applying human context to data

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Leah Spalding, VP - Western Region, Dynamic Logic, Millward Brown's Digital Practice Brian Doyle, Sr. Director Mobile Sales & Strategy Development, ESPN Dan Hill, President, Sensory Logic & Author, "Emotionomics" Session Leader: Jason Burnham, Partner & Social Engineer, Burnham Marketing Applying Human Context to Data

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Page 1: Applying Human Context to Data

Leah Spalding, VP - Western Region, Dynamic Logic, Millward Brown's Digital Practice

Brian Doyle, Sr. Director Mobile Sales & Strategy Development, ESPN

Dan Hill, President, Sensory Logic & Author, "Emotionomics"

Session Leader: Jason Burnham, Partner & Social Engineer, Burnham Marketing

Applying Human Context to Data

Page 2: Applying Human Context to Data

NEUROGRAPHICS [neu-ro-graph-ics] plural:

The statistical characteristics of human cognition and their relationship to common behavioral attributes that identify the predictable drivers of decision making cause and effect.

Page 3: Applying Human Context to Data

The Force of Certainty: Past Thinking

The Force of Probability: Present Thinking

The Force of Possibility: Future Thinking

Rational Risk Adverse Fears Change

Quality Driven Seeks Truth

Skeptical Prudent

Validates Analytical Selective

Practical Realistic

Controlled Process Driven

Seeks Order Utilitarian Methodical

Plans Compares Organized

Optimistic Impulsive

Aspirational Hope Driven

Individualistic Spontaneous Enthusiastic

Fickle Chaotic

Proactive

Page 4: Applying Human Context to Data

DEMOGRAPHICS

PSYCHOGRAPHICS

BEHAVIORAL

ATTITUDINAL

RESPONSE NEU

RO

GR

AP

HIC

S NEU

RO

GR

AP

HIC

S

GEOGRAPHICS

ADDRESSABLE AUDIENCE

Page 5: Applying Human Context to Data

Introduction

Communication

Understanding

Perception

Motivation

Behavior

Satisfaction

Result

Learning

Express

Share

Favor

“How It Should Look”

“How It Should Be Said”

“What They Will Need ”

“How It Will Resonate”

“What It Will Take”

“How They Will React”

“Will It Fulfill Them”

“What It Will Be”

“What It Will Require”

“How They Do It”

“To What Extent”

“In Relation To”

ADDRESSABLE

PROSPECT

CUSTOMER

ADVOCATE

Page 6: Applying Human Context to Data

OBJECTIVE: Position .NET as the TLD for small business

AUDIENCE: Small Business Owners & Entrepreneurs

KEY MEASURES: Awareness, Familiarity, Favorability, Intent

METHODOLOGY: Control/exposed comparisons, 1700 respondents

Page 7: Applying Human Context to Data

PROBABILITY PRESENT THINKING

POSSIBILITY FUTURE THINKING

CERTAINTY PAST THINKING

MindTime® is a registered trademark of MindTime Inc. © 2009 MindTime Inc. Patent Pending.

Page 8: Applying Human Context to Data
Page 9: Applying Human Context to Data

SportsCenter

Is…

35 years in the making

…and still innovating

9

Page 10: Applying Human Context to Data

SportsCenter Is… An ESPN Driver

113 Million Fans

Every Week

Source: ESPN All Day, Every Day Fall 2012 10

Page 11: Applying Human Context to Data

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62 Million Fans on Non-TV Media

55% of Fans Are Using Our Non-TV Platforms at Any Given Moment

Source: ESPN All Day, Every Day Fall 2012

Page 12: Applying Human Context to Data

12

6PM SportsCenter + 3% increase among A18-49 Jan.‘12 vs. Jan. ‘13

SC Instant Replay The first-of-its-kind

73% over-delivery on ESPN video ad starts

Source: Nielsen Media Research, Live US Rtgs; Arbitron Nationwide, Fall 2012

SportsCenter Is… the Leader on Every Screen

SportsCenter Live No. 2 watched program on WatchESPN

Directly behind Notre Dame vs. Alabama: 2013 Discover BCS National Championship game

SportsCenter Live No. 4 ranked ‘Sport’ on

WatchESPN via iPad

Behind football, basketball, tennis

SportsCenter Updates Every 30 Minutes .5 Million Weekly Reach, + 16% vs. 2010

Jan. ‘13

Jan. ‘13

Page 13: Applying Human Context to Data

Best Available Screen

Usage of TV, Internet and Mobile is place-based: Users select the best available screen

Page 14: Applying Human Context to Data

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ESPN.com ESPN Mobile ScoreCenter WatchESPN ESPN Nets

October 2012 College Football

ESPN Media Assests Net Users by Hour Saturday

Web

/Mo

bile

Per

son

s (0

00)

TV P

erson

s (000)

Source: Nielsen NPOWER Reach (ESPN, ESPN2, ESPNEWS) for TV; Adobe/Omniture for Web/Mobile; Saturday, October 6th, 2012

Page 15: Applying Human Context to Data

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ESPN.com ESPN Mobile ScoreCenter WatchESPN ESPN Nets

October 2012 NFL

ESPN Media Assests Net Users by Hour Sunday

Web

/Mo

bile

Per

son

s (0

00)

TV P

erson

s (000)

Source: Nielsen NPOWER Reach (ESPN, ESPN2, ESPNEWS) for TV; Adobe/Omniture for Web/Mobile; Sunday, October 7th, 2012

Page 16: Applying Human Context to Data

Source: Adobe Omniture, 9/10/12 – 9/16/12; Index = Index of per hour page views relative the typical hourly traffic for that platform

• MORNING: Standings, Player Statistics, Game Recaps

• MIDDAY: Preview Pages, Schedule, Features/Stories

• LATE AFTERNOON: Game Previews, Fantasy

• EVENING: Gamecast, Boxscores, Scoreboard Mobile

MLB Traffic Flow

Page 17: Applying Human Context to Data

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Not Who Won but How They Won

Social Conversation

Context and Perspective

Live Pressers and Headlines

The Biggest Stories of the Day

What’s Now Is What’s On

The Day in Sports

Closing out the Night’s Events

Your Weekend Ticket

18 hours of live coverage guides fans throughout the sports day

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Page 18: Applying Human Context to Data

1) What is currently the biggest problem with big data and how it is being utilized for marketing and advertising?

2) How should we define the "human" element and how do we incorporate this understanding of people into an increasingly data-driven industry?

3) What is the social media's role in understanding human behavior and where are agencies falling short?