design-led approach to big data

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

jenni@useagility.com

www.linkedin.com/jenni-mitchell/

@KC_Arti

AADeshpande@dstsystems.com

www.linkedin.com/artiacharya/