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Leveraging Big Data to Drive Marketing Innovation
Andrew Leone, BS Engineering, MBA, MS Finance
Summary of “The Big Data-Driven Business”
2
Information Processing Engine
Big Data is incredibly fast analysis enabled by increased processing speeds & cheap storage
Moore’s Law: Gordon
Moore, co-founder of
Intel
The number of
transistors on a
computer chip will
double every two years
IBM’s “Big Data at
the Speed of
Business”
We create 2.5
quintillion byes of data
every day. 90% of the
world’s data has been
created in the last two
years
“In three decades between 1980 and 2009, the cost per gigabyte of storage plummeted from
$193k per gigabyte to 7 cents per gigabyte”
3
Three Primary Categories of Individuals
Despite obvious power, the understanding and use of Big Data has remained sporadic
The Frozen
Either don’t know how to get started or don’t want to uncover the
truths that data might deliver
The Pioneers
Embracing troves of data that they have access to and who are
truly transforming the way businesses are run and how customer
communication is done
The Denialists
Don’t believe big data has any value to deliver and whose
businesses are dead or dying
“The winners create cultures that embrace big data, employing data scientists to analyze data and draw conclusions
that may contradict the company’s assumptions, and to take action that takes advantage of the truth the detail reveals.”
4
Successful & Highly Polarizing Case Study
How Dan Stroker used Big Data to help elevate Barack Obama’s campaign to the White House
• Who is Dan Stroker: ex-Google employee
 Joined campaign after Obama mentioned bringing digital & data expertise to government
• Obama was in 3rd place behind John Edwards and Hilary Clinton before joining
• Stroker introduced Big Data approach to campaign including web optimization, A/B testing
 Digital campaigns used A/B testing on combinations of 3 videos, 3 photos, 4 calls to action
 Analyzed results on >300k web visitors, 24 permutations,
 Discovered winning combination (“learn more” w/ family photo)  40% higher performance
• Generated incremental $60 million in campaign contributions to vault into 1st place
• Fundamental to winning Party nomination
5
Business area of highest impact: Marketing
“A company has only two functions: marketing and innovation” – Peter Drucker
“Marketing is purchasing
significant marketing related
technology and services from
their own capital and expense
budget – both outside control
of the internal IT organization
and in conjunction with
them… By 2017, the
CMO will spend more on IT
than the CIO
- Laura McLellan, Gartner
Research VP
Marketing stack: 360◦ customer view
Central marketing data repository
Product discovery, decision, experiences
Right message, time & channel
Optimizing tactics and resources
6
Shift in control from Salesperson to Buyer
Potential customers completed 90% of buyer journey before talking to Salesperson (Forrester Research)
“A sales professional's ability to observe and understand the buyer’s body language was an irreplaceable
component of his success. That’s no longer possible in the new paradigm. Instead marketers must rise to
the challenge: marketers must cultivate new skills to observe and understand the buyer’s digital body
language” – Steve Wood, Digital Body Language
Traditional Sales Digital Marketing
Information
Learning
Relationship
Purchase control
Asymmetrical (sales advantage) Symmetrical (buyer parity)
Salesperson Search engine, web, reviews, blogs
Salesperson relationship Customer review, communities
Salesperson Buyer
vs
7
Importance of CMO & CIO Relationship
“Where the CMO and the CIO work well together, the enterprise is 76% more likely to outperform…” - IBM
Set well defined goals, together
McKinsey tips for solidifying relationship (Getting the CMO & CIO to work as partners, 2014):
1
2
3
4
5
CMO is metric driven, transparent
CIO must shift mindset
Team building is essential
Think big but start small
• Alignment on targets
• Shared accountability to reach goals
• Right metrics for gauging outcomes, tech & data
• Both marketing & IT ability to track progress
• Revenue generation vs. cost center
• Hire people with understanding of both sides
• “Marketing & IT translators”
• Agile vs. waterfall
• Pilot and fail fast; constant improvement
8
Elements of the Marketing Technology Stack
Marketing
Automation
Segment
audience and
use to nurture
flows and
deliver relevant
content
CRM System
Sales & account
management
teams as
customer
system of
record. Track
activities vs.
pipeline
Content
Management
Fast and easy
posting &
changing of
content to web.
