One warehouse for inquiries, consultations and bookings,
and real conversion per source market
A medical tourism agency usually has ad spend in one dashboard, inquiries in a messaging app, and booked procedures in a CRM or a spreadsheet nobody fully trusts, which makes it hard to say which source market and channel actually produces booked patients. We connect it all into one warehouse and give you the real conversion numbers per market and channel.
Why medical tourism agencies lose money today
A medical tourism agency typically tracks ad spend in the ad platform’s own dashboard, inquiries in WhatsApp or a shared inbox, and consultations and booked procedures in a CRM or spreadsheet, three systems that were never designed to agree with each other across multiple source markets and currencies. An agency deciding where to spend the next ad dollar is often deciding on inquiry volume alone, without knowing which source market’s inquiries actually turn into booked procedures.
The deeper gap is response time, which this category’s own industry data treats as one of the largest levers on conversion, yet most agencies have no system connecting how fast a specific inquiry was answered to whether it converted. Without that join, response time stays a vague priority instead of a measured one.
A third problem is averaging across source markets. A market producing a high volume of cheap inquiries can look like the best channel in an ads dashboard while actually converting far below a smaller, more expensive market, a distinction that disappears the moment the numbers get blended into one total.
A fourth problem is the long, multi-touch path typical of this category. A patient who first saw an ad weeks before finally messaging, after visiting the site several times in between, gets credited entirely to whichever touchpoint happened last in most simple attribution setups, which systematically undervalues the content that actually built the trust needed to reach out at all.
What we build
A warehouse joining ad platforms, inquiry channels and CRM. Meta and Google Ads on the spend side, WhatsApp and your site chat for inquiries, and your CRM or spreadsheet for consultation and booking stages, reconciled into one database with a daily sync.
A full funnel from inquiry to consultation to booked procedure. Broken out by source market and channel, so you can see exactly where a specific market’s funnel is actually losing patients.
Response-time tracking joined to conversion. So the effect of answering faster is a measured number for your agency, not an assumption borrowed from an industry benchmark.
An AI analyst for ongoing questions, answering questions like “which source market converted best to booked procedures last quarter” in Telegram, with the query it ran.
Typical integrations: Meta and Google Ads, WhatsApp Business API, your CRM, and a daily sync job with historical backfill.
What stays with humans
The AI analyst’s access excludes patient-identifying fields by design, and any decision about which markets or partner clinics to prioritize stays with your team. The warehouse surfaces the numbers; people make the calls. Any judgment about why a specific market underperforms, cultural fit, a weak local partner, pricing mismatch, requires context the data alone cannot provide, and we say so rather than overstating what the dashboard can explain on its own.
Price and timeline
| Model | Price | What you get |
|---|---|---|
| Agency runs it | from $2,500 | We build, sync and maintain the warehouse and dashboards |
| Full control, handover-ready | from $4,250 | Same build, full source code, documentation and the warehouse schema transferred, paid edits available as an option |
Both run on the same 3 to 6 week build.
Related
Pair this with an AI agent for medical tourism agencies so inquiry and response-time data feed the same warehouse, or a website for medical tourism agencies if the inquiry funnel itself needs fixing first. See the full analytics service page. A funnel audit and unit-economics approach of similar depth is detailed in the trading app funnel audit case study, and a two-brand warehouse with an AI analyst is in the analytics hub case study. Get in touch and we will reply with a fixed price and plan.
FAQ
How much does this cost and what do we get for it?
From $2,500 for a warehouse connecting your ad platforms, inquiry channels and CRM, with dashboards on conversion and cost per source market. An AI analyst layer on top is $5,000 and up. A tracking audit alone starts around $800.
How long does it take?
3 to 6 weeks for the warehouse and dashboards. Adding the AI analyst extends that to 6 to 10 weeks.
Which platforms and systems do you connect?
Meta and Google Ads on the spend side, WhatsApp and your site chat for inquiries, and amoCRM, HubSpot or a spreadsheet for consultation and booking stages.
Can it show which source market actually converts best, not just which sends the most inquiries?
Yes, that is the main point. A market sending the most inquiries is not always the one producing the most booked procedures once response time and consultation show-rate are accounted for.
Can an AI analyst really be trusted with real patient inquiry data?
It runs read-only SQL on a prepared data mart, one query at a time, with forced limits, and it shows the query it ran rather than a black-box answer. Patient-identifying fields are excluded from what it can access by design.