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Big data & human knowledge:sxsw
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Transcript of Big data & human knowledge:sxsw
Think love match not shotgun wedding
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SXSW 2013: Big Data & Human Experience
Submitted for SXSW 2013
Dr. Lauren TuckerDirector of Consumer Forensics
The Martin Agency
Chris DickeyDirector of AnalyticsThe Martin Agency
Core Business Challenge:Making smart decisions in an uncertain world
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Information explosion
Economic implosion
Market globalization
Great Opportunities
Great Risks
Big Data, especially post recession, can have gaps that limit it’s predictive power.
Big Data
Pattern recognitionStrength
Limited by data
Weakness
Human Experience can be an important additive to Big Data, which can smooth out the biases of human instinct.
Statistical Analysis Human Experience
Pattern recognitionStrength Logical reasoning
Limited by instinctual biases
Limited by data
Weakness
Range of Predictive Outcomes
Real world expertiseHistorical Data
Hard Data
Alone:Past isn’t always
predictive
Human Experience Better Choices from Scenario Simulation
Alone:Experience isn’t always precise
Together:Precise, predictive decision support
+ =
Advances in technology and mathematics allow for a numerical value to be assigned to human experience so it can be integrated with data
to deliver smarter decisions
This approach overcomes common modeling issues, allows for transparency, collaboration and immediacy.
Data vs. Knowledge
Lots of Data(Tight fit, Lots of data)
Lots of Knowledge(Lots of experience, strong basis)
Li@le Knowledge (Li@le experience, weak
basis)
Li@le Data(Erroneous fit, li@le data)
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Models that integrate data and knowledge are constantly optimized to achieve a balance of both.
75th percenGle25th percenGle
75%25%
Illustra(ve
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• Experience• MarkeGng research• Database a@ribuGon• Sales over Gme• MarkeGng acGvity over Gme• CorrelaGons between data sales and markeGng acGvity
AnalysisSimulation
Optimization
Historical data:Sales demand
Sales force activity
Marketing activity
Financials
Management information:Past marketing allocation decisions
Investment guidanceOptimal investment according to forecast targets, fixed budget constraints and profit maximization
Optimized tactical allocation across sales and marketing channels
Scenario resultsSales and marketing budget
Revenue forecasts short & long term
Risk assessments
This approach produces a learning model that is continually updated with new inputs.
Scenario Planning:The development of optimal media
plans with projected outcomes
Account for Impact of Past Decisions:Assigns values to subjective experience, events and changes in market.
Adaptive Testing:Employs an iterative process and constantly optimizes by updating priors to improve models.
Basic Analysis:ROI for all communications channels and
for each individual channel
Table Stakes …And Beyond
Strategic Investment Planning:Long and short term ROI
Budget Planning:Optimizes investments to
business targets
The advantage for marketers over traditional modeling approaches used for decision support.
Dr. Lauren TuckerDirector of Consumer Forensics
The Martin [email protected]
Chris DickeyDirector of AnalyticsThe Martin Agency
For more information: