This document outlines a presentation on driving marketing programs with big data analytics. It discusses the evolution of analytics, provides a 4-step roadmap for implementing big data marketing, and reviews some key risks. The 4 steps are: 1) proof of concept, 2) datatification, 3) governance, and 4) consumerization. Each step provides critical people, process, and technology considerations. The presentation also reviews big data enablers and provides references for further information.
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Digital-Warriors-Marketing Roadmap with Big Data Analytics
1. 4 Key Steps to Drive your Marketing Program with Big Data Analytics
Jason Bowden – Chief Warrior & Consultant
www.digital-warriors.com
IT Consulting - Business Intelligence Analytics - Digital Marketing
@DigitalWarrior8
Copyright Digital-Warriors 2014
2. Jason Bowden
Chief Warrior & Consultant
www.digital-warriors.com
@DigitalWarrior8
Presenter
Experience:
• 17 years of experience with roles specializing
in Enterprise Intelligence & Analytics
• Fortune 500 experience: UPS, T- Mobile, and
Cox
• Successful execution of 200+ Analytics Project
Implementations
• CFY Technology Board Member (Non-Profit)
• Influential publisher for socialmediatoday.com
• Known as an very helpful GEEK!
Contact: jasonbowden1@gmail.com Or 404-966-7676
Free eBook: http://www.digital-warriors.com/big-
data-marketing-analytics/
Copyright Digital-Warriors 2014
3. What you will Learn in this Session…..
Big Data Marketing Phenomenon you care about….
How did we get here? The Evolution of Analytics
4 Key Steps for your Big Data Marketing Roadmap
Key Risks to think about….
Free eBook: http://www.digital-warriors.com/big-data-marketing-analytics/
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4. Big Data Marketing Phenomenon you care about….
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5. The NEW 4P’s of Marketing!
Performance
Near Real Time Decisions and
Treatment
High Fidelity Enrichment of ALL
the Data!
Personalization & Preference
Focus on Localization and
Environment factors
Focus on Relationships
Focus on Individual Behavior
Prediction
Why vs. What or Causality vs.
Correlation
Machine Learning &
Probabilities
Privacy
Great Power has Great
Responsibilities
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7. Foresight
Understanding the Evolution of AnalyticsBusinessValue
Complexity
High
High
Big Data
Enables these…
PredictiveExploratoryDescriptive
InsightHindsight
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Free eBook: http://www.digital-warriors.com/big-data-marketing-analytics/
8. Auto Discovery of Unknowns
• Things I don’t
understand
• I can ask questions
• Things I Know
• I can ask questions
• Things I don’t know
• I can Discover
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• Things I don’t know
• I can’t ask questions
• Very difficult to
discover
Big Data Value PropositionTraditional Analytics
9. How to get there? 4 Key Steps…..
Proof of Concept Datatification Governance Consumerization
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Free eBook: http://www.digital-warriors.com/big-data-marketing-analytics/
10. Big Data Analytics Marketing Roadmap
Proof of Concept Critical Steps
People:
• Recruit Open Minded Executive
• Find/Grow and Dedicate a
Techno-Functional Resource
Process:
• Invest in Use Cases!
