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CHANNEL OPTIMIZATION THROUGH PERSONALIZATION
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Zimm Zimmermann Vice President, Personalization
Introductions
Identity Management
Audience Management
Consumer Privacy & Compliance
Media Optimization
Channel Optimization
Experience Design & Creation
Platforms Utilization
Measurement & Attribution
Marketing Technology
Platform Data
Platform Execution
Platform Enablers
Platform Marketer Competencies
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Media Optimization
Channel Optimization
Experience Design & Creation
Platform Data
Platform Execution
Platform Enablers
Channel Optimization
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Personalization Maturity Stages
Revenue Impact
• Basic "Batch" List Targeting
• No Optimization • Email or Print • Single Message for
everyone • “Dear Harry”
Personalization
• Simple Segmentation • A/B Testing • Email tied to Site
Landing Page • Email Champion
message delivered to everyone
• Tag Personalization
• Model Defined Segmentation
• Multivariate Optimization • Email tied to Site
Landing Page • Optimization within
Email and landing page • Tag Personalization
• Segment or persona driven
• Automated Modeled • Optimization • Channel and Media
Integration • Best Message / Best
Product Offer • Personalized with
customer / product attributes
• Customer Journey Based Segmentation
• Automated Predictive Optimization
• Channel and Media Integration
• Next Best point within the conversation / relationship
• Personalized content based upon conversation
Characteristics and Tactics
Channels
Stage 1
Static Campaign
Stage 2
Rules Based Campaign
Stage 3
Model Based Campaign
Stage 4
Integrated Customer Centric
Stage 5
Customer Centric Conversation
60% 120% 20% - 3% 10%
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Personalization thru Customer Centric Conversations
Revenue Impact
• Basic "Batch" List Targeting
• No Optimization • Email or Print • Single Message for
everyone • “Dear Harry”
Personalization
• Simple Segmentation • A/B Testing • Email tied to Site
Landing Page • Email Champion
message delivered to everyone
• Tag Personalization
• Model Defined Segmentation
• Multivariate Optimization • Email tied to Site
Landing Page • Optimization within
Email and landing page • Tag Personalization
• Segment or persona driven
• Automated Modeled • Optimization • Channel and Media
Integration • Best Message / Best
Product Offer • Personalized with
customer / product attributes
• Customer Journey Based Segmentation
• Automated Predictive Optimization
• Channel and Media Integration
• Next Best point within the conversation / relationship
• Personalized content based upon conversation
Characteristics and Tactics
Channels
Stage 1
Static Campaign
Stage 2
Rules Based Campaign
Stage 3
Model Based Campaign
Stage 4
Integrated Customer Centric
Stage 5
Customer Centric Conversation
60% 120% 20% - 3% 10%
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Merkle on Personalization Device
Offer
Treatment
Message
Time
Call-to-Action
Personalization manages the conversation of optimized content relevant to the customer journey. • Integrates Channel and Media • Explicit (customer provided) and implicit
(market derived) data • Converses with anonymous and known
consumers • Leverages all relevant data, models and
other Personalization Methodologies
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Conversations Begins at Anonymous The Addressability Spectrum
Channels & Media:
Anonymous Partially Identified Identified Identification:
Unknown Some Knowledge Well Known Knowledge:
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Personalization is Different than Traditional Marketing
Personalization – Dynamic conversations refined to the individual
Traditional – One marketing offer or message utilized for everyone
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Click-Through %
site.com
site.com site.com
site.com
Click-Through %
site.com
site.com site.com
site.com
Personalization is Multivariate on Steroids
Personalization – Format / Message aligns to customer preferences.
Multivariate – Focuses on a Winning format / message. Either / Or
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Personalization is Automated Self Learning Campaign Management is a Linear Process
Personalization is Self Optimizing Engine
Source Databases
Analytical Mart
Data Mining Tools
Scores & Lists
Operational Applications
Delay Feedback – Days/ Weeks/ Months
Input from External Models, Lists, Databases
Self- Learning Predictive Analysis
Operational Applications
Events
Decisions Immediate Feedback — Real-Time
Profiled Group
Individualized Offer
Linear Campaigns
Interactive Dynamic Offers
Analysis & Data Mining
Self Learning/Predictive
Delayed Response
Immediate Feedback
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Personalization Moves Static Sites to Dynamic Conversations
Zone 1
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Conversations Occur at Multiple Points
Zone 1
Personalized Content: Message / Offer
Call-to-Action
Treatment / Product
A B C
A
B
C
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Conversations occur across the entire Consumer Journey
Zone 1
Zone 2
Zone 3
Zone 4
Integrates across Channel & Media 1
Manages multiple placements within a Channel or Media 2
Multiple Conversations require more collateral 3
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Personalization within the Tech Stack
Custom analytics with automated machine learning at the core
Customer strategy expertise to drive customer experience design
Creative team purpose built for 1 to 1 consumer interactions
Expert in customer data integration and management
Optimization Cycle
Identity Management
Marketing Database
Channel and media execution
Workflow Content Management Marketing Automation
Offer Message Treatment Device Time
Predictive Decisions
FOUNDATIONAL DATA
Analytics Insights Platform Decision Management
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He finds some airfares, but he isn’t 100% certain.
Unknown visitor has come to Origin to research a trip.
Don’t book; instead, checks the weather forecast for the region,
where Origin continues the conversation
Over at Facebook, Origin offers me a 20%
discount if I “Like” them.
Coming back to the website, I purchase the ticket, which changes the conversation from sell to “Thank you.”
Forecast didn’t look great, so let me check a different destination.
Personalization Demo
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Within the initial deployment and pilot of the Customer Centric Conversation program, a major airline saw a 24:1 ROI.
An American multinational financial services corporation generated 180% incremental increase in online credit card acquisitions.
An industry leader in banking achieved a 400% ROI within the first year of an integrated Customer Centric Conversation program.
Success
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