ddma - when customers take charge - presentatie alan mitchell - 13 december 2012
TRANSCRIPT
DDMA
When Customers Take Charge December 13 2012
Alan Mitchell
Relevance ROI
Relationship
Gather data
Mix and crunch it
Generate model
Gain insight Creative execution and
targeting
Consumer response
The status quo
Relevance ROI
Relationship
Gather data
Mix and crunch it
Generate model
Gain insight Consumer response
lea
A learning loop
Creative execution and targeting
The status quo
Gather data
Blanket broadcast
Perfect targeting
Name and address
Demographic data
Lifestyle Pscyhographic
data
Social network data
Online behavioural
data
The goal: to know who to contact, about what,
when, how.
Transaction data
The dream of perfect targeting
The dream of perfect targeting … turning sour
WORLD ECONOMIC FORUM RETHINKING PERSONAL DATA “The existing dialogue about personal data is currently anchored in fear, uncertainty and doubt. A lack of trust has the potential to pull the ecosystem apart.”
Relevance ROI
Relationship
Mix and crunch it
Generate model
Gain insight Creative execution
Consumer response
Data quality
Privacy
Problems with the status quo
Relevance ROI
Relationship Gain insight Creative
execution Consumer response
Modeling error Predictive models don’t predict!
Data quality
Privacy
Problems with the status quo
Relevance ROI
Relationship Consumer response
Modeling error Predictive models don’t predict!
Creativity and insight focus on the company’s problem, not the customer’s
Data quality
Privacy
Problems with the status quo
Relevance ROI
Relationship
Data quality
Privacy
Modeling error Predictive models don’t predict!
Creativity and insight focus on the company’s problem, not the customer’s
Poor customer experience
Problems with the status quo
Relevance ROI
Relationship
Limited learning opportunities
Modeling error Predictive models don’t predict!
Creativity and insight focus on the company’s problem, not the customer’s
Poor customer experience
Data quality
Privacy
Problems with the status quo
The individual’s relationship management problem
Mortgage provider Bank account 1 Bank account 2 Credit card 1 Credit card 2 Credit card 3 Credit card 4 Pension provider 1 Pension provider 2 National Savings Life insurance Gas and electricity Water company Landline telephone Mobile telephone Home service insurance Car insurance Automobile Association Home and contents insurance Travel insurance Retail loyalty card Local cinema loyalty scheme
British Airways Executive Club National Film Institution Royal Shakespeare Company Charity 1 Charity 2 Doctor Dentist Fitness Club Taxi company Retailer 1 Retailer 2 Railway company 3 Railway company 4 London Transport Expedia Travelocity Subscriptions 1 – Harvard Business Review Subscriptions 2 – Business Week Subscriptions 3 – Fortune Subscriptions 4 – Marketing magazine Subscription TV Amazon
My suppliers How do I keep my details up to data with all of them?
How do I manage permissions?
How do I get best value?
All of them gathering data, profiling, modeling, targeting, messaging
The customer perspective
Where we came from
Organisations as managers of customer data • Companies collecting data about customers • Data as a tool in the hands of the organisation
CRM
Direct marketing
Where we came from
Where we are moving to
Individuals as managers of their own data • Individuals collecting data about their own lives • Data as a tool in the hands of the individual
VRM
‘Intent Casting’
CRM
Direct marketing
Where we are moving to
The customer in charge
Expression
The customer in charge
Expression
Filtering
The customer in charge
Relevance ROI
Relationship
Limited learning opportunities
Modeling error Predictive models don’t predict!
Creativity and insight focus on the company’s problem, not the customer’s
Poor customer experience
Data quality
Privacy
Richer, better data Privacy enhancing
The customer in charge: benefits for marketers
Relevance ROI
Relationship
Limited learning opportunities
Modeling error Predictive models don’t predict!
Creativity and insight focus on the company’s problem, not the customer’s
Poor customer experience
Data quality
Privacy
Richer, better data Privacy enhancing
More certainty Less waste
The customer in charge: benefits for marketers
Relevance ROI
Relationship
Limited learning opportunities
Modeling error Predictive models don’t predict!
Creativity and insight focus on the company’s problem, not the customer’s
Poor customer experience
Data quality
Privacy
Richer, better data Privacy enhancing
More certainty Less waste
Positively helpful to customers
The customer in charge: benefits for marketers
Relevance ROI
Relationship
Limited learning opportunities
Modeling error Predictive models don’t predict!
Creativity and insight focus on the company’s problem, not the customer’s
Poor customer experience
Data quality
Privacy
Richer, better data Privacy enhancing
More certainty Less waste
Positively helpful to customers
A genuine customer service
The customer in charge: benefits for marketers
Relevance ROI
Relationship
Limited learning opportunities
Modeling error Predictive models don’t predict!