Includes text,
images &
videos
Blogging
Platform
Easy to push
out content via
email,
newsletters,
SEO aids, RSS
feeds. Data on
readership,
traffic & time
Data
Management
Use 1st & 3rd
party cookies as
well as APIs to
create audience
segments for
targeting
Analytic
Tools
Data-driven
window into
web traffic
Social Media
Management
Includes social
listening, post
scheduling,
social selling,
customer care,
curation and
promotion
Predictive
Analytics
Statistical
analysis
performed on
leads to
determine best
leads and
predictors of
success
E-Commerce
Platform
Understand
who is buying,
what they are
buying, and
how much they
are spending
Search Engine
Mgmt Platform
Manage,
automate, and
optimize search
engine
marketing &
pay-per-click
Demand-side
Platform
Enables
marketers and
agencies to use
real time
bidding
Call Center
Software
Answer
questions and
solve problems
as quickly and
easily as
possible
9
Overview of top software Giants
Major players are acquiring and developing software and systems, enabling more sophistication
• ‘09: Omniture, web analytics
• ‘11: Demedex, data mgmt.
• ’11: Auditude, video ad
• ‘11: Efficient Frontier, Programmic
search mktg
• ‘14: Neolane, marketing auto
• ’06: aQuantive
• Microsoft Dynamics ERP/CRM
• ’06: Youtube, online video
• ‘07: Double Click: ad server
• ‘09: AdMob: mobile ad network
• ‘09: Teracent: ad platform
• ‘11: AdMeld, supply side
• ‘12: Motorola Mobility
• ‘14: Spider.iO, Nest
• ’12: Vitrue, social mgmt.
• ’12: Involver, social development
• ‘12: Eloqua: mktg automation
• ‘13: Compendium, blogging
• ‘13: Responsys: mktg automation
• ‘14: BlueKai, data mgmt
• ‘07: Cognos, BI platform
• ‘09: SPSS, analytics
• ‘10: Coremetrics, web analytics
• ‘10: Unica, customer preference
• ‘10: Sterling commerce
• ‘10: Jigsaw, crowdsourced
business database
• ‘11: Radian6: social media
• ‘12: Buddy Media: social media
• ‘13: Exact Target, mktg
automation
10
11 Principles: Bringing Big Data into Business
Basic advice applicable to businesses of all sizes
1. Focus on the customer to determine what questions you want your data to answer
 Ex: What do best customers have in common? Where can you find more? What behaviors indicate leaving?
2. Its Big Data, but start small
 Look for small wins: 1) won’t tax budget, 2) build processes in controlled fashion, 3) earn decision maker buy-in
3. Don’t bet everything on technology
 Human element is critical. Start w/ buyer’s journey, customer needs and company culture
4. Hire the right people
 Embracing big data means hiring more mathematicians, data scientists and marketing technologists
5. Maintain some control of the technology piece
 Have technical and analytic arms that report up thru the Marketing org.
6. Measure, measure and measure some more
 A/B testing, dashboard tracking, Campaign measurement including engagement & effectiveness
7. Stay on top of your data and the processes around that data
 Strategy and software are linked. Do not cede control
8. Conduct an audit and strive to integrate data silos
 Take stock of all sources of data; centralize sources into 360-degree view of customers
9. Cooperate w/ IT, Sales, Human Resources and other key stakeholders
 Biggest barriers often relate to business management and process change
10. Practice good data hygiene
 Data-entry priority, update customer info frequently, streamline cleansing, contact cust. to update but allow access
11. Develop a road map, but anticipate detours
 Get data in place for measurement; do things out of the box to create unique advantage
11
Data Measurement and Testing
Test initiatives, measure responses and focus efforts on those that maximize revenue & income
Measurement
• More sophisticated & holistic
view
• Precise measurement
• Enabled real-time
Testing
• Focus groups limited; handful of
opinions w/ opinions not actual
behaviors
• Use A/B testing w/ immediate
feedback
12
Data and Attribution
System that accurately attributes contributions made by each and every one of tactics
Last-click attribution
100% credit to last element the prospect interacted
with prior to a sale
Rules-based attribution
Marketer assigns a certain value to particular tactics
based on predetermined rules
Algorithmic attribution
Assigns values to each interaction based on
statistical regression or probalistic models
13
Central Trends to Big Data’s Future
Personalization
Integrating data silos and platforms
Predictive analytics / machine learning
Internet of things
Mobile
14
Recommended Reading
Glass, R. and Callahan, S. (2015). “The Big Data-Driven
Business,” Hoboken, New Jersey: John Wiley and Sons, Inc.
15
Continue the Conversation
www.Governingthought.com

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Leveraging big data to drive marketing innovation

  • 1. Leveraging Big Data to Drive Marketing Innovation Andrew Leone, BS Engineering, MBA, MS Finance Summary of “The Big Data-Driven Business”
  • 2. 2 Information Processing Engine Big Data is incredibly fast analysis enabled by increased processing speeds & cheap storage Moore’s Law: Gordon Moore, co-founder of Intel The number of transistors on a computer chip will double every two years IBM’s “Big Data at the Speed of Business” We create 2.5 quintillion byes of data every day. 90% of the world’s data has been created in the last two years “In three decades between 1980 and 2009, the cost per gigabyte of storage plummeted from $193k per gigabyte to 7 cents per gigabyte”
  • 3. 3 Three Primary Categories of Individuals Despite obvious power, the understanding and use of Big Data has remained sporadic The Frozen Either don’t know how to get started or don’t want to uncover the truths that data might deliver The Pioneers Embracing troves of data that they have access to and who are truly transforming the way businesses are run and how customer communication is done The Denialists Don’t believe big data has any value to deliver and whose businesses are dead or dying “The winners create cultures that embrace big data, employing data scientists to analyze data and draw conclusions that may contradict the company’s assumptions, and to take action that takes advantage of the truth the detail reveals.”
  • 4. 4 Successful & Highly Polarizing Case Study How Dan Stroker used Big Data to help elevate Barack Obama’s campaign to the White House • Who is Dan Stroker: ex-Google employee  Joined campaign after Obama mentioned bringing digital & data expertise to government • Obama was in 3rd place behind John Edwards and Hilary Clinton before joining • Stroker introduced Big Data approach to campaign including web optimization, A/B testing  Digital campaigns used A/B testing on combinations of 3 videos, 3 photos, 4 calls to action  Analyzed results on >300k web visitors, 24 permutations,  Discovered winning combination (“learn more” w/ family photo)  40% higher performance • Generated incremental $60 million in campaign contributions to vault into 1st place • Fundamental to winning Party nomination
  • 5. 5 Business area of highest impact: Marketing “A company has only two functions: marketing and innovation” – Peter Drucker “Marketing is purchasing significant marketing related technology and services from their own capital and expense budget – both outside control of the internal IT organization and in conjunction with them… By 2017, the CMO will spend more on IT than the CIO - Laura McLellan, Gartner Research VP Marketing stack: 360◦ customer view Central marketing data repository Product discovery, decision, experiences Right message, time & channel Optimizing tactics and resources
  • 6. 6 Shift in control from Salesperson to Buyer Potential customers completed 90% of buyer journey before talking to Salesperson (Forrester Research) “A sales professional's ability to observe and understand the buyer’s body language was an irreplaceable component of his success. That’s no longer possible in the new paradigm. Instead marketers must rise to the challenge: marketers must cultivate new skills to observe and understand the buyer’s digital body language” – Steve Wood, Digital Body Language Traditional Sales Digital Marketing Information Learning Relationship Purchase control Asymmetrical (sales advantage) Symmetrical (buyer parity) Salesperson Search engine, web, reviews, blogs Salesperson relationship Customer review, communities Salesperson Buyer vs
  • 7. 7 Importance of CMO & CIO Relationship “Where the CMO and the CIO work well together, the enterprise is 76% more likely to outperform…” - IBM Set well defined goals, together McKinsey tips for solidifying relationship (Getting the CMO & CIO to work as partners, 2014): 1 2 3 4 5 CMO is metric driven, transparent CIO must shift mindset Team building is essential Think big but start small • Alignment on targets • Shared accountability to reach goals • Right metrics for gauging outcomes, tech & data • Both marketing & IT ability to track progress • Revenue generation vs. cost center • Hire people with understanding of both sides • “Marketing & IT translators” • Agile vs. waterfall • Pilot and fail fast; constant improvement
