Multi Channel CX Ashish Rishi

AWARE CONSIDER PREFER PURCHASE You

DECISIONS

Complexity in customer behavior informs your organisational decision making

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AWARE CONSIDER PREFER PURCHASE You

DECISIONS

…however, customer footprints fragment when viewed through multiple data lenses

Structured

Semi-structured

Unstructured

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…and end up in these siloes

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Instead, what you want is this…

Who is looking at these interactions?

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The Warmth of the cold call !!

Prospect List/Data

Scoring Engine

Target List

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Scoring Engine

Target List Communication

Strategy

Lead Nurturing Engine

Active Experience Data Input

Email Campaigns

Web metrics

Social metrics

Prospect List/Data

The Warmth of the cold call !!

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A lead scoring model for a travel and hospitality major in India

Opportunity • A vacation ownership company wanted to qualify leads from online channels • It required a solution to identify leads with a higher propensity to sign up for its offerings

Solution • Developed a lead scoring model with regression analysis to rank leads most likely to sign up • Scientific allocation of leads to sales executives • Captured variables like ability and willingness to buy

Results • Identified that 30% of leads contribute to 70% of sales, improving conversion rate by 2.33 times • Grouped leads into Hot, Warm and Cold to help strategize sales

Qualifying leads for unqualified success

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From Aeons to nanosec - Loan Account Management

Default Behavior Models

Escalated Collections Effort

Standard Marketing Communication

Credit Bureau Data

Loan Payment Behavior Macro-economic Indicators

Past Purchase Behavior

Upsell/Cross Sell Models

High Propensity of near-term default

High Propensity of a purchase

Traditional approaches rely on proprietary or provider data to build “one size fit all strategies”

Website/App browsing Data

Social Media Activity

Credit/Debit Card Usage Pattern

Cross Product Payment Behavior

Mobile phone usage patterns

Social Network Data

Product Recommendation Engines

Payment Plan Revision Engines

Early Identification of Default and Focused Repayment

Plan

Need based Product Offer and Custom Marketing

Communication

Multi-channel data driven strategies are personalized and lead to enhanced customer experience while generating more business value

Loan Payment Behavior

Traditionally, loan account management in credit lending organizations has been reactive and generic. Advent of big data has paved the way for custom strategies that boost customer experience

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Building analytics engine to support Operations, Risk and Marketing functions

• An MFI was undergoing digital transformation and is looking to embed analytics at the core

• It required a solution to that helps all core functions by

applying and utilizing analytics across the business value chain

• Developed a central decision engine that had four advanced interventions: • A behavioural scorecard that

provides the risk status of each customer

• A credit approval engine that is used at the time of loan approval

• A operations risk engine that tracks all aspects of operations

• A portfolio management tool

• Cost of operations reduced by200 bps

• Approval process reduced from 7 days to 7 sec

• Workflows for operation management initiated

• Expansion of product portfolio

Developing analytics platform for a MFI

Opportunity Solution Results

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CAPstone Framework

1 2 Segment & Measure

Relate & Recognize 3 Manage &

Act

• Arrive at logical segments • Identifying experience

parameters • Experience Measurement

• Ongoing customer scorecard • Ongoing process reviews

• Overlay experience on behaviour

• Identify experiential drivers of behaviour

From experience measurement to action

Establishing measurable linkages between customer experience and customer behaviour provide proactive tools that help enterprises leverage this knowledge in taking tactical decisions towards customer engagement

Conventional Data

Traditional instruments and data such as NPS, VoC provide insights on customer experience, however they often fail to raise real time alerts around customer disengagement

NPS

VoC

Synergistic Data

Customer behavior data is a significant proxy to customer experience. Customer behavior could be an indicator to set up early warning systems

Transactions

Sales

Customer Experience to …… Customer Advocacy

Only 1 out of 26 unhappy customers complain. Others forsake..

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• A leading cement manufacturing company wanted to provide their sales team with better intelligence on dealers to improve prioritization and planning of sales efforts

• The challenge was to

introduce and implement the idea of data driven dealer engagement across the large function

• Proposed CAPStone framework for building effective Dealer management system entailing A dealer segmentation to

identify natural clusters based on sales behaviour and demographics.

An engagement survey exercise to identify drivers of experience and

A dealer scorecard that provides the ability to track dealer performance on a regular basis

• The segmentation activity helped client unearth the top 2% dealers that were driving one third of the business and hence were core to them.

• The scorecard provided an ability to track all 4000+ dealers at the same time and flag disengagement behaiour

• The capstone framework provided sales team targeted actionable at individual account level

Dealer Engagement Solution

Opportunity Solution Results

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1. Inter Channel diffusion always existed, however the leakage effect was too low to garner interest

• The channel diffusion is at its peak now. “Social is not important for us”

2. Departmental walls of wisdom need to redefine themselves

• Silos of knowledge will die the slow death of non-existence. “My metric is my power”

3. Metric definitions & benchmarks have to evolve

• Call centre productivity is still a metric, how you measure it is important. “One tool to solve it all”

4. Customer Experience moments are more real time than ever before. They are not one size fit all

• Real time is not a myth. It exits all around us. “She will come back”

5. CX Analytics is an enabler to true customer experience. Customer (& his FB Friends) is still the king

• Create Strategy, test & Learn , Implement , learn again. “One ML to help another ML”

What do we learn!

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Contact :

Ashish Rishi

ashish@mafoianalytics.com>

Website: http://www.mafoianalytics.com/metafore

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