the value of mining (big) data - data-driven marketing conference

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The Value of Mining (Big) Data… Without Scaring Your Customers Matthew Quint Director, Center on Global Brand Leadership Columbia Business School gsb.columbia.edu/globalbrands @mattquint Data Driven Marketing Conference August 20, 2013 [NOTE: Images for Prof. Netzer, Everyday Health, The Weather Company, and Target, have hyperlinks to video talks on the topic!]

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It was a pleasure to kick-off Marketing Magazine's Data-Driven Marketing Conference (August 2013). These are the slides from my presentation in which I talk about the the key challenges of "big data" and present both academic and brand-based case studies on how data, bigger data, and BIG data can: 1. Drive brand and consumer insights 2. Evaluate if marketing messages are working 3. Better target marketing communications efforts 4. Become a company asset to market 5. Allow for continued experimentation

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Page 1: The Value of Mining (Big) Data - Data-Driven Marketing Conference

The Value of Mining (Big) Data… Without Scaring Your Customers

Matthew Quint Director, Center on Global Brand Leadership Columbia Business School gsb.columbia.edu/globalbrands @mattquint Data Driven Marketing Conference – August 20, 2013 [NOTE: Images for Prof. Netzer, Everyday Health, The Weather Company, and Target, have hyperlinks to video talks on the topic!]

Page 2: The Value of Mining (Big) Data - Data-Driven Marketing Conference

…and not everything that counts can be counted - Prof. William Bruce Cameron

Not everything that can be counted counts…

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Data Bigger Data BIG Data

Small No integration Unit collected

Large Some integration Firm collected

Massive Heavy integration Firm and external

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All marketers want to be DATA-DRIVEN

Believe successful brands use data to drive marketing decisions

91%

But many are NOT COLLECTING the data they need

say their own company’s data are collected too infrequently

39%

Marketing ROI in the Era of Big Data: 2012 BRITE-NYAMA Marketing Measurement in Transition Study David Rogers and Prof. Don Sexton, Columbia Business School

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TOO LITTLE

TOO INFREQUENT

NOT SHARED

NOT SPECIFIC

DON’T PERSONALIZE

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“The evidence is clear:

Data-driven decisions tend to be better decisions.

In sector after sector, companies that embrace this fact will pull away from their rivals.” - Erik Brynjolfsson and Andrew McAfee, MIT (Harvard Business Review)

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Five key

CHALLENGES of (Big) Data

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Everywhere

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Unstructured

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Needs cleaning

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Storage and processing

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Privacy and security

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Case studies on

THE VALUE of (Big) Data

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1. Gain insights on brands or consumers 2. Understand what messaging works 3. Better target your communications 4. Your data becomes an asset to market 5. Continue experimenting

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Brand and consumer INSIGHTS from (Big) Data

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Edmunds.com sedan forum <Brand>Honda</Brand>

<Model>Honda Accord</Model>

<Model>Toyota Camry</Model>

<Brand>Toyota </Brand>

<Term>Best</Term>

<Term>Sedans</Term>

<Term>Competent</Term>

<Term>Price</Term>

<Term>Love</Term>

<Term>Best selling</Term>

<Term>Best</Term>

Honda Accords and Toyota Camrys are nice sedans, but hardly the best car on the road (for many people). It's just that they are very compentant in their price range. So, a love fest of the best selling may not tell you what is "best".

Text mining

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Network analysis

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MODEL SENTRA COROLLA CIVIC

Commonalities

Differentiators

Economy | Small-car | Subcompact | Compact

Power Performance

College

Mileage Plastic parts

Mom/Daughter

VTEC Engine Hatchback

Mud guards

Edmunds.com brand sentiment

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Consumer insights

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MESSAGING EFFECTIVENESS from (Big) Data

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American Luxury

Messaging effectiveness Prof. Oded Netzer

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Based on JD Power PIN Data

Brand-switching map

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Brands mentioned alongside Cadillac

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LUXURY imports

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Brands traded-in for Cadillac

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Demonstrate ROI

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TARGETING improvements from (Big) Data

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Better ad targeting

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Cross-Platform Campaign Ratings

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MARKET YOUR OWN (Big) Data

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Stores care about the weather

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Get acquired because of data

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Continue

EXPERIMENTING

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A/B Testing for Obama Campaign

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DON’T FREAK OUT your customers

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Charles Duhigg, “How Companies Learn Your Secrets,” The New York Times (Feb 16, 2012)

Target’s predictive analytics

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Tracking your whereabouts

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“I keep saying that the sexy job in the next 10 years will be statisticians. And I’m not kidding.”

- Hal Varian, chief economist at Google.

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The data scientist

1.Quantitative

2.Technical

3.Curious and creative

4.Skeptical

5.Communicative and collaborative

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Questions?

Matthew Quint Director, Center on Global Brand Leadership Columbia Business School [email protected] Data Driven Marketing Conference – August 20, 2013