Notes for owners · CRM, automation and RevOps
Reading a clinic's enquiry data: from ad click to first visit
Four counts, enquiries, replies, bookings and visits, show where a clinic's patients drop out between an ad and the first consultation, and which gap to fix before spending more.
The GullySales team · Updated 17 Oct 2026 · 7 min read
Rules for this trade differ by state and professional body, and they change. Check the current position with your own council or adviser before you act on anything here.
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To read a clinic's enquiry data, count four things for the same period: enquiries received, enquiries replied to, appointments booked, and patients who actually attended a first visit. Then divide each count by the one before it. The step with the lowest share is where patients are leaving, and in a clinic that is often after the click, not in the advert. Check it against head-count too, then fix that step before you spend more on the top.
Why click and cost numbers are not enough
An ad platform tells you clicks, calls and form fills. That is the top of the journey. A clinic that judges a campaign on cost per enquiry may be paying for people who never get a proper answer. Others book and do not arrive.
Take an invented example: a cosmetic dentistry clinic in Ludhiana running a Google ad for smile correction. The dashboard says the cost per enquiry is low and the owner is pleased, yet the chairs are not filling. Nobody has counted what happened between the call and the appointment.
The four counts
| Count | What it is | Where to find it |
|---|---|---|
| Enquiries | Every distinct person who asked: call, WhatsApp, form, walk-in | One shared sheet, one line per person |
| Replied | Enquiries where a human answered the question | A column: replied, with the time |
| Booked | Replies that turned into a fixed appointment | Your appointment book, matched by number |
| Visited | Booked patients who came and were seen | The day's register or billing |
Do not count missed calls as enquiries until someone has rung back. Record them separately: "missed, called back, spoke" is a reply; "missed, no call back" is a loss, and it belongs in its own column.
The arithmetic
Use any four-week period. The numbers below are illustrative, not a benchmark.
120 enquiries. 84 replied. 38 booked. 27 visited.
Divide step to step:
- Replied: 84 of 120 is 70 per cent. Thirty per cent of enquirers never got an answer.
- Booked: 38 of 84 is 45 per cent.
- Visited: 27 of 38 is 71 per cent. Nearly three in ten booked and did not come.
The biggest single fall in head-count is between replies and bookings: forty-six people spoke to the clinic and did not book. Next come the thirty-six who got no reply at all, then eleven no-shows. Each has a different cause and a different fix, and the lowest percentage is not always the largest loss, so look at both.
What each gap usually means
Enquiries to replies. Calls at lunch, WhatsApp messages after OPD hours, forms that land in an inbox nobody opens. The fix is a rota, not an ad. Decide who answers at which hour and what the clinic does with a call it misses.
Replies to bookings. The patient asked, was told, and went away. Look at what the first reply said. Did it quote a price without context? Offer a slot? Ask what the problem was? A reply that only gives the fee and the address leaves the patient to make the next move, and many will not. Our post on the journey from online enquiry to appointment covers the reply itself.
Bookings to visits. Patients booked a day ahead and something got in the way. A reminder the day before and a way to reschedule with one reply usually reduces this. If the no-show is the same few slots every week, look at the slot, not the patients.
Which channel brought which patient
Once the four counts are in one sheet, add a column for the source. For calls, a separate tracking number per channel is cleanest; failing that, the front desk asks "how did you hear of us?" and writes the answer down. Then run the four counts by source.
An ad may bring many enquiries and few visits, while a doctor's referral or a search for the clinic's name brings fewer enquiries and a higher share of visits. Judge each channel on visits and, later, on treatments completed, not enquiries. See call tracking for advertising for the tracking route.
The Ludhiana clinic, one column later
Back to the invented clinic. Of the 120 enquiries from the ad, only 84 were replied to, because the ad ran in the evening and the front desk shut at 7 pm. Of the 84, 38 booked. The owner adds one more column, the hour each enquiry arrived, and finds that 25 of the 36 unanswered ones came after 7. So the doctor's assistant checks WhatsApp until 9 pm and answers the evening enquiries, which costs the clinic extra hours of pay.
In the next four weeks, say, the replied share rises from 70 to 85 per cent, but bookings from those late replies are fewer than the daytime ones, since people who write at 8 pm are often only comparing prices. The other eleven unanswered enquiries were forms sent to an inbox nobody opened, which is a separate fix. The ad was left alone, because the counts pointed after the click.
When this reading goes wrong
- If you have fewer than thirty enquiries in the period, percentages jump around. Read the lines one by one instead.
- Treatments with a long thinking time, such as implants or surgery, book weeks after the first enquiry. Count by the date of the enquiry, and revisit the period later.
- If the sheet is filled from memory at the end of the week, the replied column will be wrong. Fill it as you go.
Setting up the five columns
Set up the four counts and one source column in a shared sheet today, and make one person responsible for filling it as enquiries arrive. After a period you choose, divide step by step and find the lowest. If the sheet outgrows you, see marketing attribution, and for more on clinics visit the healthcare hub. When you are ready, tell us what you need.
