1. Predictive Customer Engagement
A Work in Progress

2. The Opportunity?
How can we provide information that we have … that customers would value… but don’t know to ask for?
© 2015 Consortium
for Service Innovation

3. The Goal of the Support Organization?
Definition of Service Excellence
Maximize customer realized value/success through the use of our products and services
Easy and seamless service integrated into the context of use
Continuous improvement of the whole customer experience
© 2015 Consortium
for Service Innovation

4. - Customer Value + Customer Value Expectations Exceeded “Added Value”
Customer Value
Expectations
Not Met
“Maintenance” -
Time
© 2015 Consortium
for Service Innovation

5. * * - Value Erosion + Customer Value Value Erosion Exception
Open
Incident
Exception
Self-service
and Forums
Automation *
Customer
Expectations
Customer Value *
Chat
Value Erosion -
Time
© 2015 Consortium
for Service Innovation

6. Customer Effort Model * High Case Customer Effort Self-service
and Forums *
Integrated
Resolution
Customer Effort
Low
Time
© 2015 Consortium
for Service Innovation

7. Customer Value/Effort Model and Knowledge Activation
High
High
Case
Community
Automate
Prevent
Eliminate
Chat
Customer Value
Customer
Expectations
Customer Effort
Knowledge Activation
Low
Low
Time
© 2015 Consortium
for Service Innovation

8. “Added Value” Reduce Customer Effort
High
Customer
Expectations
Customer Effort
Automation
Ease of use
Context sensitive help
Low
Time
© 2015 Consortium
for Service Innovation

9. “Added Value” Increase Capability
Sense and respond
to customer intent
Learning
On-demand
Functionality
High
Customer
Expectations
Customer Value
Low
Time
© 2015 Consortium
for Service Innovation

10. What if we could do both! Increase capability and reduce effort
Automation
Ease of use
Sense and respond
to customer intent
Learning
Context sensitive help
On-demand
Functionality
High
High
Customer Value
Customer Effort
Low
Low
Time
© 2015 Consortium
for Service Innovation

11. Service Excellence
Customer support is not about solving incidents or customer sat with incident resolution
It is about our ability to contribute to customer success and productivity
It means we have to be good at:
Minimizing value erosion
Maximizing value realization by reducing customer effort and increasing their capability
© 2015 Consortium
for Service Innovation

12. The Value Stack Value Customer’s Customer Success Customer Success
and Productivity
Predictive and
Preemptive
Fix
© 2015 Consortium
for Service Innovation

13. The Value Stack Value Customer’s Customer Success Customer Success
High
High
Customer’s Customer
Success
Customer Success
and Productivity
Business Acumen
Know-me Factor
Level of Trust
Predictive and
Preemptive
Co-creation Factor
Fix
Low
Low
© 2015 Consortium
for Service Innovation

14. Added Value
Enabling pre-defined customer capability and service levels is necessary.
Responding to un-anticipated needs and opportunities is compelling!
How do we:
Dynamically create the capability and capacity to respond to unanticipated customer needs?
Predict opportunities to co-create value with customers (without them asking)?
© 2015 Consortium
for Service Innovation

15. A Generic Customer Touch Point Model
Purchase or
Upgrade
Renew
GET
Cycle
USE
Cycle
Consideration
Support
Awareness
Usage
© 2015 Consortium
for Service Innovation

16. CX Framework Customer Touch Points “the journey” Awareness
Consideration
Purchase/Upg rade
Use
Support
Renew
Customer Touch Points
“the journey”
© 2015 Consortium
for Service Innovation

17. CX Framework Customer Modes of Interaction Awareness Consideration
Purchase/Upg rade
Use
Support
Renew
Customer Modes of Interaction
Apps
Print Media
Web/Social
Group Chat
People (WoM)
Analog Media
Agent Assisted
Search Engine
Digital Content
Social Network
User Community
Comm of Interest
© 2015 Consortium
for Service Innovation

18. CX Framework Customer Modes of Interaction Traditional Digital Mobile
Awareness
Consideration
Purchase/Upg rade
Use
Support
Renew
Customer Modes of Interaction
Apps
Print Media
Web/Social
Group Chat
People (WoM)
Analog Media
Agent Assisted
Search Engine
Digital Content
Social Network
User Community
Comm of Interest
© 2015 Consortium
for Service Innovation

19. Customer Scenario Traditional Digital Mobile Awareness Consideration
Purchase/Upg rade
Use
Support
Renew
Apps
Print Media
Web/Social
Group Chat
People (WoM)
Analog Media
Agent Assisted
Search Engine
Digital Content
Social Network
User Community
Comm of Interest
© 2015 Consortium
for Service Innovation

20. Customer Scenario Traditional Digital Mobile Awareness Consideration
Purchase/Upg rade
Use
Support
Renew
Apps
Print Media
Web/Social
Group Chat
People (WoM)
Analog Media
Agent Assisted
Search Engine
Digital Content
Social Network
User Community
Comm of Interest
© 2015 Consortium
for Service Innovation

21. Where Should You Focus Your CX Efforts?
Identify your map of space and time
Map the customer journey and modes of interaction
Look at frequently visited touch points and modes of interaction
Gather data on the high traffic touch points (surveys)
Where does CX not meet brand promise expectations
Don’t need to look at all touch points
© 2015 Consortium
for Service Innovation

22. Where to Focus Predictive Customer Engagement?
Uni-directional 1-to-many
Uni-directional 1-to-1
Bi-directional many to many
Bi-directional 1-to-1 or 1-to-few
© 2015 Consortium
for Service Innovation

23. Customer Scenario Traditional Digital Mobile Awareness Consideration
Purchase/Upg rade
Use
Support
Renew
Apps
Print Media
Web/Social
Group Chat
People (WoM)
Analog Media
Agent Assisted
Search Engine
Digital content
Social Network
User Community
Comm of Interest
© 2015 Consortium
for Service Innovation

24. Company/organization
The Event Loop (A Loop)
Events
Listening Posts
Communication
Mechanisms
Analysis
People
Product/
services
Knowledge articles
Company/organization
Work
Action
Rules
Discovery
© 2015 Consortium
for Service Innovation

25. Company/organization
The Black Box
Analysis
Context
Channel
Stage of journey
Asset characteristics
Inferred intent
Universal data
Relevance defined by context
Trends
Events over time
Universal trends
Results of success of action
Meta data
Usage/consumption
Algorithms and data science
Data analysis can be input or output
Analysis
People
Product/
services
Knowledge articles
Company/organization
Work
Rules
© 2015 Consortium
for Service Innovation

26. Company/organization
The Black Box
Rules
Define: what, who how, when
Profiles and Assets
People
Work
Company/organization
Knowledge Articles
Products/services
Analysis
People
Product/
services
Knowledge articles
Company/organization
Work
Rules
© 2015 Consortium
for Service Innovation

27. Knowledge Assets People Profiles Vendor Offerings Knowledge Articles
Work or
Tasks
Customer Entity
Original names
People, knowledge, customer entity, work/tasks, offerings
© 2015 Consortium
for Service Innovation

28. The Improve Loop (B Loop)
Impact Assessment
Engagement Assessment
Asset Quality
Rules Effectiveness
Analysis Effectiveness
People
Product/
services
Knowledge articles
Company/organization
Work
Analysis
Rules
Event
Action
© 2015 Consortium
for Service Innovation

29. The Role of the Data Scientist in Service Innovation
Objective: predict or anticipate value co-creation opportunities
Cross functional perspective
Sources of data
Data collection
Analysis techniques
Rules development
Assessment of relevance and accuracy of rules outcomes
© 2015 Consortium
for Service Innovation