design-led approach to big data
DESCRIPTION
Take the next big step in big data: designing a user experience that enables end users to easily understand and consume information and insights. Presented at the BigData Summit conference in Kansas City, November 2014.TRANSCRIPT
ARTI DESHPANDE | JENNI MITCHELL
Design Led Approach to Big Data
Agenda
• Expectation setting.
• A tangible example.
• High level design process.
• Value of research.
• What does this have to do with Big Data?!
• Now what?
• Answer all your burning questions!
Expectation setting.
We are not data scientists…
@KC_Arti
Experience Design ManagerDST Systems
Adjunct ProfessorJCCC
@useagility
Experience DirectorUseagility
We design experiences.
We hear “Big Data”, we picture this:
What’s the common theme?
• Information overload
• Information anxiety
• Flood of information
• Analysis paralysis
• Infobesity
• Infoxication
• Information glut
• Data smog
A tangible example.
Searching for an apartment in Chicago when
you have more requirements than just how
many bedrooms and baths, square footage,
or parking is very difficult.
eLocate
• Charge commission for:
- Apartment listings on the site
- Visits scheduled through the site
- Rentals that result from the site
- Promoting professional services like movers, cleaning services, etc
• Apartments will list with them if they get a lot of visitors.
• They’ll get a lot of visitors if they have flexible and helpful
search tools.
fictional company that targets renters unfamiliar with Chicago who are relocating
Typical apartment search
High-level design process.
Synthesize to
Understand
Prototypeto
Validate
Researchto
Discover
ResearchObservations
Interviews
Surveys
Existing data
Competitive analysis
DiscoverHow people think about activities
User goals
Business goals
Motivations
Scenarios
Gaps in the experience
Synthesize to
Understand
Prototypeto
Validate
Researchto
Discover
SynthesizePersonas
Mental models
Scenarios and storytelling
Mapping & Models
UnderstandThe people and the business
Behavior patterns
Communication patterns
The possibilities
The desired experience
Synthesize to
Understand
Prototypeto
Validate
Researchto
Discover
PrototypeSketching
Wireframing
Rapid Prototyping
ValidateOur collective understanding
Experiential evidence
Our frameworks and blueprints
Our prototypes before we implement
Synthesize to
Understand
Prototypeto
Validate
Researchto
Discover
Value of research.
Cliff’s Notes
User Needs
Business Goals
The sweet spot.
Conduct stakeholder & user research
• eLocate stakeholders
• Client stakeholders at apartment complexes
• Potential Advertisers
• Apartment seekers
Synthesize to
Understand
Prototypeto
Validate
Researchto
Discover
eLocate Business Objectives
• Provide a unique, fun, and accurate way to find an
apartment in Chicago leveraging all of the relevant data
available.
• Have the largest apartment selection for Chicago
available online.
• Collect high quality professional services to partner with.
• Make more money.
Synthesize to
Understand
Prototypeto
Validate
Researchto
Discover
eLocate Revenue Model
Revenue driven design
Apartment Complex Objectives
• Increase visibility of their apartments.
• Increase visits from prospective renters.
• Increase actual rental agreements to reduce vacancies.
Synthesize to
Understand
Prototypeto
Validate
Researchto
Discover
Professional Service Goals
• Increase visibility of services.
• Capture business from new comers to the area and keep
their ongoing business.
• Increased ratings and referrals.
• Create partnerships with apartment complexes to be the
preferred service provider.
Jonah Porter (27 years old)
Jonah is relocating because of a transfer to Chicago from Ann
Arbor, MI for his job. He’s been to Chicago several times, but just as
weekend trips and is not very familiar with the different areas.
About Jonah:
• Doesn’t want to bring his car
• Has a medium sized dog
• Doesn’t cook and orders a lot of takeout
• Loves an active music scene and young lively crowd
“Where you live says a lot about you…”
User Personas
Goals• Live somewhere that reflects his personality & tastes
• Make friends and have an active social life.
• Select a home that makes his life easier.
Tasks promote incremental
improvement.
Goals can lead to disruptive
products or services.
Task: Control temperature.
Goal: Save on heating/cooling costs
while maintaining optimal comfort.
What does this have to do with big data??
Now what?
Synthesize to
Understand
Prototypeto
Validate
Researchto
Discover
Remember
me??
Remember this?
Practical tip: Use the right scale
Practical tip: Focus on targeted info
April May June July Aug Sept Oct
2009 2014
Close to what you need:
• 5 minutes to grocery store
• 8 minutes to Shedd Aquarium
• 10 minutes to train
• 15 minutes to Millennium Park
• 20 minutes to Solider Field
OK Better
Practical tip: Make it consumable
At a minimum, don’t go overboard.
Before
After
Your turn. Questions?
Connect with us.
@useagility
www.linkedin.com/jenni-mitchell/
@KC_Arti
www.linkedin.com/artiacharya/