Study Unit 1 CRM and Business Analytics › unisim.e... · Consumer Loyalty, