It’s time to embrace the future of customer engagement. You need a customer-centric approach in order to build your business around the needs, preferences and intents of your customers on an ongoing basis. But do you know how to create the optimal customer insight platform to get you there? Our guest Brandon Purcell, Senior Analyst at Forrester Research, and Steven Noels, CTO and Co-Founder of NGDATA, defines what the customer insight platform is, and how it can be used to engage in a relevant way with your customers, transform your business, optimize costs and achieve new growth. Key takeaways include: How to stay ahead of evolving customer demands, and how data and analytics play an essential part Understanding all the components necessary to transform customer data into insights to meet and exceed your customers’ expectations How to operationalize customer insights to optimize every customer interaction

1. Delivering Smarter Customer Interactions
Defining the Customer Insight Platform to Get You There
Featuring
Brandon Purcell
Senior Analyst
Forrester Research
Steven Noels
CTO & Co-Founder
NGDATA
WEBINAR

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Imagine a world in which….
1. Customer data captured from all interactions:
2. Data is collected and
managed in a central
repository
3. Customer analytics
unlocks valuable insights
4. Insights are operationalized
across channels

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“We are drowning in data and
starving for insight.”
— Global Bank

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Customer insights are the gold buried
within your data

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P = potential
value of data
E = value extracted
from data
P E/P = ~1
Customer
analytics
Customer analytics unlocks the potential value in your data

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What is Customer Analytics?
Customer analytics uses customer data
and analytic insight to design
customer-focused programs that win,
serve and retain customers.

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The potential value for analytics is real across the customer
lifecycle
Source: June 19, 2014, “How Analytics Drives Customer Life-Cycle Management” Forrester report

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Customer analytics is different. Really.
METHODS DATA TECHNOLOGY
Descriptive
Predictive
• Predictive
modeling
• Forecasting
• Simulation
Prescriptive
• Reporting &
measurement
• Business intelligence
• Optimization
• Decision
arbitration
Internally-sourced, at-
rest, Structured
Externally-sourced,
unstructured
Multi-sourced, in-motion,
multi-structured
Relational
Non-relational
• CRM, EDW, POS,
Web
• Social, location, VoC
• Sensor, open data,
IOT data, device
data
• Hadoop, noSQL
• Traditional EDWs
DataScience&
CustomerAnalytics
Traditional
Analytics

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Source: February 2014 “TechRadar™: Customer Analytics Methods, Q1 2014”
Deciding where to begin may be the hardest part

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Source: “Close The Insights To Action Gap With A Clear Implementation Plan”
The analytical process begins and ends with business
requirements

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› What is the key business objective of the project?
› Who is the project owner? Who are the relevant stakeholders?
› What will the cost and benefits of the project be?
› Are there risks / constraints we need to take into account?
› What would an ideal solution look like in action?
› How will we measure the success of this project?
› What is my project plan?
Key business questions before beginning analysis

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Source: “Analyzing Analytics: How To Measure The Impact Of Customer Analytics”
Select an objective with a measureable financial impact

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Now let’s turn to the data

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Image Source: http://en.wikipedia.org/wiki/File:Google_Glass_detail.jpg
Customer data ain’t what it used to be

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Data type Definition Examples
Numerical
Continuous All numerical values,
including fractions
Purchase amount
Discrete Only integer values Website visits
Categorical
Nominal Qualitative data without
order
Region
Ordinal Ordered qualitative data Level of education
Binary Qualitative data with 2
values
Offer click
Time and date Time and date data Timestamp
String Text data Email content
Actually…in analytical terms, there are only a few types
of data

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Developing a single source of customer truth is onerous…
but essential
Source https://vision.cloudera.com/using-big-data-to-drive-a-true-customer-360/

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Business
objective
Data
Customer
analytics
Choosing the right analytical method depends on your
business objectives and your data

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Now let’s explore the menu

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The customer analytics “menu”

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Source: February 2014 “TechRadar™: Customer Analytics Methods, Q2 2016”
Customer experience
analytics methods:
• Customer satisfaction
analysis
• Customer engagement
analysis
• Customer journey
analysis
Methods which improve the customer experience

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Source: February 2014 “TechRadar™: Customer Analytics Methods, Q1 2014”
Personalization
analytics methods:
• Next best action
• Recommendation
analysis
• Cross-sell and
upsell analysis
Methods which drive personalization

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Source: February 2014 “TechRadar™: Customer Analytics Methods, Q1 2014”
Acquisition analytics
methods:
• Behavioral customer
segmentation
• Customer lifetime
value analysis
• Customer lookalike
targeting
Methods which drive acquisition

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Aren’t we forgetting something?
Business
objective
Data
Customer
analytics

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Business
objective
Data
Customer
analytics
ACTION
Aren’t we forgetting something?

