The document discusses analyzing customer sentiment about eye hospitals through social media data. It presents a case study of a customer journey map for an eye hospital created by analyzing tweets related to eye surgery and appointments. Negative sentiments were expressed regarding long wait times and poor communication. The importance of a positive patient experience with friendly staff in maintaining clean facilities is emphasized. Analyzing emotional language in tweets can provide insights into improving patient satisfaction and promoting recommendations.
2. These are great visual tools to
inspect the delights and pains of
customers
Customer Journey Maps
3. These are great visual tools to inspect the
delights and pains of customers
And (CJMs) shall have a greater value if
coupled with data extracted from social
media such as Twitter
Customer Journey Maps (CJMs)
4. A case study is Customer Journey
Map to an eye hospital
6. Surgery
Post SurgeryMeeting with DrWaitingArrivalResearch
Pre-testingCheck in
Make
appointment
Starts with reviewing
comments and asking friends
Social media is a great source
of information
7. Starts with reviewing
comments and asking friends
Social media is a great source
of information
Surgery
Post SurgeryMeeting with DrWaitingArrivalResearch
Pre-testingCheck in
Make
appointment
First
impressions are
lasting
8. Surgery
Post SurgeryMeeting with DrWaitingArrivalResearch
Pre-testingCheck in
Make
appointment
A special thanks the registrar on duty
on 7th August at 9pm who performed
the procedure in spite of pressure of
emergency calls from elsewhere in the
hospital
10. Surgery
Post SurgeryMeeting with DrWaitingArrivalResearch
Pre-testingCheck in
Make
appointment
have made many
mistakes on making
appointments for my wife
Information and appointments
sent out on white paper in small
print, how they expect a person
with poor sight to read this
records of treatment
may not have been
updated
The hospital system is
designed for the
convenience of the
specialists, not for the
needs of the patient
I wanted better
eyesight, but it’s all
blurred now’
11. What are the words most com-
monly used in tweets pertaining
to eye hospitals globally?
A sample world cloud is shown in
the next slide
14. Analysis of Tweets
Cleanliness, staff co-operation and respecting the
dignity of patients are prime factors of patients’
satisfaction. These results show the importance
of emotional intelligence in the medical field.
15. Super friendly and efficient staff
You will wait multiple hours -- I was here for more than 3 hours, which I
found pretty ridiculous
… my perception of the resident clinic was a little off, because the attending
physician never looked in my eyes
16. He was wonderful in explaining the history of the procedure, the differences
in the procedures themselves, the risks/benefits of each, and recovery time
for each
Two hour wait minimum every time. This is so ridiculous
Meanwhile i think i will end up blind in my right eye
17. If you end up going here, assume well over six hours to complete your
appointment and don't expect a friendly greeting
They apparently do not read the information they demand you send ahead of
time and they got some of my information wrong
The waiting rooms are noisy and crowded
18. ..... including several treatment options that had never been discussed by
previous doctors
and have left feeling that the management and staff left us with a lot to
desire
When going to a place that has a good reputation you should expect high
quality service
19. Emotional Words Are a Must in
Eye Hospitals
Using harsh and negative words may upset the patient to a large scale
20. Negative Words Have Negative
Consequences
Negative feelings of patients leading to angry reactions or passive ones by
not cooperating with the hospital staff
21. Do Not Blame Patients or Narrow
Their Options
Hospital staff must be positive by avoiding blame, explaining different eye
treatment possibilities and promise what the hospital can do
Don’t increase the pain of your patient
22. Maximize delight and minimize pain of your customers at each touch point.
This way they may recommend you to others
24. Net Promoter Score in Healthcare
Promoter
Extremely
Unlikely
Extremely
likely
Passive
How likely are you to recommend?
Detractor
Promoter Passive Detractor
% Promoter % Detractor Net Promoter Score=-
012345678910