BRIDGEi2i - #CustomerAnalytics Conference, Chicago 2014

© 2014 BRIDGEi2i Analytics Solutions Pvt. Ltd. All rights reserved

Prithvijit Roy CEO & Co-founder

[email protected]

#CustomerAnalytics Summit

Maruti Peri VP, Business Development

[email protected]

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“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

A Customer Centric Organizational Approach

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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

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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

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Customer Analytics Journey

360 degree customer data view to understand customers

Target-marketing models and personalization opportunities

Drive personalized recommendations, operationalize campaigns

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

Operationalize impact

Develop actionable

insights

Diverse Applications of Personalization

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Pervasive Customer Experience Analytics

Customer Lifetime Value

Channel Recommendation

Engine

Case Study Industry Function

Build customer knowledge

Focus

Information Technology- B2B Customer Service

Insight Ecommerce- B2C Marketing

Impact CPG Sales

1. Pervasive Customer Experience Analytics (1/2)

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• 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

1. Pervasive Customer Experience Analytics (2/2)

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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%

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• 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

2. Customer Lifetime Value (2/2)

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• 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

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

3. Channel Recommendation Engine (2/2)

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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%

For the Business

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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

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INFORMATION

INSIGHT

IMPACT

Val

ue

for

bu

sin

ess

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

CUSTOMER INTELLIGENCE Customer Experience Management Analytics | Personalized Lifecycle Marketing Analytics

www.bridgei2i.com

: BRIDGEi2i