This presentation was presented at #CustomerAnalytics Conference, Chicago 2014 by Maruti Peri, VP Sales. BRIDGEi2i helps businesses extract each ounce of loyalty in today's “Age of the Customers” as customer loyalty keeps fighting an uphill battle with increased product choices and proliferation of prospective client information. To know more about BRIDGEi2i Customer Intelligence Solutions, visit http://www.bridgei2i.com/customer-intelligence.html

1. © 2014 BRIDGEi2i Analytics Solutions Pvt. Ltd. All rights reserved
Prithvijit Roy
CEO & Co-founder
prithvijit.roy@bridgei2i.com
#CustomerAnalytics Summit
Maruti Peri
VP, Business Development
maruti.peri@bridgei2i.com

2. 2
“We see our
customers as
invited guests to a
party, and we are
the hosts. It’s our
job every day to
make every
important aspect of
the customer
experience a little
bit better.”
Jeff Bezos
“ It is not the
employer who pays
the wages.
Employers only
handle the money.
It is the customer
who pays the
wages.”
Henry Ford
In a world of constant change…there is one tenet which hasn’t…Customer Focus

3. A Customer Centric Organizational Approach
3
Marketing
Sales
Operations
Finance
Product
Development
Customer
Centricity
CUSTOMER CENTRICITY ACROSS BUSINESS FUNCTIONS
Product
Profitability
Current Sales
Brand Equity Customer Equity
Market Share
Customer Equity
Share
Product NVP Customer NPS
Product Life-cycle
Customer-
lifecycle
Strategy driven by
Products
Strategy driven by
Customer needs
Incentives at
product level
Incentives at
customer level
METRICS THAT MATTER
Customer
Lifetime value
Customer
Profitability

4. 4
Customer Profile
Segment
Profile
Web
Profile
CRM
Profile
Social
Profile
Market
Research
Data
Web
Data
CRM
Data
Social
Data
Data is key to a Customer Centric Approach

5. 5
Customer Analytics Journey
360 degree customer data view
to understand customers
Target-marketing models and
personalization opportunities
Drive personalized recommendations,
operationalize campaigns

6. Customer Analytics : The Evolution
Market Research Transactional Data
INFORMATION
Offline Sales
Insights
IMPACT
Purchase
Propensity Models
INSIGHT
Segmentation
Social /
Unstructured Data Micro-segmentation
focus Lifetime Value
Real-time
recommendations on
cloud/mobile/web

7. Operationalize
impact
Develop actionable
insights
Diverse Applications of Personalization
7
Pervasive Customer
Experience Analytics
Customer Lifetime
Value
Channel
Recommendation
Engine
Case StudyIndustry Function
Build customer
knowledge
Focus
Information Technology- B2B Customer Service
Insight Ecommerce- B2C Marketing
Impact CPG Sales

8. 1. Pervasive Customer Experience Analytics (1/2)
8
• Business: Global Provider of IT services to other enterprises.
• Challenges :
• Declining Contract renewals
• Sliding Premium / Margins
• Clueless about what was driving this.
Disparate Data Survey Data
Customer
support data Social data
• Why are Customer Satisfaction metrics not reflecting the slide?
• Are we measuring our performance right?
• What do we do to reverse the slide?
Business Questions?
Rich incidence as well as
account level satisfaction
scores
All transcribed customer
support data across
calls/email/chats
Reviews/ Blogs/ Opinions/
Expert Analysis

9. 1. Pervasive Customer Experience Analytics (2/2)
9
Query across 360 degree customer
data view
Identify drivers of customer experience
from customer interactions
Prioiritize key actions to focus on
Data Integration Platform
360 degree Customer View Key Driver Analysis Insights and Recommendations
Incidence rate
10%
Adoption Rate
10%
Support Satisfaction
14%

10. 10
• Who will be my most valuable customer in the future?
• How do I focus my investments on potential High value Customers?
• How do I build Loyalty and move away from deep discounting?
2. Customer Lifetime Value (1/2)
Demographics Past purchases Typical promotions
Marketing Costs
Frequency of
purchases
Offline to online
transactions
Data Considered for
calculating LTV
Business : Global technology B2C ecommerce site.
Challenges:
• Repeat Purchase rates declining.
• Discount seeking customers eroding margin.
• Acquisition quality suspected to be lower.
Business Challenges

11. 2. Customer Lifetime Value (2/2)
11
• Estimation of an appropriate “future
period”
• Capture typical “pathways” to value
for different customers
• Statistical models to predict “High
Value” segment and non transactors
• Rank order customers from 1- 10 on the
basis of future value potential next 2
years
• Ascribe expected value to each LTV
segment
• Design loyalty programs to connect with
best customers
• Overlaid with current propensity models
to assess and refine %
• marketing spend on high revenue
customers
High
Med
Low
LTV
based Persona New
Customer
Or Prospect
SCORING
Modelling Approach Strategy Design Implementation
Target : 5% increase in Repeat Purchase rates.
$25 increase in Average Ticket Size

12. Business : A CPG Giant in ASIA . Sells to 1.5+ M stores through about 50 + sole
distributors spread across 1000+ branches
Challenges :
• High turnover in Stores and shelf space.
• Intense Competition from a transforming market place.
3. Channel Recommendation Engine (1/2)
Data Available
Store level sales data
Store Panel Data Promotion SKUs
Product Rates
Business Questions
• How do we help stores increase their revenues?
• How do we capture shelf space to keep competition out?
• How do I use distributors and wholesalers to build loyalty for the brand

13. 3. Channel Recommendation Engine (2/2)
13
Segmentation of stores based on
extent and mix of purchases
Identify stores similar to a given
store based on purchase pattern
Define expected purchase behaviour
and potential cross sells
High Level Segmentation Define Neighborhood Build Recommendation Rules
Recommendation Hit-rate
45%
Revenue uplift
10%

14. For the Business
14
More Customers
More Revenue
from Customer
Add Customer
at a Lower Cost
For the Customer
A better and more personalized Experience
Evaluate
Purchase
Install
Usage
Marketing
Support
Disposal
Interact
…to enhance customer experience and business impact

15. 15
INFORMATION
INSIGHT
IMPACT
Valueforbusiness
Actionability
BRIDGEi2i bridges the
gap in customer
understanding from
INFORMATION to
IMPACT through
INSIGHTS.
BRIDGEi2i solves
unstructured problems
by using multiple data
sources, leveraging
technology and
operationalizing the
solution for clients
How BRIDGEi2i transforms the Customer Journey

16. CUSTOMER INTELLIGENCE
Customer Experience Management Analytics | Personalized
Lifecycle Marketing Analytics
www.bridgei2i.com
: BRIDGEi2i