Creativity and insight focus on the company’s problem, not the customer’s
Poor customer experience
Data quality
Privacy
Richer, better data Privacy enhancing
More certainty Less waste
Positively helpful to customers
A genuine customer service
Accelerated learning The customer in charge: benefits for marketers
The dumb letterbox
Lets everything in … And nothing out
A different model
The smart letterbox
Stops unwanted things coming in
A different model
The smart letterbox
Stops unwanted things coming in Signals what I want to come in
A different model
The smart letterbox
Stops unwanted things coming in Signals what I want to come in
Provides additional information
A different model
The smart letterbox
Stops unwanted things coming in Signals what I want to come in
Provides additional information While protecting my privacy
A different model
Pie in the sky?
Digital Asset Grid
Pie in the sky?
Digital Asset Grid
Pie in the sky?
Pie in the sky?
Pie in the sky?
Sudden interest in a growing market
Examples of new personal data management services
‘e-relationship management’
supplier dashboard
• inspect and correct
• automatic updates
• permissions dashboard
• digital letterbox
My relationships Bank account 1 Bank account 2 Credit card 1 Credit card 2 Credit card 3 Credit card 4 Pension provider 1 Pension provider 2 National Savings Life insurance Gas and electricity Water company Landline telephone Mobile telephone Home service insurance Car insurance Automobile Association Home and contents insurance Travel insurance Retail loyalty card Local cinema loyalty scheme
British Airways Executive Club National Film Institution Royal Shakespeare Company Charity 1 Charity 2 Doctor Dentist Fitness Club Taxi company Railway company 1 Railway company 2 Railway company 3 Railway company 4 London Transport Expedia Travelocity Subscriptions 1 – Harvard Business Review Subscriptions 2 – Business Week Subscriptions 3 – Fortune Subscriptions 4 – Marketing magazine Subscription TV Amazon
My suppliers
‘e-relationship management’
Attribute verification • identity assurance
• attribute checking
• profile building
Examples of new personal data management services
A dashboard controlling:
• what information is shared
• with who
• for what purposes
• when
• via what channels
• whether personally identified or not
‘e-relationship management’
Attribute verification
Contact/permissions management
Examples of new personal data management services
Privacy as a personal setting
UK CEO Ronan Dunne
"We want our customers to have the confidence to engage with their own information and data.
"Our trial gives customers a digital dashboard sharing with them all the information we have about them, why we have it, what services it is used for.“
Telefonica O2 Customer digital dashboard
• verified attributes
• transaction and other histories
• additional volunteered information
• reputation scores
• permissioned information sharing including purpose, terms, conditions
‘e-relationship management’
Attribute verification
Contact/permissions management
Profile building and sharing
Examples of new personal data management services Examples of new personal data management services
• goals, preferences, priorities
• circumstances, trade-offs, constraints
• ‘matching and connecting’ process
• advice seeking and giving
‘e-relationship management’
Attribute verification
Contact/permissions management
Profile building and sharing
Specification building
Examples of new personal data management services
• ‘what I’m in the market for right now’
Plus
• buyer profile, including verified attributes, reputation score
• contact and permissions settings
• specification
‘e-relationship management’
Attribute verification
Contact/permissions management
Profile building and sharing
Specification building
Intent casting
Examples of new personal data management services
Who I am What I do My views and feelings The questions I ask What I want
Admin/updates Identity data Verified attributes Lifestyle (income, profession, no of children etc) Transactions Behaviours Personae Values, views and feelings My questions (what’s possible? how to? what if?) Preferences Current interests Current priorities and purposes Future goals, plans and intention
Volunteered Personal Information
VPI: information individuals could tell organisations if they wanted to and if they saw good reason to
Improved data accuracy
Data more complete
Data more up-to-date
Improved ID assurance
Access to previously inaccessible information
Improved analytics, new insights
Reduced guesswork, error, waste
Improved relevance and higher response rates
Reduced data acquisition costs
Reduced fraud, risk
Improved innovation
Reduced cost to serve
Reduced go to market costs
Improved marketing ROI
Reduced regulatory burden
Lower product/service development costs
Higher levels of trust
Improved differentiation, competitive positioning
Improved customer acquisition and loyalty
Improved market share, revenues
Reduced opt-outs, higher permissions
Improved brand & corporate reputation
Data quality Data processes Commercial Corporate/brand
Benefits of new information sharing relationships
Personalised and customised services
Reduced data management costs
More personalised customer service
New growth opportunities
• Mindset • Legacy systems and skills • Priorities • Scale • Risk
Company reactions
Against
• Brand / reputation
• Mindset • Legacy systems and skills • Priorities • Scale • Risk
Against
For
Company reactions
• Brand / reputation • Strategic direction
• Mindset • Legacy systems and skills • Priorities • Scale • Risk
Against
For
Company reactions
• Brand / reputation • Strategic direction • Cost efficiency benefits
• Mindset • Legacy systems and skills • Priorities • Scale • Risk
Against
For
Company reactions
• Brand / reputation • Strategic direction • Cost efficiency benefits • A learning / innovating opportunity
• Mindset • Legacy systems and skills • Priorities • Scale • Risk
Against
For
Company reactions
Key trends in personal data
• Information as a tool in the hands
of the individual
• Individuals as managers of their
own data
• Individuals as points of integration
of data about themselves & their
lives
• Privacy as a personal setting (vs an
organisation’s policy)
Become the customer’s trusted information partner
Summary
