brad terrell: marketing in real time: technology & data imperative
Post on 19-Oct-2014
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Brad Terrell, VP & General Manager, Digital Media at Netezza: Marketing in Real Time: The Technology & Data Imperative: Keys to creating marketing value opportunities with real-time data.TRANSCRIPT
Brad TerrellBrad Terrell
Marketing in Real Time:The Technology
& Data Imperative
“Innovation distinguishes between
a leader and a follower”
– Steve Jobs
SEPTEMBER 20, 2010, 9:34 AM ET
3
SEPTEMBER 20, 2010, 9:34 AM ET
IBM Buys Netezza for $1.7 Billion
Data-centric strategies create valueData-centric strategies create value
Data
Uniquenessis a source of
Uniqueness
CompetitiveAdvantage
is a source of
We made it!We made it!
Marketing and Data Analysis are Intertwined
Digital Exhaustbenefits marketers
“75% of CMOs rearranging their teams in 2011
to keep pace with the demands of digital media”to keep pace with the demands of digital media”
– Chris Stutzman, Forrester Research
“The sexy job in the
next 10 years will
be statisticians” –
Hal Varian, Chief
Economist, Google
10
A+ players
are hard to find
Extracting insights from exploding data volumes
requires new technologies and methodologies
Extracting insights from exploding data volumes
requires new technologies and methodologies
What initiated this trend?What initiated this trend?
Sampling can be a good thing…
but not in
digital marketing!
Throwing out impressions
breaks attribution analysis
Massively.
Parallel.Parallel.
Computing.
“The company with
the most data wins”
– Tim O’Reilly
It’s not just about big…
Reducing data latency
creates significant marketing value
Real-time marketing is like being in the
stands instead of watching it on TV later
Increasing consumer power
means the stakes are higher
Relevance:
does not fit all
because one size
The Data Aggregation Problem
Market X: Price/Volume Curve
0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
IMP
RE
SS
ION
S P
ER
DA
Y
Price/Volume Forecast Curves Show the Optimal Bid in Each Market:
( ) ( )( )BNBRmax ⋅−
The Bidding Problem
0
0.00 1.00 2.00 3.00 4.00 5.00
CPM Bid
0
500
1,000
1,500
2,000
2,500
3,000
3,500
0.00 1.00 2.00 3.00 4.00 5.00
CPM Bid
PR
OF
IT
Market X: Profit Curve
R = revenue derived from showing ad
B = ad’s bid N(B) = impression volume for bid B as
predicted by P/V Curve
Customer Insight Through Deeper Analysis(The Fastest Climbers Win)
BI Reporting and
Ad-Hoc Analysis
Predictive
Analytics
Optimization
• What happened?
• When and where?
• How much?
• What will happen?
• What will the impact be?
• What is the
best choice?