webinar presentation- accelerating growth through big data and analytics
TRANSCRIPT
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Accelerating growth through Big Data
and Analytics
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December 6, 2012
Presented by:
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Key points we want to make today
I. Overview on Luminar and Impetus
II. Shift from the status quo
III. How Big data is helping advance how we market to Latinos
IV. The journey, implementation approach
V. A new business model supporting clients
VI. Lessons Learned
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Luminar is an analytics and modeling company focused onhelping clients become more efficient in targeting the US
Hispanic market
Company was established Spring 2012
Luminar is a business unit of Entravision Communications(NASDAQ: EVC)
Based in Denver with operations in LA, DC, Buenos Aires,
Argentina; and Mexico City
Key client segments include: Retail, CPG, Financial Services,Media & Entertainment, and Publishing
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Big DataWhat it is
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BigData is NOT just analytics. It's NOT just about storage. It's
NOT just about anything - it's about everything. It's abouttossing out the old way of doing things because those ways
simply won't work in the world of BIG.
- Steve Duplessie, founder and senior analyst at ESG
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The value of Big Data varies by company
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Save Time
Lower Complexity
Self Service
Improve OperationalEfficiencies
Grow Sales &Profitability
Empower NewBusiness Models
Actionable Customer
Insights
Reduce Churn
Predictive Analytics
Improve Customer
Experience
Competitive
Differentiation
Data As a Service
Data Science Services
Incubate New
Ventures
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Understanding the magnitude of the US
Hispanic Population some basic facts
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Understanding why Luminar decided to
make a Big Data play
Four key factors influenced this decision:
1. We wanted to shift from the current marketing
paradigm targeting Latinos focused on sample data
2. We recognized that Hispanic consumers are underrepresented with most marketing approaches
3. Our service offerings are synergistic to our parent
company
4. Our model would necessitate ingesting vast amountsof diverse data that required a robust analytics
environment
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Underserved market what we
saw in the marketplace
Brands are making marketing investmentdecisions on limited information
Targeting assumptions based mostly on survey or
sample methods (i.e. Latinos over-index on
mobile usage)
No real insights or true performance of program
Campaigns mostly based on just ethnically-
coded data
Stereotype approach; they speak Spanish,
consume Spanish media, heavy onlineusersthereforegood target
Little or no cultural relevancy
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Actionable insights is an evolving process
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Testing market
No in-language
experience
Mass media, singlechannel
No dedicated
Hispanic team
Lack of
understanding how
to use analytics
Retains Hispanic
agency
Use focus group
Multi-channel, oftennot integrated
Top Hispanic DMAs
Bilingual experience
Qualitative data use
Increased ability
to capture,
aggregate and
analyze data Use analytics to
guide actions
Growing use of
insights to guide
future strategy
Use analytics to
prescribe actions
Effective at sharing
information andinsights
Strong ability to
capture, aggregate,
analyze or share
information
Strong use of
insights to guideday-to-day
operations
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Big Data brings a high-value offering
Ability to more precisely support customers across the entiremarketing value chain:
- Move from a media & communications discussion to a
business challenge discussion
- Help identify growth opportunity within the Hispanic market- Improve measurement of Hispanic market investments
- Demonstrate ROI
- Help accelerate growth through empirical data insights
Transformative in the way we approached business and marketingneeds
Leverage big data environment and 3rd party data sources across
business units
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Winning executive buy-in was critical
Its was a significant investment and commitment that required CEO visionand support
Developed detailed roadmap for success:
- Prepared comprehensive plan detailing operations, resources, level of
investment and implementation path
- We weighted the need for big data as new revenue source for EVC
- We identified packaged solutions for a big data offering
- And, we clearly defined how big data fulfilled an underserved market
and provided a shift from sample-based research to empiricalanalytics
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Result Luminar was created as a new
Entravision business unit
New business unit was created dedicated to serving
