Compass Lens Description
The Compass Lens recommendation system objectively selects the ideal lens for each patient by considering feedback from previous patients’ lens experience.
The best lens for each patient is selected by the Compass Lens Algorithm, which is constantly learning and improving over time.
MACHINE LEARNING*
*Patent number: WO2017222835
Compass Description
• Visual profile: Prescription / Previous lens / Expectations / Lifestyle
• ECPs get an unique customer ID when ordering the patients lenses
• Ability to track rejections and fix them
• Allows ECP to gather customer feedback
• Recommends second pair to the ECP
Compass LensPlatform
• Unique technologically advanced lens system that has never been available before
• Consistent way of gathering feedback
• Capacity to track patient satisfaction
• Reduces risk of non-adapts / rejections
• A product that is always up-to-date
• More consistency
• The “what’s next” answer objectively guided
• A system that guides you in the right direction
RIGHTNOW
OVERTIME
YOU
, AS
A C
OM
PAN
Y
WHAT Compass Lens provides you now and brings in the future
• Latest lens innovation
• Easy lens solution
• Sophisticated platform to prescribe lenses
• Automatic system that fixes rejections cases
• Differentiation
• Higher loyalty & credibility
• Security when prescribing the next progressive lens to a patient
• Minimize non adaptation cases
RIGHTNOW
OVERTIME
DO
CTO
RS / EC
PS
WHAT Compass Lens provides you now and brings in the future
• Better buying experience
• Higher lens satisfaction
• Incentives for providing feedback – optional
• Greater guarantee of adaptation
• An even higher better visual experience
• Easy transition to their next pair of progressive lenses
RIGHTNOW
OVERTIME
YOU
R P
ATI
ENTS
WHAT Compass Lens provides you now and brings in the future
is the one that meets patient expectationsand increases patient satisfaction
THE BEST LENS
PRESCRIBING the best posible lens for each patient
EASIESTSCENARIOS
ALWAYSA CHALLENGE
There is no one-size-fits-all lens…
… so many variables need to be considered…
…there isn’t any objective criteria
PRESCRIBING the best posible lens for each patient
HIGH SATISFACTION NON-ADAPT / REJECTION
Customer’s expectations
A constant improvement is
important
The last opportunity
Can’t predict if the next choice will be better
HARDERSCENARIOS
ALWAYSA CHALLENGE
PRESCRIBING the best posible lens for each patient
An objective way to select the best lens for each wearer, and fix rejections, brings added value
PRESCRIBING A LENSIS A HARD TASK
PRESCRIBING the best posible lens for each patient
The wearer’s lens feedback is the most important variable, so it should be part of the lens selection process and we all should learn from it.
CUSTOMER SATISFACTIONIS EVERYTHING
PRESCRIBING the best posible lens for each patient
THE IDEAAN OBJECTIVE WAY TO SELECT THE IDEAL LENS FOR EACH PATIENT, AND LEARNING FROM PREVIOUS WEARER FEEDBACK
It is successfully applied by different companies worldwide in other industries.
MACHINELEARNING
INCREASING Customer Satisfaction
A better service that is fully adapted to the wearer’s preferences, likes and needs.
FLEXIBLE & FULLYCUSTOMIZED
INCREASING Customer Satisfaction
Machine learning algorithms constantly learn from other patients like you.
PERSONALRECOMMENDATIONS
INCREASING Customer Satisfaction
It is based on the same principle, IT LISTENS TO THE WEARERS AND
LEARNS FROM THEM
INCREASING Customer Satisfaction
1 SELLING PROCESS
Compass ECP platform. Clara ID + job info +
visual profile
2 Compass ALGORITHM
Selects the best lens for Clara
FEEDBACK
Email / Compass ECP
web interface
3
CLARAThe Beginnings
• Visual profile : Rx + lifestyle + expectations + previous lens
• Job info
• Selected lens
• Wearer ID
• Feedback : satisfied / non satisfied
Compass Lens DATA BASE
collects data from ALL lens wearer’s: SATISFIED
NON
SATISFIED
The Beginnings
HOW?
DAVID
1 SELLING PROCESS
Compass ECP web. David + job info + visual
profile
2 Compass ALGORITHM
Selects the best lens for David: Lens design A
The Evolution
Compass Lens algorithm starts finding
similar satified wearers like David (based on his visual profile)
The Evolution
DAVID
By machine learning wearer satisfaction tendencies are detected. The Compass Lens algorithm compares wearers with low satisfaction rates to those with high satisfaction rates and similar visual profiles and/or job data.
A : lens design
DAVIDAAA
AAA A
A
The Evolution
GOOD JOB!
This is how CompassAlgorithm increaseswearer’s satisfacctionover time.
FEEDBACK
DAVIDThe Evolution
Experiences from controlled wearer trials
more than
1500patients
more than
7years of R&D
IT HAS BEEN PROVEN TO WORK EXPERIMENTAL
CONDITIONS
2017-2018
Compass LensAlgorithm
more than
150optical stores
more than
5000feedback collected
IT HAS BEEN PROVEN TO WORKREAL CONDITIONS
2017-2018
Compass LensAlgorithm
It is constantly supervised and
validated by experienced
optometrists, engineers & data
analysis experts
IT HAS BEEN PROVEN TO WORK
Compass LensAlgorithm
PAUL51 % Design A
49 % Design B
51 % Design A
49 % Design B
In case of rejection Compass Algorithm recommends the second closest option.
Resolving Non Satisfied Patients
Compass Lens is a data-driven recommendation system created to
increase patient’s lens satisfaction and improve over time
The Compass Lens analysis interface is a powerful tool that gives you access to your lens
business data and allows you to accurately define your business strategy for success
Conclusions