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Personalizing the Consumer Experience

with Data    

MARINA RAKHLIN  

Follow the action on Twitter using #AtE2014  

Data-Driven Personalization

Tools • POS data • Persona

Brief History of Personalization

Tools • POS data • Persona

Brief History of Personalization

Challenges • Web

Tools • Cookies • Recommenders

Brief History of Personalization

Tools • Cookies • Recommenders

Brief History of Personalization

Challenges • Consistency • Relevancy

But  there  is  a  problem  

Tools • Tracking •  Internet of

Things • Social Graphs

Brief History of Personalization

Tools • Tracking •  Internet of

Things • Social Graphs

Brief History of Personalization

Challenges • Disjointed data • Noise

“ The signal is the truth. The noise is what distracts us from the truth.”

~ Nate Silver

Segmentation

But  there  is  a  problem  

3 assumptions behind segmentation:

But  there  is  a  problem  

3 assumptions behind segmentation: A segment can be •  Identified

But  there  is  a  problem  

3 assumptions behind segmentation: A segment can be •  Identified • Described

But  there  is  a  problem  3 assumptions behind segmentation: A segment can be •  Identified • Described • Reached selectively and

efficiently

Identify: get your data in order

But  there  is  a  problem  

Data: • Contextual • Behavioral • Historical

 Segments  

Demographics  

Preferences  Behavior  

 Segments  

Demographics  

Preferences  Behavior  

Describe

Segment Definition: •  “A priori” (pre-determined)

•  Has purchased from category X

•  “Post-hoc” (market-defined) •  Conversion based on demographics, psychographics

A priori – getting started •  New vs returning visitors •  Brand loyal vs brand switchers •  Demographics •  Geographics •  Census data (income groups)

A priori – getting started •  New vs returning visitors •  Brand loyal vs brand switchers •  Demographics •  Geographics •  Census data (income groups)

Post-hoc analysis •  Cluster analysis •  Aggregation models •  Disaggregation •  Optimization

3 segmentation best practices:

• Pay attention to segment stability •  time, situations, seasonality

• Groups that do not differ in behavior are not segments, just groups

• Segmentation should be an on-going effort

Reach selectively and efficiently

Customers in your DMP

Customers in your DMP

25% come to your site

Customers in your DMP

25% come to your site

10% are part of a segment

Steps to data-driven personalization: •  Unify data sources to identify segments •  Describe and analyze segments •  Create relevant targeted messaging

Thank you mrakhlin@monetate.com