS |
| General practitioner → specialist | Day 7–45 | Twice a week | SMS |
| Laboratory → doctor to explain results | Day 3–14 | Daily | SMS, call for high-value patients |
| Procedure room → next procedure in the course | Per the course schedule | Daily | Call |
Timing matters more than the discount here. Three weeks after the first service, interest in continuing treatment drops noticeably, and after a month the patient has usually solved the problem elsewhere or forgotten about it.
Analysis in a spreadsheet changes nothing until front-desk staff get a ready list in the morning. So the end product of this work is a set of reports in the clinic management system or accounting software that build segment lists every day.
Each list has the phone number, date and amount of the last visit, the last service, total spend and a “Recommended action” column: call or SMS, reason and coupon size. Staff record the call outcome from a fixed list: booked, will call back, declined, unreachable, number does not exist, call again later. After a month the clinic sees not only how many calls were made, but which segment and which reason produce bookings.
A separate summary report shows the director the size of each segment and its share of revenue. If Can’t Lose grows while Champions shrinks, the clinic sees churn before it shows up in the till.
To estimate patient value, use cohort-based LTV; for early signs of churn, predictive churn modelling. Feedback from satisfied patients after a return is easy to collect through NPS: a high score should turn straight into a request for a review on maps.
Pushers runs operational marketing for medical clinics. We take over the operational management of marketing and promotion channels, manage contractors and set up advertising ourselves. Work on the patient base is always our first stage: the clinic earns revenue from what it has already paid for, and we see where to send new patients. More on how this fits with maps and advertising is on our healthcare marketing page.
You can start with a free clinic marketing audit: we will look at your patient base and show how many patients you can win back this month.
Almost any base with at least a year of receipt history will do. RFM analysis needs the patient's phone number, visit dates, receipt amounts and service names. Our analysis covered 125,000 receipts over three years, but the share of one-time patients and the return window are visible on a base of a few thousand people.
No. Segmentation and cross-selling need only commercial data: which services were paid for, when and for how much. Diagnoses and doctors' notes play no part in this work, and we do not use them.
It depends on the patient's value. A call costs more, so it goes to regulars, high-value patients and new patients with a large first receipt. Everyone else gets an SMS or a messenger message, and only if they consented to marketing messages.
Compare first-to-second-visit conversion and the share of patients who return after a 90-day pause, before and after the triggers go live. In the clinic we analysed, second-visit conversion fell from 69% in 2023 to 32% in 2025, and restoring it gives the fastest revenue gain.
A fintech marketing agency can build campaigns. It cannot own the compliance review, the KYC drop-off or the multi-market licensing rules that decide whether a lead ever becomes a customer.
A fractional CMO brings strategy and judgment. Without reporting, CRM hygiene and a named owner per number, the engagement produces a slide deck instead of a system.
Ads and search bring the request in. What happens between the click and the booked, attended visit decides whether the spend paid off.
