An overwhelming choice of applications, websites and digital platforms leaves our customers with multiple interaction channels and devices to connect with organizations. In a digitally connected economy, businesses need to represent a “single view” of the brand to the customer. The key here is to integrate customer information from multiple touch points and get a 360 degree view of the customer This presentation talks about BRIDGEi2i’s Customer Experience Tracking Platform – ExTrack and how it could help businesses with near-real-time actionable recommendations for improving customer experience.

1. @ 2015 BRIDGEi2i Analytics Solutions Pvt. Ltd. All rights reserved
6 May 2015
Customer Experience
Management

2. Customer experience management shifting from
reactive to proactive model
How do I improve customer experience for high
potential customer?
What type of customer do we have? Who are our
loyal customers?
Questions asked yesterday Questions asked today
What is the NPS trending at and how can we
improve the same? What are the key issues customers are facing &
how do I get a single view of all customer issues?
How are customer responding to satisfaction
surveys? What is their feedback? What are the key topics that customers are
talking about in social media?
How to reduce service cost?
How to improve customer satisfaction with
optimized spent?
How can I improve support center productivity?
How can I equip support center better to improve
customer satisfaction?

3. Using valuable data across customer lifecycle
Purchase
Receives emails Registers
product
Have support interaction
Respond to surveysPost in social media
Direct marketing interactions Repurchase
Transaction Data Marketing Interactions Data Registration Data
Survey Data Support Data ( Chat, Phone, Email)Social Media Data
Visits site Browse
Web traffic Data

4. Pertinent questions which analytics can help answering
Measure & track
customer
satisfaction
Identify key drivers
to customer
satisfaction
Recommend
actionable insights
• Who are the dissatisfied customer?
• What are the main pain points faced by customers?
• How is customer experience trending over time?
• What is the preferred channel to reach out to customer?
• What is impacting customer experience?
• Who are the best customers?
• Which customers are at risk and needs immediate attention?
• What are customer sentiments, needs, and preferences?
• How to optimize service cost?
• What product features to enhance?
• How to improve service agent productivity?
• How to sale at the point of service?

5. BRIDGEi2i platform intends to create a 360 degree view…
5
Mobile
Page views
Source
Time spent
Web data
Survey response
Reviews Blogs
Transactional
data
Marketing
response
2. Product
Purchase
3.Marketing
efforts
4. Repeat
Purchases
5. Customer
servicing
cost
6. Customer
Churn
1. Contact
Acquisition
Customer
Transactional
data
Support data
Social media
Summarize &
Visualize key
customer
experience metrics
Discover
correlation
between different
events and KPIs
Identify
immediate action
items to work on
Integrate customer touch-points data and create metrics to…

6. ExTrack – Create a quantitative dashboard to relate various
metrics…
6
Which geography needs more attention? What are the top features discussed by customers?
What is the channel preference for customers? How many reviews generated over past months?

7. ExTrack – Deep dive & discover areas that needs immediate
attention…
7
Open ended customer reviews…
…converted to structured data
identifying key topics …
…to deep dive into specific topic

8. Ex-Track – Provide a search and text mining mechanism for
various facets of experience…
Co-Relative Features Discussed Sentiments Expressed over Features
Mine open ended customer reviews
for search keywords…
…to identify sentiments related to associated terms & act on it
Performance
Speed
Wifi
Camera
Apps
Heat
3G
Charge
Replace
Service
Warranty
Updates
Refurbish
Support Battery Life Performance
BatterySupport
Negative Positive
Technology

9. We are already supporting few clients on customer
experience
9
Supported a sports
entertainment company
assess pain points in
customer experience
through analysis of social
media posts and
comments
Supporting a high tech
company in measuring
and reacting to IT user
experience across email,
chat and surveys
Supported a leading
group insurance provider
in US assess key drivers of
volume & dissatisfaction
with support instances
Supporting a large retailer
periodically track various
engagement indices and
correlate with visit , spend
share and social media
trends
Social Media Feedback
analysis
User Experience from
emails and surveys
Customer Support Log
analysis
Customer Loyalty Tracking

