Liquid customization - Megan Meeker

Liquid Customization
And Personalizing the Guest
Experience at Scale

WAQ • Liquid Customization Proprietary & Confidential 2
Who am I?

3WAQ • Liquid Customization Proprietary & Confidential
Who am I?
Megan Meeker 
Interaction Design Principal  
Connected Products Group

Our focus is on delivering beautiful and functional
products that connects to your customers. From
prototyping to tooling, we support our clients
through product realization spanning hardware,
software and services.
Our process fuses
physical and digital
design to produce
holistic
experiences.

College Thesis

College Thesis
If you take all of Starbuck’s core
beverages, multiply them by the
modifiers and the customization
options, you get 87,000 combinations.
Tall, Non-Fat Latte With
Caramel Drizzle
Grande, Iced, Sugar-Free,
Vanilla Latte With Soy Milk
Triple, Venti, Soy, No Foam
Latte
Triple, Venti, Half Sweet, Non-
Fat, Caramel Macchiato
Decaf, Soy Latte With An
Extra Shot And Cream
Tall, Half-Caff, Soy Latte At
120 Degrees
Non-Fat Frappuccino With
Extra Whipped Cream And
Chocolate Sauce
Grande, Quad, Nonfat, One-
Pump, No-Whip, Mocha
Decaf Soy Latte With An Extra
Shot And Cream
Venti Iced Skinny Hazelnut
Macchiato, Sugar-Free Syrup,
Extra Shot, Light Ice, No Whip
Quad Grande, Non Fat, Extra
Hot Caramel Macchiato Upside
Down
Iced, Half Caff, Ristretto, Venti,
4-Pump, Sugar Free,
Cinnamon, Dolce Soy Skinny
Latte
Caramel Macchiato, Venti,
Skim, Extra Shot, Extra-Hot,
Extra-Whip, Sugar-Free
Grande Chai Tea Latte, 3
Pump, Skim Milk, Lite Water,
No Foam, Extra Hot
Tall Nonfat Latte, 2 Percent
Foam
Venti 1/2 & 1/2, 10 Pumps
Vanilla, Extra Whip

What is customization?

cus·tom·i·za·tionˌ kəstəmīˈzāSH(ə)n
First introduced in 1930.
To modify or build according to  
personal specifications or preference:
to customize an automobile.

0
0.025
0.05
0.075
0.1
1940 1960 1980 2000
Usage in Written Language

How did we get here?

12
WAQ • Liquid Customization Proprietary & Confidential
Pre-Industrial Era

Businesses
operated as local,
independent, and
often family-
owned
enterprises.

The first Industrial
Revolution originated
in Britain’s textile
industry. The
Spinning Jenny
created the world’s
first factory.

The impact of the
railroads welcomed the
emergence of larger
companies, with larger
labor forces that were
generating and
distributing mass-
produced goods.

16
Industrial Revolution
16

Assembly Lines

Any customer can have a car
painted any color that he
wants so long as it is black.”
“
18

19
We find the forced,  
no alternative garish
décor revolting and
dictatorship-like.”
”

There has been a push
for mass personalization
with a finite set of
variables.
21

22

Algorithms

Algorithms are step by step
instructions or recipes. They predate
computers by thousands of years.

Algorithm = Logic + Control”
— Robert Kowalski
”

Algorithms
As basic information gets broken down, algorithms
put the data back together translating code into
what we see.
• Online dating
• Kidney matching
• Route planning
• Face detection
• Shopping online
• Email
• Checked luggage
• College admissions

Algorithms
In 1963 bubble sorting was
developed where the largest
unsorted objects bubble to
the top. It considers objects
in pairs and swaps them if
they’re in the wrong order
over and over until all objects
are in the right order.

Bubble Sort

Merge Sort

In Sort Joke Here

Algorithms
There are 20+ current sorting algorithms all
achieving the same result by different means.
There are new and more more complicated
algorithms created everyday… and with
today’s technology they can begin to write
themselves. This brings us to the birth of
Artificial Intelligence.
• Merge sort
• Quick sort
• Shell sort
• Select sort
• Insert sort
• Heap sort
• Pigeon hole sort
• Introsort
• Timsort
• Cubesort
• Binary tree sort
• Cycle sort
• Library sort
• Smoothsort
• Strand sort
• Tournament sort
• Cocktail sort
• Comb sort
• Gnome sort

A Brief History of AI

Artificial Intelligence enables machines
to have intelligence parallel (or greater)
to that of a human, giving them the
capability to perform tasks that requires
human intelligence.

The Birth of AI: 1956
The Dartmouth Summer Research
Project on Artificial Intelligence is
considered the seminal event for AI.
The proposal for the conference
included: "every aspect of learning or
any other feature of intelligence can
be so precisely described that a
machine can be made to simulate it".

37Odopod • EmTech Overview Proprietary & Confidential

The Golden Years: 1956 - 1974
In 1966, Joseph Weizenbaum's
ELIZA, the first chatbot, could carry
out conversations that were so
realistic that users occasionally
were fooled into thinking they were
communicating with a human being
and not a program.


Welcome to
EEEEEE  LL      IIII  ZZZZZZZ   AAAAA
EE      LL       II       ZZ   AA   AA
EEEEE   LL       II     ZZZ    AAAAAAA
EE      LL       II    ZZ      AA   AA
EEEEEE  LLLLLL  IIII  ZZZZZZZ  AA   AA
ELIZA: Is something troubling you ?

YOU:

39Odopod • EmTech Overview Proprietary & Confidential

The First AI Winter: 1974 - 1980
Peak of
Expectations
Disillusionment Enlightenment Profitability
1980s AI Winter 1990s 21st Century
Excitement Despair Confidence
Visibility

AI Now: 1993 - Present
1987 - 1993 
The 2nd AI Winter
happens when funding
was cut and Apple and
IBM computers gained
speed and power.
1997 
Deep Blue became the
first computer chess-
playing system to beat a
reigning world champion.
2005 
A Stanford robot won the
DARPA Grand Challenge
by driving autonomously
for 131 miles along an
unrehearsed desert trail.
2007 
CMU won the DARPA
Urban Challenge by
autonomously navigating
55 miles in an Urban
environment adhering to
traffic laws.

AI Now: 1993 - Present
2011 
In a Jeopardy! match,
IBM's Watson, defeated
the two greatest
Jeopardy! champions.
2011 
Siri is introduced on the
iPhone 4s.
2014 
Amazon launches Alexa
and Eugene Goostman, a
chatbot, passes the
Turing Test (meaning
humans believe it is a
human).
2017 
Google’s AI AlphaGo
beats the world
champion in the complex
name of Go.

AI Future
A timeline of when machines can exceed human
performance.2024
Translating
Languages
2025
Assem
bling
Legos2026
W
riting
High
SchoolEssays
2027
Driving
Autonom
ousTrucks
2029
Running
a
5K
Race
2031
W
orking
in
Retail

AI Future
A timeline of when machines can exceed human
performance.
2049
W
riting
a
NYT
BestSeller
2053
W
orking
asa
Surgeon

By 2020 we will be flooded with data.
1.5 GB/Day - The Average Internet User
4 TB/Day - Autonomous Vehicles
5 TB/Day - Connected Airplanes
5 PB/Day - Smart Factories

Data is the newest natural resource.

Machine Learning

Machine Learning is a subset of Artificial
Intelligence which aims at providing
machines with the ability to learn
without explicitly programming them.
Once built, machines will be able to
evolve and adapt when they are exposed
to new data.

Machine Learning
Supervised Learning 
Learning known patterns
• Labeled data
• Direct feedback
• Predict outcome
Unsupervised Learning 
Learning unknown patterns
• No labels
• No feedback
• Find hidden structure
Reinforcement Learning 
Generating data and
learning patterns
• Decision process
• Reward system
• Learn series of actions

Deep Learning is a subset of Machine
Learning which focuses on an area of
algorithms which was inspired by our
understanding of how the brain works.

Why Deep Learning?
Data
Accuracy
Deep Learning
Traditional
Machine Learning

The world shapes us,  
and we get to shape the world.

Participatory Customization

54
Experiences of the future may look
increasingly like stores of the past, but
this time its what AI and machine
learning technology does with data
that makes true customization and
personalization possible.

Participatory Design
Contexts are always shifting, because
requirements vary from task to task, and also
because ability and tendency vary from
individual to individual.
• Weather
• Heartbeat
• Steps
• Who you are with
• Time of day
• Mood

Experience is perpetually on the move.

A platform is a foundation
for contributions that are
never complete.
1. Create a flexible
framework
2. Plan for what is known
3. Start improvising around  
the unknown

Jazz has common rules to
ensure a fruitful process.
The first rule of improv is
“Yes and….”

59
Personalized
Experiences
and Services

60
Waze

61
Sephora
61Lyft • Who is MM? Proprietary & Confidential
Sephora

Dinning Preferences Dinning Preferences
w
ning
Sharing your preferences will allow
Our maitre d’s to create the best dining
experiene for you.
Preferred
Dining Time
Play it by ear
Play it
by ear
8:30 pm
every night
8:30 pm
every night
6:30 pm
every night
6:30 pm
every night
Dining
Companions
Dining
Companions
Only Travel C… Only Travel C…
Prefered Pacing Prefered Pacing
As food is ready As food is ready

Ocean Apex Portal
Public Multi-Guest
Touch Interactive
Ocean Portal
Public Single-Guest
Touch Interactive
Ocean Stateroom Portal
Private Single-Guest
Touch Interactive
Ocean Light
Public Multi-Guest
Non-Touch Interactive
Compass Archetypes

Foster RelationshipsFoster Relationships

Lead with the Answer

Embrace the Familiar

Foster Relationships
Learning: Be the connective tissue.
The physical is the enabler for digital to become
permeable and ever present to ultimately connect
people, places and things.

Recommendation Logic

1:1 Prototype

Living Design
Designs are always living. It is
a system of parts that users
can construct and customize
in realtime.
With modularity, it is possible
to change pieces of a system
without redoing the whole.

Connecting people, places and cultures.

What’s next?

76
Future Scaleability…
Closed vs. Open
• What happens when you apply this methodology to public
infrastructure and democratize this for the rest of society?
Consumer Input vs. Machine Input
• Machines will be able to capture more inputs than ever before
• Listening as an input will be able to generate a vast amount of data
and designs
• Frameworks will need to become more advanced to deal with higher
degrees of unpredictability and chance

Thanks!

Liquid customization - Megan Meeker

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