Hispanic-focused analytics and insights
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Luminar Big Data would need to support
these needs
Analytics-as-a-Service platform Aggregate multiple sources of data from diverse sources
- Licensed data
- EVC data
- Unstructured social data
- Client data
Offer an advanced and unique focused analytics service
- Provide insights into Hispanic consumer behavior
- Targeting customers in retail, financial services, insurance and auto
segments
Future offerings
- Platform as a Service
- White Label Services
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Importance of aligning our vision with the
right technology partner
Proven track record vendor had to have a demonstrableexperience in the implementation of big data solutions
Technology agnostic We needed a technology partner thatcould help plan and deploy a solution architecture that was
not married to any one vendor
Experience with multiple technology providers/suppliers
We needed a partner that could understand the big data
landscape now, in 6 moths and 18 months from today
Blended team approach Our ideal partner had to clearly
understand that they would be operating in a blendedclient/vendor team environment
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Deployment Objectives
Build a best-of-breed model based on Luminar requirements
- Take a vendor neutral approach
- Lowest Total Cost of Ownership
- No requirement to integrate with any legacy systems but SQL
data migration Cloud based architecture
Maximize re-use of vendor experience in Big Data
Scalability for future data requirements
Data security requirements Visualization
Start with a shoestring approach
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Build the right foundation for growth
Impetus lead solution architecture and vendor selection process
We established a solution framework that delivers four client offerings
We architected a solution that defined all major technology Key
Performance Indicators (KPIs) and SPOF
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AdvisorsExperience. Architects Expertise. Applications Excellence.
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Use Case Discovery and Implementations
Verticals
Use-Case
Patterns
ValueDrivers and
Functional areas
Big Data
Analytics
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Solution Creation Approach - Steps
1: Initial
Phase
Understand Data, ETL and Analytical/Reporting &roadmap requirements
Prepare comprehensive/ long list of candidates
Finalize assessment criteria and weightage factors
2: Finalize
POC
Candidates
Compare and recommend short list ofcandidates after detailed evaluationincluding vendor meetings
3: POC
Implement, execute andbenchmark critical use cases
Execute POC candidates inparallel if possible
4: FinalPhase
Assessment report Recommend bestsolution fit
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Vendor selection based on weighted scoring
We created a custom-scoring matrix used for evaluating
vendors pros and cons, defining requirements, andweighting against Luminars objectives
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Licensed
Data
Internal
Data
Client
Data
Unstructured
Data
OtherData Sources
Data Sources
Luminar Data Store Cluster(HDFS on EBS + P+G + 53 + RDS + Hdbase)
Horton Works
ETL / ELT Security Module
& Compliance Software
Data
Talend
Stream
Processing
(LADAP)
Tableau
BI Tools/ Data
Services
Revolution
/Hive
Statistical
Modeling
Web-based
Workstation
Tablet
Mobile
Notebook
BI Display OutputsAmazon AWS
Technology Hybrid architecture
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Implemented solution overview
Hadoop Cluster provisioned on
Amazon EC2 in under four hours
Original data sets imported from
MySQL to HDFS/Hive usingSqoop and Talend
Existing R scripts were modified
to work with Hive for data
analysis. Minimal code
modification required
Tableau work books modified to
connect to Hive via Hortonworks
ODBC driver
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Our value proposition formula
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How we do It
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Customer Visualization Application
Big Data Analytics
Data Management & StagingData Sources
Client Data Files
Unstructured Data
Luminar Data
Insight Solutions
3rd Party Data
Customer
Decision Engine
Luminar
Insight App
Real-Time
Cloud Insights
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Luminar Business Insights
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Closing remarksFourkey takeaways
Make a strategic connection to Big Data In Luminarscase, it provided a clear strategic path to a new
marketing approach
Big Data initiative requires holistic approach bringing
business and IT together to stitch all the parts
While IT and business need to work together, the
business must own the initiatives
Have a flexible approach to your roll-out strategy
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Accelerating Growth through Big
Data and Analytics
Q & A
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December 6, 2012
Presented by: