.png)
Back to home
Back to home
%20(1).png)
By Viktorija Vlasenko, Managing Partner and Founder of Adore Digital
Artificial intelligence is rapidly becoming part of everyday healthcare marketing. Medical clinics are already using AI to analyse advertising performance, support CRM workflows, summarise patient calls, translate communication, develop content and automate repetitive administrative tasks.
But the more AI enters our work, the more important another question becomes: where does it actually create value?
Since 2018, I have worked specifically with healthcare and beauty businesses, including medical clinics and doctors' practices. Over the years, I have seen marketing technology change significantly. New platforms appear, advertising becomes increasingly automated, CRM systems become more sophisticated, and now AI is entering almost every part of the digital workflow.
Yet one principle has remained surprisingly consistent.
Technology itself does not fix a patient journey that does not work.
This is why, at Adore Digital, we do not start an AI conversation by asking which tools a clinic should implement.
We start with the patient journey.
Our approach: Map the patient journey first. Identify friction second. Automate third.
This is the first article in our AI & Healthcare series. I want to use this series to explore AI from a practical healthcare marketing perspective: where it can improve patient acquisition and clinic operations, where human judgement remains essential, and what European healthcare organisations need to consider as AI becomes part of everyday work.
Medical clinics can use AI to analyse advertising and conversion data, structure patient enquiries, support CRM workflows, summarise calls, assist patient coordinators, translate communication and automate repetitive follow-up tasks.
But the biggest opportunity is not implementing a single AI tool. It is understanding where patients, information and time are being lost across the patient journey, and then deciding where AI or automation can remove that friction.
For most clinics, the best starting question is therefore not:
"Which AI tool should we buy?"
It is:
"Where are we currently losing time, information and patients?"
Healthcare marketing is often evaluated through advertising metrics. We look at impressions, clicks, cost per click, cost per lead and the number of enquiries generated.
Of course, these metrics matter. But they tell us only how efficiently we generated initial interest. They do not tell us whether that interest became a patient.
The actual digital patient journey is much longer:
Google / Social Media → Website → Enquiry → CRM → Patient Coordinator → Consultation → Treatment → Follow-up
This distinction is especially important for private clinics investing significantly in digital marketing and for clinics attracting international patients.
A clinic can run successful Google Ads or Meta campaigns, generate hundreds of enquiries and still struggle to turn those enquiries into consultations and treatments.
In that situation, generating more leads may not solve the problem.
The problem may not be advertising. It may be what happens after the lead arrives.
This is where AI becomes much more interesting for healthcare marketing.
Not because it can generate another advertisement or another piece of content, but because it can help us understand and improve what happens between the first click and the final treatment.
When we look at opportunities for AI and automation, we start by mapping the patient journey.
We want to understand what happens after someone sees an advertisement or discovers the clinic through search. How quickly is the enquiry answered? Where is the information stored? Does it reach the CRM? What happens after the first conversation? Who follows up? At what point do prospective patients disappear?
The next step is identifying friction.
Response times may be too slow. Perhaps coordinators spend too much time manually transferring information between systems. Perhaps WhatsApp conversations and calls never reach the CRM. Marketing could report the cost per lead but cannot tell management which campaigns eventually generated treatments.
Only after understanding these problems should technology enter the conversation.
Sometimes AI is the right solution. Sometimes conventional automation is enough. Sometimes the clinic needs better CRM implementation or analytics. And sometimes the real problem is simply a process that needs to be redesigned.
Technology should support the patient journey. The patient journey should not be redesigned around a new AI tool.
One of the simplest ways to understand this is to look beyond lead generation.
Imagine that a clinic generates:
100 leads → 40 contacted → 15 consultations → 5 treatments
If we look only at cost per lead, we see the first number.
But as a healthcare marketer, I am much more interested in what happened between those numbers.
Why were 60 leads not contacted successfully? Was the response too slow? Did they arrive outside working hours? Was the contact information incorrect? Were the enquiries distributed properly?
Then we need to understand why only 15 of the 40 prospects we contacted booked a consultation. Perhaps they did not receive enough information. There may have been recurring concerns about pricing, treatment, travel or trust.
And finally, why did only five consultations become treatments?
This is where healthcare marketing starts becoming much more than advertising.
A clinic should ideally understand not only its cost per lead, but also its lead-to-contact rate, response time, consultation conversion, treatment conversion and ultimately patient acquisition cost. For international clinics, it can also be extremely useful to understand how these numbers differ by market, country, procedure and marketing source.
AI can help analyse patterns across larger volumes of this data.
But there is a condition.
The data has to exist.
If advertising, CRM, calls and patient outcomes are disconnected, AI cannot magically reconstruct a patient journey that the clinic itself cannot see.
In that case, the first job is not AI. It is data and process integration.
When AI is connected to a specific problem rather than treated as a goal in itself, the opportunities become much clearer.
I would not interpret this table as a recommendation to automate every stage.
The more useful question is: where is technology capable of removing a meaningful constraint without damaging the patient experience?
This is something healthcare businesses sometimes underestimate.
Advertising may create demand, but in many private clinics a person still needs to turn that demand into a patient journey.
The role of the patient coordinator becomes even more important when the clinic works internationally.
A patient considering treatment in another country may need to understand the procedure, pricing, consultation process, travel arrangements, accommodation, documentation, payment, and what happens after returning home.
This is not a simple sales transaction.
The patient may have several conversations before making a decision, and each conversation can either increase or reduce confidence in the clinic.
This is why I do not see replacing patient coordinators as the most interesting use of AI.
I see much more potential in removing repetitive administrative work around them.
AI can assist with conversation summaries, translations, draft follow-ups, CRM notes and identifying next actions. The coordinator can then spend more time on the part of the journey where human communication matters most.
Healthcare is built on trust. Automation should support that relationship, not weaken it.
I started my career in communications, long before AI became part of everyday marketing. My background is in Public Relations, and I have worked in television and as a press secretary. I founded my first business in 2014 and, since 2018, have focused specifically on digital marketing for healthcare and health & beauty.
Technology has changed enormously during that time.
But one lesson I keep returning to is that generating demand and converting demand are two different problems.
Digital marketing can bring a prospective patient to a clinic. It cannot guarantee that the enquiry will be answered quickly, that the right information will reach the patient, that the CRM will be updated, or that follow-up will happen consistently.
This is why our work at Adore Digital increasingly looks beyond the advertising account.
For us, patient acquisition is the relationship between:
Marketing + Website + Communication + CRM + Patient Coordination + Conversion
AI can make parts of this system faster and more intelligent. It can help us research markets, analyse larger volumes of information, identify patterns, structure data and reduce repetitive work.
But it does not replace understanding the patient, the market, the clinic's positioning or its commercial strategy.
A language model can produce twenty advertising headlines in seconds. It does not automatically know whether a medical claim is accurate, whether a message reflects the clinic's real competitive advantage or whether a prospective patient in a particular market will trust it.
That requires context and judgement.
AI can accelerate specialist work. It does not remove the need for specialists.
International patient acquisition is an area where this becomes particularly important.
A person considering medical treatment abroad is making a complex decision.
They are not simply comparing two doctors. They may be deciding whether they trust a clinic they have never visited, whether travelling to another country is worth it, what the complete treatment journey will cost, how long they need to stay and what support they will receive before and after treatment.
Every unanswered question creates friction.
AI can help clinics manage parts of this complexity. It can support multilingual communication, summarise conversations, structure enquiries and help identify recurring patient questions or differences between markets.
But there are limits.
Translation is not localisation. Automation is not patient experience. And more leads do not necessarily mean more patients.
The objective of international healthcare marketing is not simply to generate enquiries from another country. It is to build a patient journey that reduces uncertainty and creates enough trust for someone to make an important healthcare decision, often far from home.
The excitement around AI makes it tempting to look for places to implement it simply because the technology exists.
Clinics should be careful with this approach.
If leads are not consistently entering the CRM, if nobody owns the follow-up process, if clinics cannot connect marketing data to patient outcomes, or if staff are already using unapproved AI tools with sensitive information, adding another AI platform may create more complexity rather than less.
A weak process does not automatically become a strong process because AI is added to it.
This is why our approach remains deliberately simple:
Map the patient journey first. Identify friction second. Automate third.
There is another reason healthcare organisations need to approach AI differently from many other industries.
A person can begin sharing sensitive information from the very first enquiry. They may describe symptoms, send medical photographs, discuss a diagnosis or provide information about previous treatments before they have ever attended a formal consultation.
This means that marketing, CRM and patient coordination workflows can contain sensitive health information much earlier than organisations sometimes expect.
A practical rule is therefore worth establishing:
Do not enter identifiable patient information, medical photographs, consultation recordings or clinical notes into an AI service that has not been approved for that purpose.
For European healthcare organisations, AI adoption also needs to be considered alongside GDPR, the EU AI Act and other applicable healthcare and medical device requirements.
Not every AI system used by a clinic has the same regulatory profile. A marketing analysis tool, a patient-facing chatbot and an AI-enabled medical device may involve very different risks and obligations.
This topic deserves much more than a few paragraphs, so we will explore it separately in this series.
In the next articles, we will look more closely at whether medical clinics can use ChatGPT with patient data, as well as what the EU AI Act means in practice for medical clinics and healthcare providers.
If there is one practical exercise I would recommend to clinic management, it is not creating a list of AI platforms.
Lay out the patient journey and put it on the table.
Start with the first marketing touchpoint and follow the patient through enquiry, CRM, communication, consultation, treatment and follow-up.
Then ask where patients disappear, where responses slow down, where information is lost, where employees repeat the same tasks and where management lacks visibility.
Also ask what AI your organisation is already using. A marketing manager may already be using generative AI for content. A coordinator may use an AI translator. A CRM or call platform may already be generating summaries or transcripts.
Only after you understand the current journey does it make sense to decide what to automate.
Sometimes the answer will be AI.
Sometimes it will be better marketing automation, better CRM implementation, improved analytics or simply a better process.
Medical clinics can use AI to analyse advertising and conversion data, categorise enquiries, assist CRM workflows, summarise calls, support multilingual communication and automate repetitive follow-up tasks. The most useful applications depend on where friction exists in the clinic's patient journey.
AI can support patient acquisition by helping clinics understand lead quality, improve response workflows, identify conversion patterns and reduce repetitive work. However, AI cannot compensate for weak marketing, disconnected data or an inconsistent patient journey.
In my view, that should not be the default objective. A more useful application is often to reduce repetitive administrative work, so coordinators can spend more time communicating with prospective patients and managing complex situations.
Clinics need to be particularly careful when identifiable patient or health information is involved. Patient data, medical photographs, clinical notes and consultation recordings should not be entered into AI services that have not been approved for that purpose. We will explore this question in detail in a separate article in this series.
Potentially, yes, but the requirements depend on the type of AI system, its intended purpose and how the clinic uses it. A marketing tool and an AI-enabled medical device do not necessarily have the same obligations. We will cover the EU AI Act for medical clinics separately in this series.
Start with the patient journey, not the technology. Understand where patients, information and staff time are being lost. Then determine whether the right solution is AI, conventional automation, better CRM implementation, improved analytics or a process change.
AI is already becoming part of healthcare marketing and the digital patient journey.
But I do not believe the competitive advantage will come from having the largest number of AI tools.
It will come from knowing where technology genuinely improves the relationship between marketing, data, operations and patient experience, and where human expertise needs to remain central.
At Adore Digital, our starting point remains:
Map the patient journey first. Identify friction second. Automate third.
Before asking where your clinic can add AI, ask a more useful question:
Where are we currently losing time, information and patients?
This is the first article in our AI & Healthcare series, and we will continue exploring this topic from several perspectives.