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New methods deliver new output and require new
operational processes

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All possible data Untested insights
Potential learnings
All possible actions
However, we still see gaps between data and action
Source: April 27, 2015, “Digital Insight Is The New Currency Of Business” Forrester report

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Systems of insight operationalize customer analytics
All Data
Possible
ActionsInsights-to-execution
process
Insights team
Digital insights
architecture
Right
data
Effective
actions

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THIS is a system of insight
1. Customer data captured from all interactions:
2. Data is collected and
managed in a central
repository
3. Customer analytics
unlocks valuable insights
4. Insights are operationalized
across channels

29. Analytics in Action
Customer Insight Platform
Featuring

30. Insight-Driven Processes
ACTION
INSIGHT
Customer DNA
DATA
Big Data
Sources
Enterprise
Data Sources
Dashboards
BI or
Analytics
Tools
mobile online physical IoT social Call center Credit card 3rd party mail email
One Solution Driving Your Customer Experience
Lily Enterprise: The Customer Experience Operating System (CX-OS)
ONE Solution to:
• Capture data across all
channels
• Gain real-time insights
from analytics
• Drive opti-channel
actions

31. SOLUTION
OPPORTUNITY
RESULTS
• Offer the customer the next best product to improve customer’s Telenet experience.
• Guide the call center advisor to sell the most relevant products.
• Alerts advisors in case special attention is needed.
• Setting up and maintaining the complex business logic rules within the application.
• Created Customer DNA - a sophisticated and nuanced understanding of customers from millions
of data points around both inbound and outbound interactions.
• Addressable campaigns - using viewers’ data to determine the right ad to show at the right time.
• Personalized offers or services – targeting dormant customers to reduce potential churn.
• One Care Portal - providing viewers with personalized information in their personal portal.
Telenet (part of Liberty Global group), Belgium’s largest provider of cable TV and
broadband cable services to close to 5 million service subscribers, needed to reduce
churn propensity and lower broad marketing costs, while improve customer loyalty.
Targeted Outbound Marketing Programs
With the international expertise of NGDATA, our CRM department now exists at the center of all our
inbound and outbound customer interactions, sharing real, actionable business intelligence and insights,
executing hundreds of targeted campaigns on a yearly basis.
- Bert Van Driessch, Director of CRM and Consumer Intelligence, Telenet
REDUCED ATTRITION BY
MORE THAN
20%
INCREASED SEGMENTED CAMPAIGNS
FROM 100 CAMPAIGNS PER YEAR TO NOW
MORE THAN 750 PER YEAR,
WITH PERSONALIZED CONTENT
MOBILE CUSTOMER BASE INCREASED
MORE THAN 4X
WITHIN A FEW MONTHS OF ITS AVAILABILITY
INCREASED RETURN RATE ON
SALES CAMPAIGNS BY
300-400%
Belgium’s largest provider of cable TV and broadband cable services

32. SOLUTION
OPPORTUNITY
RESULTS
• Belfius’ key objective was to propose the right offers - actions with the right messages via the right
channels, at the right moment, in a personalized way - for all products and all channels available
within the bank. They wanted to achieve this by fully leveraging their existing analytics capabilities
and adding real-time analytics to support their digital channels.
• NGDATA brought all of Belfius’ data together to get an individual-level view of each customer in
one solution.
• The first specific use case focused on a next best action program around their pension savings
product offerings. First, they wanted to know which customers had the greatest propensity for
specific products, and to devise specific messages to them based on their behaviors and
backgrounds. Second, they wanted to nurture their targets’ interest in the Simulate Loan
Calculator. Third, they wanted to get those targets into the sales flow, and to see them through
the path-to-purchase.
• An array of content channels were used to entice the targets to take action, including a banner
campaign that was personalized to the users.
Belfius is a bank and insurance group that is owned by the Belgian federal government.
Belfius is not listed on the stock exchange and is made up of a bank, an insurance
company and various other subsidiaries.
• Belfius is now able to use that single
customer profile, with real-time scoring
and analytics across all channels, and for
all banking products
• Belfius is now able to implement
additional use cases, based on a jointly
defined roadmap that includes next best
action, cross- and upsell, loyalty and
churn prevention programs
Next Best Action Programs
Banking & Insurance

