1. BIG DATA FOR MARKETING
Christopher S. Penn, Vice President, Marketing Technology

2. WHO ARE THESE PEOPLE?

3. WHO?
Prashant Kaw
@prashantkaw
Raj Vysetty
@rvysetty
Christopher Penn
@cspenn

4. WHAT IS BIG DATA?

5. DEFINITIONS
“Any data you do not have a story for. Also, data that does not fit on an Excel spreadsheet.”
- Tom Webster, VP Strategy, Edison Research

6. EVOLUTION
1960: Data Warehouse
1990: Process Mining
1989: Business Intelligence
1974: Decision Support Systems
2003: Business Analytics
1993: OLAP/OLTP
2005: Big Data

7. EXABYTE
One BILLION Gigabytes (or more)

8. PERSPECTIVE
1 Exabyte =
13,333 Netflix
Repositories of
75,000 movies

9. TWO CONSTANTS
How do we store all this stuff?
What does this stuff tell us?

10. 3 REASONS DATA-DRIVEN MARKETING FAILS
Sometimes, we ask for big
data but what we’re really
asking for is his sister,
better math.
Not many of us are dealing in exabytes right now.

11. 3 REASONS DATA-DRIVEN MARKETING FAILS

12. 3 REASONS DATA-DRIVEN MARKETING FAILS
Asking bad questions
of good data.
Most of the time, bad answers come from bad questions. The data is usually pretty good.

13. 3 REASONS DATA-DRIVEN MARKETING FAILS
1: “LET’S GO DIGGING!”

14. 3 REASONS DATA-DRIVEN MARKETING FAILS
2: WRONG FOCUS

15. 3 REASONS DATA-DRIVEN MARKETING FAILS
3: ASSUMING WHAT =

16. LET’S TALK ABOUT IT
How do we store all this stuff?
What does this stuff tell us?
Prashant Kaw
@prashantkaw
Raj Vysetty
@rvysetty
Christopher Penn
@cspenn

17. THANK YOU!
Q&A