• Listen for Unsolved Problems
• Develop ROI Case
Technology:
• Setup Low Cost Sandbox
• Cloud Based-Amazon Redshift
• Use Open Source
• Experiment with APIs
Use Case Definition Datatification Governance Consumerization
Copyright Digital-Warriors 2014
Free eBook: http://www.digital-warriors.com/big-data-marketing-analytics/
11. 4 Steps: Big Data Marketing Roadmap
Datatification Critical Steps
People:
• Position User/Customer Incentives
• Turn Intangible Behavior into Tangible data
Process:
• Focus on Unique Identifiers
• Top Down Metric Definition
• Understand Data Exhaust & Reuse
Technology:
• Map Collection Channels:
• Proprietary, Public, Purchase
• Create a Data Lake
Use Case Defition Datatification Governance Consumerization
Data Lake
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Free eBook: http://www.digital-warriors.com/big-data-marketing-analytics/
12. 4 Steps: Big Data Marketing Roadmap
Critical Steps:
People:
• Establish a Customer Health
Organization
Process:
• Integration into Current Process and
Systems
• Focus on Unique Identifiers and
matching logic
Technology:
• Meta-Data Management
• Business Process & Statistical
Modeling
Proof of Concept Datatification Governance Consumerization
Copyright Digital-Warriors 2014
Free eBook: http://www.digital-warriors.com/big-data-marketing-analytics/
13. 4 Steps: Big Data Marketing Roadmap
Critical Steps:
People:
• Enable Internal Adoption by many levels
of Employees
• High Touch or White Glove Customer
Service
Process:
• Prescriptive Actions
• Automation of Decisions
• Internal Training
Technology:
• Mobile Enablement
• Visualization & Infographics
• Self-Service Analytics & Exploration
• Security
Proof of Concept Datatification Governance Consumerization
Copyright Digital-Warriors 2014
Free eBook: http://www.digital-warriors.com/big-data-marketing-analytics/
14. Big Data Marketing Risks to Consider
Privacy Paradox
Human Freewill
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15. Big Data
Enablers
Cloud Infrastructure and
Cheap Storage
Distributed and In Memory
Processing
Complex Data Visualization
Business Process &
Statistical Modeling
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16. Presentation Services
Platform
DW Big Data Services Information Reference Model
Traditional ODS
Replication
Integration Platform
MicroBatchEnrichment
Master Data
Traditional EDW
Structured Transactions
In Memory Data
ComplexNightlyBatch
Data Marts
OLAP Services
SOA: Web Services
Security, Data Quality Interface, Meta Data
Day or GreaterIntra-DayNear Real-Time
Structured
Data
Master Entities &
Hierarchies
Alerting/Notification
Treatment Engines
Structured to
Unstructured
Interface
Internal Sources
Real-Time
CRM
Billing
Projects
SFDC
Financials
Others
Social
Media
SDFC
External Sources Internal Apps
Direct Connections
Enrichment
Services
Web
Portals
Visualization
Note Key Understanding
• Data Collection from Internal and External
Sources; Datatification, Data Exhaust, Data
Reuse
• Matching Algorithm to Identify and Enrich
Internal Business Entities: Customers, Vendors,
Assets, Brands etc.
• Data Science Environment: Statistical Modeling
and Rapid access with In memory database
architecture
• Enrichment to business processes, products and
service offerings. Powerful Presentation services
should provide embeddable content
• Outline items are new logical architecture
required to support Big Data Analytics and
Services
1
2
3
4
Mobile Machines
• HDFS (Storage)
• Pig (Scripting)
• Hive (Query)
• MapReduce (MPP)
Data Lake
Platform
Mobile
Apps
Machine Learning
1
2
3
1
Advanced
Analytics
API: Restful
4
4
Near Real-Time
Near Real-Time
Copyright Digital-Warriors 2014
17. Follow me on Twitter:
@DigitalWarrior8
Download my Free eBook:
www.digital-warriors.com/big-
data-marketing-analytics
Contact:
Skype: jbowden2005
Email: info@digital-warriors.com
Phone: 888-988-7567
Copyright Digital-Warriors 2014
18. I am Board Member for a Non-Profit Org
MISSION
CFY helps students, together with their parents and teachers, use digital learning
to improve educational outcomes. Our goal is to help improve student
engagement and academic achievement in Atlanta’s low-income communities,
where there is a tremendous need for educational programs and resources to help
close the achievement gap.
Our signature Digital Learning Program is a whole-school/community initiative
that provides school leadership support along with technology tools and training
to increase family involvement in learning, strengthen teachers’ ability to use
digital learning to personalize instruction, and help students become self-directed
learners.