33. SOLUTION
OPPORTUNITY
RESULTS
• Essent wanted to deliver better service to their customers while lowering their call center costs –
specifically around inbound calls regarding invoicing - which can be lengthy and costly.
• Customer DNA was created on each customer from data stored in different systems (CRM –
contract, billing, usage, etc., and contact interactions from inbound and outbound activities – call
center, mail, website, etc.) to better understand their behaviors and propensities when it came to
invoicing.
• Once they had the Customer DNA in place, they created a model to enable them to predict which
customers were most likely to call about invoices.
• The ones mostly likely to inquire received a personalized video, with information about their
current status of usage, which would reflect on their next invoice. Results of views were also fed
back into the system for further insights.
Essent supplies electricity and gas to 350,000 customers in Belgium, owned by top 5
European (German) energy supplier RWE Group
ROLLING OUT THE PERSONALIZED
VIDEOS TO THE RIGHT CUSTOMERS,
RESULTED IN
CALL REDUCTION OF 49%
FOR CUSTOMERS WHO VIEWED VIDEO,
DIRECTLY IMPACTING CALL CENTER COSTS
OVERALL CALL REDUCTION OF
30%
WITH THE STATISTICAL MODEL
THERE WAS A LIFT OF 5.6%
IN PREDICTING THE CALLERS
Better Service, Lower Costs
Energy Supplier

34. Lily, the CX-OS
Customer-
Centric by
Design
Real-Time
Learning from
Feedback and
Analytics
Fast Benefit
Realization
Dramatic Increase
in Results (x10)
Enabling a
Collaborative Ecosystem
Always On Capitalize on Existing
Systems
Immediate Value from
Your Data Lake
Open
Architecture
Respecting
Security and
Privacy
Steering
Opti-Channel
Actions
Data-DrivenCustomer-Centric
Lily Enterprise: Key Features and Benefits

35. Recommendations
Featuring

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Commitment
Adoption
Applications
Skills
Structure
Partnerships
Sources
Management
Preparation
Methodology
Metrics
Business
KPIs
ROI
Workflow
Prioritization
Execution
Sharing
Production
Consumption
Activation
STRATEGY ORGANIZATION DATA ANALYTICS PROCESS TECHNOLOGY
Take Forrester’s Assessment for Customer Analytics –
Measure your capabilities across six dimensions

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Organize for analytics
22%
37%
41%
0% 20% 40% 60%
We have an analytics center of
excellence or shared service
across all channels and…
We have a centralized
measurement and analytics
team for the entire organization
We have a decentralized
measurement and analytics
team aligned to a channel or…
Which of the following structures best
represents where the analytics team sits
in your organization?

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Develop ROI calculations to prioritize projects and
measure impact
26%
Just 26% report that
measurement and analytics
projects are prioritized
based on a methodical
ROI/business justification
process

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Invest in scalable
customer
data architecture

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Partner with a system of insight provider to jumpstart
your capabilities
Five classes of
insights platforms

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24%
38%
16%
41%
40%
26%
Prospect
acquisition
Customer
acquisition
Customer on-
boarding
Customer
retention
Customer
loyalty and
engagement
Customer
recovery and
win-back
Stages of the customer lifecycle where respondents
reported "high usage of analytics"
Apply analytics across the customer lifecycle

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Don’t be afraid to get your hands dirty

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It WILL be worth the effort

44. Brandon Purcell
Senior Analyst
Forrester Research
bpurcell@forrester.com
Steven Noels
CTO & Co-Founder
NGDATA
stevenn@NGDATA.com
Thank you. Any questions?