How to Get Your Brand Elected: Big Data Presentation at NRF by David Selinger

How Relevance Can GetYour Brand Elected

DAVID SELINGER

[email protected]

www.richrelevance.com

RAYID GHANI

[email protected]

www.rayidghani.com

© 2014 RichRelevance, Inc. All Rights Reserved. Confidential.#richrelevance


Our Platform

1. The History of Data

2. How Data Make Money, Win Elections and Other Such Nonsense

3. Demystifying the Mystical Creature, Big Data

4. Next Steps: How to Take the Next Steps


The History of Data

SECTION 1


A Brief History of Data

1980 1990 2000 Today1900

STATISTICS

PROBABILITY “DATA MINING”

MACHINE LEARNING

“BIG DATA”

DATA WAREHOUSES

BI

FRAUD PREDICTION


The 3 Tools:Getting Value from Data

1

2

3

Analytics

Prediction & Interruption

Optimization

{Relevance}


Getting Value from Data

Getting Elected with Data

SECTION 2

OR


Getting Elected with Data


I am a data geek.

Intelligence

Obsession

Social Ineptitude

Nerd

Dweeb

Geek Dork


What am I good at?

How can I make a

difference?

Data Scientist for

Obama


Everyone’s NOT a Winner… It’s Binary

The Campaign


Legacy Orgs Are Nothing Like Start-ups

The Campaign


Don’t Disdain Successful Evergreen Channels

Key Campaign Lessons

EMAILDIRECT MAIL ADVERTISING

1

2

3

Analytics


Optimization


Perfect predictions do not necessarily alter hearts and minds.

Predicting vs. changing behaviorKey Campaign Lessons

1

2

3

Analytics


Optimization


Influencing the Right PeopleKey Campaign Lessons

1

2

3

Analytics


Optimization


A: The people who are just like you

Q: Who are the best people to persuade and influence?


1

2

3

Analytics


Optimization


DONATE

Turning supporters into advocates


1

2

3

Analytics


Optimization


The 3 Tools In an ElectionGetting Value from Data

1

2

3

Analytics


Optimization


David Selinger


Legacy Shopping Engagement

Source: Omni-channel Retail: The Future of Shopping (A study in partnership with Paco Underhill)

Awareness Consideration

PreferencePurchase

Clarity

Signage

Flow

RetentionRetention

Conversion


Source: Omni-channel Retail: The Future of Shopping (A study in partnership with Paco Underhill)

Omni-Channel Engagement

Purchase

Consideration

Preference

Awareness

Retention

© 2014 RichRelevance, Inc. All Rights Reserved. Confidential.#richrelevancePersonalization and Data Mining

research

1

2

3

Analytics


Optimization



Big Data: The 3 V’s

Velocity Volume Variety


Surprise!

HOW WE GOT ELECTED WITH DATA:

Lots of good ol’ data integration with sprinkles of Hadoop dust and other” big data” technologies when appropriate.


Big Data vs. Smart Data


Let’s Get Going

SECTION 4


Where are we?


BIGDATA

IQ

DATA IQ

Catalogers/DR Marketers

NicheeCommerce

Upstarts

AdvancedeCommerce

Vendors

TraditionaleCommerce

Vendors

eCommercePureplays

Omnichannel Retailers

Where are we?


How do we apply these to our businesses?

• Getting Started: Learn Quickly

• Getting Integrated: Bite-sized Chunks

• Measure yourself: The right metrics

• Experiment, Experiment, Experiment.

• Scale: Rinse and Repeat or “Big Project”


SUCCESSFUL• Multi-channel marketing

attribution• Social network

demographics for content targeting

• Multi-channel customer profile creation for analytics, targeting, personalization

• Datamart creation

UNSUCCESSFUL• Data warehouse

replacement• “Big Data Experiment”• Online

analytics/segmentation • Board of Directors “Check

the Box” Project: “Yes, ma’am we’ve got Big Data”

Some Initial Big Data Retail Projects


Closing Thoughts


ACCESS THE HANDOUT:

richrelevance.com/nrfCONTINUE THE CONVERSATION:

DAVID SELINGER

[email protected]

www.richrelevance.com

RAYID GHANI

[email protected]

www.rayidghani.com

Thank you!

To track the progress of Big Data for

retailers, subscribe to our regular newsletter “Big Data for Retailers”

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How to Get Your Brand Elected: Big Data Presentation at NRF by David Selinger