  • 8. 8 Elements of the Marketing Technology Stack Marketing Automation Segment audience and use to nurture flows and deliver relevant content CRM System Sales & account management teams as customer system of record. Track activities vs. pipeline Content Management Fast and easy posting & changing of content to web. Includes text, images & videos Blogging Platform Easy to push out content via email, newsletters, SEO aids, RSS feeds. Data on readership, traffic & time Data Management Use 1st & 3rd party cookies as well as APIs to create audience segments for targeting Analytic Tools Data-driven window into web traffic Social Media Management Includes social listening, post scheduling, social selling, customer care, curation and promotion Predictive Analytics Statistical analysis performed on leads to determine best leads and predictors of success E-Commerce Platform Understand who is buying, what they are buying, and how much they are spending Search Engine Mgmt Platform Manage, automate, and optimize search engine marketing & pay-per-click Demand-side Platform Enables marketers and agencies to use real time bidding Call Center Software Answer questions and solve problems as quickly and easily as possible
  • 9. 9 Overview of top software Giants Major players are acquiring and developing software and systems, enabling more sophistication • ‘09: Omniture, web analytics • ‘11: Demedex, data mgmt. • ’11: Auditude, video ad • ‘11: Efficient Frontier, Programmic search mktg • ‘14: Neolane, marketing auto • ’06: aQuantive • Microsoft Dynamics ERP/CRM • ’06: Youtube, online video • ‘07: Double Click: ad server • ‘09: AdMob: mobile ad network • ‘09: Teracent: ad platform • ‘11: AdMeld, supply side • ‘12: Motorola Mobility • ‘14: Spider.iO, Nest • ’12: Vitrue, social mgmt. • ’12: Involver, social development • ‘12: Eloqua: mktg automation • ‘13: Compendium, blogging • ‘13: Responsys: mktg automation • ‘14: BlueKai, data mgmt • ‘07: Cognos, BI platform • ‘09: SPSS, analytics • ‘10: Coremetrics, web analytics • ‘10: Unica, customer preference • ‘10: Sterling commerce • ‘10: Jigsaw, crowdsourced business database • ‘11: Radian6: social media • ‘12: Buddy Media: social media • ‘13: Exact Target, mktg automation
  • 10. 10 11 Principles: Bringing Big Data into Business Basic advice applicable to businesses of all sizes 1. Focus on the customer to determine what questions you want your data to answer  Ex: What do best customers have in common? Where can you find more? What behaviors indicate leaving? 2. Its Big Data, but start small  Look for small wins: 1) won’t tax budget, 2) build processes in controlled fashion, 3) earn decision maker buy-in 3. Don’t bet everything on technology  Human element is critical. Start w/ buyer’s journey, customer needs and company culture 4. Hire the right people  Embracing big data means hiring more mathematicians, data scientists and marketing technologists 5. Maintain some control of the technology piece  Have technical and analytic arms that report up thru the Marketing org. 6. Measure, measure and measure some more  A/B testing, dashboard tracking, Campaign measurement including engagement & effectiveness 7. Stay on top of your data and the processes around that data  Strategy and software are linked. Do not cede control 8. Conduct an audit and strive to integrate data silos  Take stock of all sources of data; centralize sources into 360-degree view of customers 9. Cooperate w/ IT, Sales, Human Resources and other key stakeholders  Biggest barriers often relate to business management and process change 10. Practice good data hygiene  Data-entry priority, update customer info frequently, streamline cleansing, contact cust. to update but allow access 11. Develop a road map, but anticipate detours  Get data in place for measurement; do things out of the box to create unique advantage
  • 11. 11 Data Measurement and Testing Test initiatives, measure responses and focus efforts on those that maximize revenue & income Measurement • More sophisticated & holistic view • Precise measurement • Enabled real-time Testing • Focus groups limited; handful of opinions w/ opinions not actual behaviors • Use A/B testing w/ immediate feedback
  • 12. 12 Data and Attribution System that accurately attributes contributions made by each and every one of tactics Last-click attribution 100% credit to last element the prospect interacted with prior to a sale Rules-based attribution Marketer assigns a certain value to particular tactics based on predetermined rules Algorithmic attribution Assigns values to each interaction based on statistical regression or probalistic models
  • 13. 13 Central Trends to Big Data’s Future Personalization Integrating data silos and platforms Predictive analytics / machine learning Internet of things Mobile
  • 14. 14 Recommended Reading Glass, R. and Callahan, S. (2015). “The Big Data-Driven Business,” Hoboken, New Jersey: John Wiley and Sons, Inc.