To date, CFY-Atlanta has helped and inspired over 6,500 families across metro
Atlanta. With community support —your support— we can continue to provide
much needed training and resources to ensure that all children are able to
succeed in our digital world.
Please contact me if you have old computer your company can donate
CFA‘s Website-http://www.cfy.com/atlanta Copyright Digital-Warriors 2014
Big Data and Personalization:
Understanding individual customer preferences & behaviors
Understanding individual customer local environment
ROI understanding (data and case studies)
Big Data and Performance:
External Data enrichment
Social Listening
Sentiment Analysis
Social Signals
Competitor Analysis
ROI understanding (data and case studies
Big Data and Predictive Applications
Moving from Descriptive Analytics to Exploratory & Predictive Analytics
Machine Learning& Recommendation Engines:
Effective lead targeting
Discovering upsell opportunities
Proactive customer retention
Customer Lifetime value
ROI understanding (data and case studies)
Big Data and Personalization:
Understanding individual customer preferences & behaviors
Understanding individual customer local environment
ROI understanding (data and case studies)
Big Data and Performance:
External Data enrichment
Social Listening
Sentiment Analysis
Social Signals
Competitor Analysis
ROI understanding (data and case studies
Big Data and Predictive Applications
Moving from Descriptive Analytics to Exploratory & Predictive Analytics
Machine Learning& Recommendation Engines:
Effective lead targeting
Discovering upsell opportunities
Proactive customer retention
Customer Lifetime value
ROI understanding (data and case studies)
Proof of Concept Critical Steps
People:
Recruit Open Minded Executive
Sponsorship/Budget
Find and Dedicate a Techno-Functional Resource
Process:
Listen for Unsolved Problems
Questions to ask:
Product Recommendation
Personalized Care
Sentiment Analysis
Lead Conversion
Increase Customer Retention & Decrease Churn
Develop ROI Case
Why vs. What or Causality vs. Correlation
What is it good enough?
Technology:
Setup Low Cost Sandbox
Virtualization Cloud Based Storage Redshift
Start Collecting data ASAP!
Spin up it up in minutes
Use Open Source
Experiment with APIs-Get the data
Outline a Real Case Study: Travian Games
Overview:
Travian Games is one of Germany’s most successful
games companies, with more than 120 million registered
users. The company specializes in award-winning
browser games and MMOGs (Massive Multiplayer
Online Games), which gamers can access from any
computer or smartphone
Challenges:
Travian Games provides basic versions of
games for free and must entices players to convert to paid
versions by offering advanced features.
Key Use Case:
Understand Consumer behavior
Datatification Critical Steps
People:
Position User/Customer Incentives
Turn Intangible Behavior into Tangible data
Process:
Focus on Unique Identifiers
Top Down Metric Definition
Understand Data Exhaust & Reuse
Technology:
Map Collection Channels:
Proprietary, Public, Purchase
Create a Data Lake
People:
Establish a Customer Health Organization
Process:
Integration into Current Process and Systems
Focus on Unique Identifiers and matching logic
Technology:
Meta-Data Management
1. Use Case Investment:
Lead Conversion
Retention & Loyalty
Customer Lifetime Value
Product Recommendation
2. Sources:
Datafication
Consumerization
3. Data Collection:
Data Valuation
Data Exhaust
4. Existing process integration
Customer Health Organization
Key Identifiers & MDM
Privacy Paradox (Robert needs some graphic ideas here. Wrote some summary statements to give context)
Give your data to get great valuable services. Many will want services that are innovative and are provided based on data you have already given. Companies will generate massive innovation, jobs and prosperity in this space
At the same time….Give your data and never know exactly how it will be used again. Against you, or in ways you never dreamed that could be bad….
Human Free Will
Propensity Maps will be developed from your historical actions that will be able to predict with great accuracy your propensity to behave. Left unchecked this could erase the idea that we have the ability to shape our own future rather we are destined for certain outcomes that we can predict