7 habits of highly effective personalization organizations
Post on 16-Apr-2017
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7 Habits of Highly Effective Personalization Organizations
Hudson ArnoldStrategy Consultant, Optimizely
@hudson_arnold
hudson@optimizely.com
HABIT 1Create a Vision
“The best vision is insight.” – MALCOM FORBES
Habit 1 Takeaway:
Create a Vision
HABIT 2Experimentation Maturity
ARE WE READY TO STEP FORWARD?FORRESTER’S PERSPECTIVE
*Source: Forrester’s Q3 2015 Global Online Testing Platform Customer Online Survey
Dimensions of continuous optimization
Online testing is applied mostly to the “explore” and “buy” phases of the customer life cycle
Online testing is applied mostly to websites
Online testing practices are mostly executing only A/B tests
A minority (i.e., 30% or fewer) of customer interactions are included in online testing*
Opportunity for improvement
ARE WE READY TO STEP FORWARD?FORRESTER’S PERSPECTIVE
*Source: Forrester’s Q3 2015 Global Online Testing Platform Customer Online Survey
Dimensions of continuous optimization
Online testing is applied mostly to the “explore” and “buy” phases of the customer life cycle
Online testing is applied mostly to websites
Online testing practices are mostly executing only A/B tests
A minority (i.e., 30% or fewer) of customer interactions are included in online testing*
Opportunity for improvement
MATURE OPTIMIZATION PROGRAMS • Do more complicated tests than A/B• Test through more than just a few pages• Are segmenting analytics
ARE WE READY TO STEP FORWARD?OPTIMIZELY’S MATURITY MODEL
INTERESTED INVESTED INTEGRATED INGRAINED
VA
LUE
Culture
Process
Strategy
Development
ARE WE READY TO STEP FORWARD?OPTIMIZELY’S MATURITY MODEL
INTERESTED INVESTED INTEGRATED INGRAINED
VA
LUE
Culture
Process
Strategy
Development
YESMAYBENO
INTERESTED INVESTED INTEGRATED INGRAINED
VA
LUE
Culture
Process
Strategy
Development
• Inconsistent access to resources
MATURE OPTIMIZATION PROGRAMS • Are comfortable pushing boundaries• Have processes and teams in place• Speak language of testing
ARE WE READY TO STEP FORWARD?OPTIMIZELY’S MATURITY MODEL
LEADING INDICATORS
Experimentation Success
VELOCITYThe volume of experiments being ran, the reach of personalization campaigns.
Throughput:# of experiments per property per month/week.
AGILITYThe degree that the experimentation program acts on results.
Iteration:The % of experiments put into production and iterated upon.
EFFICIENCYThe efficiency that experiments get through production cycle
Drag:Average hours spent redeveloping due to QA
QUALITYThe average likelihood that an experiment will produce business impact
Impact Rate:% generating meaningful result
OPERATIONAL METRICS FOR EXPERIMENTATION
LEADING INDICATORS
Experimentation Success
VELOCITYThe volume of experiments being ran, the reach of personalization campaigns.
Throughput:# of experiments per property per month/week.
AGILITYThe degree that the experimentation program acts on results.
Iteration:The % of experiments put into production and iterated upon.
EFFICIENCYThe efficiency that experiments get through production cycle
Drag:Average hours spent redeveloping due to QA
QUALITYThe average likelihood that an experiment will produce business impact
Impact Rate:% generating meaningful result
OPERATIONAL METRICS FOR EXPERIMENTATION
MATURE EXPERIMENTATION PROGRAMS • Are high throughput• Develop efficiently (business as usual!)• Get consistent wins
Habit 2 Takeaway:
Experimentation Maturity
HABIT 3Assemble Your
Dream Team
D I S C O V E R Y I M P L E M E N T A T I O N P L A N N I N G P R O D U C T I O N R E P O R T I N G
PERSONALIZATION PLAYBOOKEND-END PROCESS + MILESTONES
CORE PERSONALIZATION TEAMSKILLSETS & TEAM ROLE
Executive Sponsor Project Manager Technical Lead Developer Content
makea slack channel
makethe time
Habit 3 Takeaway:
Assemble Your Dream Team
HABIT 4Enrich YourPerspective
YOUR Team
Status Quo:Tech: current capabilities and limitationsPeople and ProcessAudience Strategy
Look InternallyYour SystemsYour AnalyticsYour PersonasYour CompetitorsYour Strategy Future States:
Potential capabilities Audience ProposalUse Cases
YOUR TEAM’S TASKGATHER INTELLIGENCE
1
YOUR Team
Validation and Alternate Perspectives:Tech: Potential capabilities People and Process: Alternate ApproachesAudience Strategy
Consult External ExpertsVendorsConsultantsAgenciesAnalyst Reports Future States:
Potential capabilities Audience ProposalUse Cases
2
YOUR TEAM’S TASKGATHER INTELLIGENCE
YOUR Team
Status Quo:Tech: current capabilities and limitationsPeople and ProcessAudience Strategy
Validation and Alternate Perspectives:Tech: Potential capabilities People and Process: Alternate ApproachesAudience StrategyConsult
External ExpertsVendorsConsultantsAgenciesAnalyst Reports
Look InternallyYour SystemsYour AnalyticsYour PersonasYour CompetitorsYour Strategy
Future States:Potential capabilities Audience ProposalUse Cases
YOUR Brief
3
YOUR TEAM’S TASKGATHER INTELLIGENCE
YOUR Team
Status Quo
Validation and Alternate Perspectives
Consult External Experts
Look Internally
Future States
YOUR Brief
3
YOUR TEAM’S TASKGATHER INTELLIGENCE
Habit 4 Takeaway:
Enrich Your Perspective
HABIT 5Create Your
Audience Strategy
Recency & Frequency
Cross-sells & Up-sells
Value Propositions
START BY REVISITING YOUR BUSINESS STRATEGY
Propensity Models
Customer Journey Model
Price Sensitivity
LAYER ON MORE AUDIENCES LEFT- & RIGHT-BRAIN
PERSONAS
Brain by the Noun Project
ANALYTICS
WHAT TECHNICAL SIGNALS CAN WE LEVERAGE?CONNECT CONCEPT TO TACTIC
Viewed 2 Products, Didn’t Buy
Keyword contains ‘discount’
Most frequently viewed category
DMP + Uploaded Lists
Abandoned Checkout
Data Warehouse (Customer ID
Geo-Targeting)
Came from Ad Campign = Gift
Technical Signal Consideration-Stage
Wants a discount
Preference for a specific product type
High-Propensity
Needs a push
VIP Member
Urban Location
Shopping for a Gift
Audience Characteristic
PRIORITIZE, PRIORITIZE, PRIORITIZEPURSUE VARIETY OF AUDIENCES, MAXIMIZE REACH/QUALITY
Obvious Need
Large
Need for Creativity
Granular
Visitor Cohort; New, Returning, Active, Loyal
Large Geos; Coastal Urban, State, Key Cities
Browsed Twice; Product Category
Past Purchasers
Second Priority
Habit 5 Takeaway:
Create Your Audience Strategy
HABIT 6Unify
Everyone has to work together for personalization to work for you
View of the Customer
CONNECT YOUR DATAHOUSEKEEPING BEFORE TECHNOLOGY
Habit 6 Takeaway:
Unify
HABIT 7Crawl Before
You Walk
PHASED INTEGRATION OF PERSONALIZATIONCRAWL, WALK, RUN
0-12 weeks
BuildPhase 1
months 12-24
BuildPhase 3BuildPhase 2
months 3-12
Platform Implementation
Simple Audiences
Starter Campaigns,Limited Integration ofTesting + Personalization
Phase 2 Planning
REACH: 0-15%
PAGES: 1-3; only most critical ROI points
# CAMPAIGNS: 2-5
AUDIENCES: Natively available, simple, large, simple conditions; Metro, Single Behaviors
TACTICS: Modules (lightboxes), image swaps, little testing
0-12 weeks
BuildPhase 1
PHASED INTEGRATION OF PERSONALIZATIONCRAWL, WALK, RUN
Integration with 1st & 3rd Party Data
More Campaigns
Integration of testing & Personalization workflows
More advanced use cases
Phase 3 Planning
BuildPhase 2
months 3-12
PHASED INTEGRATION OF PERSONALIZATIONCRAWL, WALK, RUN
REACH: 30-60%
PAGES: Multiple campaign/audiences on top ROI pages
# CAMPAIGNS: 10-20 ongoing campaigns
AUDIENCES: Target intersecting audiences, 3rd & 1st party data used, more and complex behaviors
TACTICS: Experiments drive campaign execution and iteration
Full system integration
Ongoing improvement
New audience strategy
Use cases continually iterated
Web personalization data feeds email and ad deployment
BuildPhase 3
months 12-24
PHASED INTEGRATION OF PERSONALIZATIONCRAWL, WALK, RUN
REACH: 75-100%
PAGES: Most pages, multiple elements per page
# CAMPAIGNS: 25+ ongoing personalization campaigns iterated on
AUDIENCES: Old audiences iterated, new granular audiences
TACTICS: Fully expressive strategy
Habit 7 Takeaway:
Crawl Before You Walk
Create a VisionExperimentation MaturityAssemble Your Dream TeamEnrich Your PerspectiveCreate Your Audience StrategyUnifyCrawl Before You Walk
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