Vision 2014: Understanding Marketing Efficiency Through Big Data Analytics

  • 100 views
Uploaded on

A Top 10 financial institution needed additional data intelligence to detect behavior patterns and understand trends that would enhance its learnings so it could deploy new strategies. In this case …

A Top 10 financial institution needed additional data intelligence to detect behavior patterns and understand trends that would enhance its learnings so it could deploy new strategies. In this case study, attendees will learn about this approach and gain insights into improving their marketing analytics.

  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
100
On Slideshare
0
From Embeds
0
Number of Embeds
0

Actions

Shares
Downloads
2
Comments
0
Likes
0

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. ©2014 Experian Information Solutions, Inc. All rights reserved. Experian and the marks used herein are service marks or registered trademarks of Experian Information Solutions, Inc. Other product and company names mentioned herein are the trademarks of their respective owners. No part of this copyrighted work may be reproduced, modified, or distributed in any form or manner without the prior written permission of Experian. Experian Public. Understanding marketing efficiency through Big Data analytics A case study Brian Ardinger Experian Armando Ramos Experian #vision2014
  • 2. 2©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Big Data for marketing efficiencies  Marketing opportunities  Big Data challenges  Technology responds to challenges  A case study Agenda Big Data opportunities and challenges for analytical sandboxes for understanding financial trends in the industry and consumer behavior for both customers and prospects
  • 3. 3©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Big Data challenges Data Linkage Platform Analytics
  • 4. 4©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Marketing opportunities Armando Ramos
  • 5. 5©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. What’s my market penetration?  Understanding marketable universe  Peer benchmarking analysis  Developing new strategies Marketing opportunities Knowing your market footprint
  • 6. 6©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. What are my customers doing?  New product with competitors  Posturing for a big purchase?  Balance transfer alerts  Payment behavior changes Marketing opportunities Trending your customer behavior
  • 7. 7©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Deploying a new strategies  Brainstorming an idea  Sizing and validating the idea  Developing the idea into a strategy  Champion / challenger testing  In the market test and learn  Deploying a new strategy Marketing opportunities Increase your speed to market
  • 8. 8©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Big Data challenges Armando Ramos
  • 9. 9©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Volume limitation? Big Data challenges Vast amount of data available Analytical data warehouse Customer information Marketing history Consumer lifestyle Consumer behavior Consumer digital info Consumer credit
  • 10. 10©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Can we afford it?  Storage (Gigabyte) ► 1990  $10,000 ► 2000  $10 ► 2010  $0.10  CPU (Moore’s Law) ► Number of transistors on integrated circuits doubles every two years since 1965 Big Data challenges Financial feasibility
  • 11. 11©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Integration under a single key  Legacy analytic repositories  360 degree view across the enterprise  Partner data (i.e., airlines)  Vendor data (i.e., credit bureaus) Big Data challenges Linkage technology
  • 12. 12©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Who builds these environments?  Client IT priorities  Hosted environment ► Bureaus ► Agent ► Third party processors Big Data challenges Platforms
  • 13. 13©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Dynamic marketing environment  New data elements  New portfolios  Merges and acquisitions  New markets and channels Big Data challenges Scalability and flexibility
  • 14. 14©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Regulatory requirements  CFPB  CCAR  Basel II  Model and data governance Big Data challenges Regulated environment
  • 15. 15©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Analytic performance  Fully integrated view of the data  Sub populations for unit testing  Large populations for performance testing  Historical populations for validations  Query response time  IT dependencies Big Data challenges Analytics
  • 16. 16©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Technology response to challenges Armando Ramos
  • 17. 17©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public.  Hosted single full integrated platform  Linkage HUB with dynamic integration (real-time requirements)  Middleware / workflow software ► Real-time requirements  Analytical tools (i.e., SAS)  Hadoop / Cloud environments  Strategy development tools (i.e., Attribute Toolbox™) Technology responds to challenges Technology is ahead of the game
  • 18. 18©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. EXP CIS/AUTO existing EXP Consulting existing Sandbox & Storage Data Includes (TIPT): • Trades • Inquires • Public Records • Trended Raw File • Consumer level data (like ZIP) • Includes Consumer and Trade level keys “links” (PIN, TIN & PTK) No identifying information!! Experian Analytic SandboxTM Annonymized 10% Sample Bureau Database 56TB EXP Sciences existing Sandbox & Storage Client Private Sandbox Multi - Client Demo Sandbox Private sandboxs can house client’s data with PIN’s (links) to the Experian sandbox and/or include non structured data (like social media) for analysis Hosted Environment Client access via the internet/Https. All data is loaded or extracted by/through Experian. For security reasons, no data can be remotely loaded or extracted by users to servers outside of the environment Client access via the internet/Https. The Demo Sandbox is a multiple client box. Client specific data cannot be stored on server High level schema of Experian’s Analytic SandboxTM
  • 19. 19©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Client case studies Brian Ardinger
  • 20. 20©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Regional bank Regional Client portfolio National prospecting  1.3 M population (100% Client footprint)  Summarized data only  Production attributes and scores (not to exceed 500 data elements)  Added value data elements (not to exceed 500 (i.e., Premier AttributesSM, Trend ViewSM, etc.)  Six time periods (quarterly for a 18-month performance window)  Bank performance data PIN’ed and integrated  Built internally at the bank  5 M population (representative portfolio sample)  Summarized data on private and raw data on 10% File OneSM  Production attributes and scores  Added value data elements (i.e., Premier AttributesSM, Trend ViewSM, etc.)  Twenty-four time periods of 10% File OneSM  Five time periods (quarterly for a 15-month performance window)  Hosted at Experian (Cloud)  10 user seats  220 M population (full marketing file)  Summarized data only  production attributes and scores  Added value data elements (i.e., Trend ViewSM, etc.)  Sixty time periods (monthly for a five-year performance window)  Hosted at Acxiom (Cloud)
  • 21. 21©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Help clients define and size the static population with the depth and breadth of data for the analytical data repository to meet their analytical needs Consulting Experian’s PINing is a core competency function for the credit file — files with name and addresses can be linked together with a consistent and persistent key Data integration Experian can provide value-added data assets for test and learn scenarios for calculated strategy assessment Experian data assets Multiple delivery options can simplify and accelerate implementation for rapid deployment Delivery options Opportunities
  • 22. 22©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public.  National universe  Trended data ► Credit data ► Campaign history ► New data elements  Integrate client / internal data assets  Tools for analytics  Rapid response to queries  In the market testing Top-5 credit card issuer
  • 23. 23©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Big Data challenges Data Linkage Platform Analytics
  • 24. 24©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. For additional information, please contact: Brian.Ardinger@experian.com Armando.Ramos@experian.com Hear the latest from Vision 2014 in the Daily Roundup: www.experian.com/vision/blog @ExperianVision | #vision2014 Follow us on Twitter
  • 25. 25©2014 Experian Information Solutions, Inc. All rights reserved. Experian Public. Visit the Experian Expert Bar to learn more about the topics and products covered in this presentation.