Clinic Growth Made Easy with Online Marketing – 2025
Discover how clinics can grow patient footfall and revenue using ethical, NMC-compliant online marketing. A complete digital roadmap for 2025...
Friction points are moments during a patient’s journey where something goes wrong or doesn’t feel right. These can happen at different stages, such as:
Even small problems like unclear directions, delays, or confusing bills can make patients unhappy.
Example: A patient books an appointment online but never gets a confirmation message. They arrive confused and unsure. This small mistake creates frustration, and that’s a friction point.
Data helps us understand what is going wrong, where it’s going wrong, and why. Here are a few ways hospitals can use data to find friction points:
After visiting a hospital, patients often fill out surveys or leave online reviews. This feedback is very useful.
Example: If many people say, “The waiting time was too long,” then long waits are clearly a problem.
What to Do: Collect this feedback regularly. Read comments carefully to find common issues. Tools like Google Forms, SurveyMonkey, or even Google Reviews can help.
Many patients visit a hospital’s website or use an app to book appointments or check information. By looking at how they use these tools, you can find where they get stuck.
Example: If most users leave the appointment page without booking, maybe it’s too hard to use or has errors.
What to Do: Use tools like Google Analytics or Hotjar to see how people move around your website or app. Find out which pages they leave quickly or which buttons they don’t click.
When patients call your hospital or use a chatbot, they often ask questions or report problems. These calls and chats can show what’s unclear or not working.
Example: If many people ask, “Where is the hospital located?” maybe your website doesn’t clearly show directions.
What to Do: Review call logs or chatbot conversations. Look for repeated questions. That’s where patients are confused.
Inside the hospital, a lot of data is already being recorded. This includes:
Example: If patients are waiting 45 minutes to see a doctor, even with an appointment, that’s a sign of a system problem.
What to Do: Use this data to compare different departments. Find areas where time or processes can be improved.
Patients often post their experiences on social media platforms like Instagram, Facebook, Google, or Practo. These reviews can tell you what patients love or hate about your services.
Example: If several patients complain online about rude staff or unclear bills, those are friction points.
What to Do: Regularly check reviews and comments. Use free tools like Google Alerts or social listening tools to track your mentions.
Once you know where the problems are, you can start fixing them. Here are some examples:
Problem | What Data Showed | What to Do |
Long Waiting Times | Hospital logs show long delays | Adjust doctor schedules, add reminders, or reduce overbooking |
Booking is Hard | Website data shows users leave the page | Make booking simpler and mobile-friendly |
Many Missed Appointments | Data shows high no-shows | Send reminders by SMS or WhatsApp |
Confusing Bills | Feedback says billing is unclear | Explain charges better and show sample bills online |
Poor Staff Behavior | Reviews mention rude behavior | Train staff for better communication and empathy |
Yes! Once you collect enough data, you can start predicting when and where problems may happen. This is called predictive analytics.
Example:
This way, you don’t just fix problems you prevent them.
In healthcare, every small issue matters. A long wait, a confusing form, or a rude reply can make patients feel uncomfortable or lose trust.
By using data, hospitals and wellness centers can find out what patients are struggling with, and take steps to improve those areas. At HMS Consultancy, we help you make data driven decisions to create a smoother, friendlier, and more caring patient experience.
Let’s use data to make healthcare simpler, smarter, and more human.
Written by Jay Wandile
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