10. Understanding Pervasive User Experience For A Fortune 100
Networking Client
1010
• From the various data
sources available, each user
feedback is mapped to a
particular client service
• The service sub-
categorization mapping is
done based on the keyword
correlation between user
feedback and the services’
associated keywords
• The sentiment of each of the
user feedbacks pertaining to
a Service are classified
based on the sentiment
analysis algorithm and are
assigned one of the three
categories: Positive/
Neutral/ Negative
• Each of the user feedback
content is then analyzed to
identify the issue that it
relates to
• A noun based algorithm is
developed to understand
the theme/ issue that a user
informs about. This helps
the service owner to take
appropriate actions
• Categorizing
user feedbacks
to a particular
client
service/tool
• Understanding
the sentiment
of the feedback
• Identifying the
issue and help
the service
owner address
those issues
Data Key Features Outcome
Tools & Services Sentiment Analysis Thematic Analysis
Email
Remedy
Client feedback tools
Survey
• To have a single presentation layer to ensure that near real-time user feedback methods are in place in combination with
the existing client’s feedback programs offering new centralized services, robust analytics and an active response
process.
Objective
Tools &
Services
Sentiment
Analysis
Thematic
Analysis

11. Identification of key reasons for calling contact centre and
drivers of low first call resolution based on agent notes
1111
• Agent notes are textual, and
contains many spelling
issues. Publicly available
lexicons & dictionaries are
used to enable this
• The history of conversations
were broken into single
discussions to allow
separate analysis
• Semantics based text
mining methods are used to
segment discussions into
various topics which allowed
to identify various reasons
for calls.
• Analysis of service instances
needing multiple calls
provided insights on key
bottlenecks in the claim
management process.
• Analysis of time taken to
resolve various issues
helped to set right
expectations with customers
• Insights obtained
from the exercise
helped the insurance
company identify key
bottlenecks in the
process and
conceptualize
measures to
significantly decrease
the service instances
as well as improve
customer
satisfaction.
Data Sources Approach Outcome
Internal unstructured
query logs from call
centre Agents
The Client is a large provider of group insurance especially in the US. Hundreds of queries regarding claims and other
related service are made by customers at the company’s contact centre every day. The objective of the project was to
analyse the huge volume unstructured texts in contact centre agent comment to assess the key drivers of service call
volume and other related aspects .
Objective
Report:
Summary
Statistics
Data Structuring Identify Key topics Analyze drivers of delay
Report:
Identify
Problems
and trends

12. Assessing customer pain points from social media feedbacks
1212
BRIDGEi2i identified 3 sources of
information towards the Client’s
objective
• Yelp to mine consumer
sentiments. Slow data but with
profound insights
• Facebook to understand key
event response metrics.
• Twitter to understand rate at
which Client is engaging
patrons
• Share of voice across social
media – mentions in SM vis-à-
vis competitors
• Level of engagement –
enthusiasm across patrons and
prospects towards an event
• Feature level sentiment –
across all offerings vis-à-vis
competitors
• “Attention required” – on key
areas of offerings
• Use text categorization
algorithms to identify set of
words that describe the new
classification
• Associate a class match with
a probability to assess its
trustworthiness
• For the first few iterations, a
feedback loop will help the
learning algorithm
The client has been
able to use the
metrics to identify
focus areas in terms
of a brand presence
or perception
improvement.
Analysis is now
being rolled out
across all new sites.
Data Sources
Approach Outcome
Yelp
Twitter
Facebook
The Client is one of the world’s largest golf entertainment companies with assets in 11 cities across US and UK. As an
initiative to improve their brand presence and perception, The Client is interested in (a) understanding the reach of its social
media promotion activities and (b) innovative methods to identify & manage consumer sentiments as soon as a negative
event has been triggered.
Objective
Dashboard:
Monitor
Metrics
DATA GATHERING AND
MINING
Creation of Metrics Delivery Mechanism
Dashboard:
Driver
Analysis

13. THANK YOU