In the next articles, we will look at AI and patient data, the EU AI Act for medical clinics, practical applications of AI in patient acquisition, and the role AI can play in international patient journeys.
The technology will continue changing quickly. Our goal with this series is to focus on what those changes actually mean for clinics, healthcare marketers and the people responsible for turning digital interest into real patient journeys.
Viktorija Vlasenko is the Managing Partner and Founder of Adore Digital, a digital marketing agency specialising in healthcare and health & beauty.
With a professional background in Public Relations, Viktorija began her career in communications, including working in television and as a press secretary. She moved into entrepreneurship in 2014 and has focused on digital marketing for healthcare and health & beauty since 2018.
Today, she works with medical clinics, doctors and healthcare businesses on digital growth strategies, international patient acquisition, and marketing funnels that connect advertising, communications, CRM, and the wider patient journey.
Viktorija describes her approach as digital-first, but not technology-first. She believes digital marketing, data, automation and AI should solve real business problems, improve the patient journey and help healthcare businesses grow sustainably.
Connect with Viktorija Vlasenko on LinkedIn
This article provides general information and does not constitute legal, regulatory or medical advice.
Medical clinics can use AI to analyse advertising and conversion data, categorise enquiries, assist CRM workflows, summarise calls, support multilingual communication and automate repetitive follow-up tasks. The most useful applications depend on where friction exists in the clinic's patient journey.
AI can support patient acquisition by helping clinics understand lead quality, improve response workflows, identify conversion patterns and reduce repetitive work. However, AI cannot compensate for weak marketing, disconnected data or an inconsistent patient journey.
In my view, that should not be the default objective. A more useful application is often to reduce repetitive administrative work, so coordinators can spend more time communicating with prospective patients and managing complex situations.
Clinics need to be particularly careful when identifiable patient or health information is involved. Patient data, medical photographs, clinical notes and consultation recordings should not be entered into AI services that have not been approved for that purpose. We will explore this question in detail in a separate article in this series.
Potentially, yes, but the requirements depend on the type of AI system, its intended purpose and how the clinic uses it. A marketing tool and an AI-enabled medical device do not necessarily have the same obligations. We will cover the EU AI Act for medical clinics separately in this series.
Start with the patient journey, not the technology. Understand where patients, information and staff time are being lost. Then determine whether the right solution is AI, conventional automation, better CRM implementation, improved analytics or a process change.
AI is already becoming part of healthcare marketing and the digital patient journey.
But I do not believe the competitive advantage will come from having the largest number of AI tools.
It will come from knowing where technology genuinely improves the relationship between marketing, data, operations and patient experience, and where human expertise needs to remain central.
At Adore Digital, our starting point remains:
Map the patient journey first. Identify friction second. Automate third.
Before asking where your clinic can add AI, ask a more useful question:
Where are we currently losing time, information and patients?
This is the first article in our AI & Healthcare series, and we will continue exploring this topic from several perspectives.
In the next articles, we will look at AI and patient data, the EU AI Act for medical clinics, practical applications of AI in patient acquisition, and the role AI can play in international patient journeys.
The technology will continue changing quickly. Our goal with this series is to focus on what those changes actually mean for clinics, healthcare marketers and the people responsible for turning digital interest into real patient journeys.
Viktorija Vlasenko is the Managing Partner and Founder of Adore Digital, a digital marketing agency specialising in healthcare and health & beauty.
With a professional background in Public Relations, Viktorija began her career in communications, including working in television and as a press secretary. She moved into entrepreneurship in 2014 and has focused on digital marketing for healthcare and health & beauty since 2018.
Today, she works with medical clinics, doctors and healthcare businesses on digital growth strategies, international patient acquisition, and marketing funnels that connect advertising, communications, CRM, and the wider patient journey.
Viktorija describes her approach as digital-first, but not technology-first. She believes digital marketing, data, automation and AI should solve real business problems, improve the patient journey and help healthcare businesses grow sustainably.
Connect with Viktorija Vlasenko on LinkedIn
This article provides general information and does not constitute legal, regulatory or medical advice.
