Analytics across the customer lifecycle

Nirmal Palaparthi 21 July 2015

Why is Analytics important?

• Latest buzzword?

• Provides jobs?

• Solves business problems

Customer lifecycle

• Acquisition

• Usage management

• X sell and Upsell

• Retention

• Advocacy

Acquisition Analytics• Start from prospects

• Goal: better ROI

• Same budget more conversions or

• Lower budget same conversions

• Solutions

• Response models, Conversion models, Funnel analytics

• Leading bank increases mailer response rate from 4% to 19%

Well…. data is kinda important!

Usage Analytics

• Different strokes for different folks

• Behavioral Segmentation

• Parameters for segmentation that reflect useful behaviour

• Watchout: Demographic segmentation is useful in product design, rarely in usage

Behavioral Segmentation

Credit Card portfolio segmentation construct

Behavioral Segmentation

X Sell and Upsell Analytics• right product to the right customer at the right time

using the right channel

• Selling to existing customers is far easier than selling to new customers

• Incoming channels make for better campaigns

• Examples: Bancassurance, beer and diapers

• Solutions: Market Basket Analysis, X-Sell modeling

Xsell and Upsell in actionProduct Details

Product DetailsXSell

Upsell

Retention Analytics

• Leaky funnel

• Different definitions of attrition

• NUNP, Dormancy, Inactive

• Early warning signals

• Example: Attrition models: Photo card

Churn Model in action

Advocacy Analytics

• Member get Member

• Reviews are powerful, even with strangers

• Solutions: Sentiment analysis, Social Listening

Sentiment Analysis has multiple benefits

Source: Slideshare: How Do Users Like This Feature? A Fine Grained Sentiment Analysis of App Reviews (RE2014 Paper)

uh… and one more thing…

Listening based reinvention

Questions?

nirmalholdings@gmail.com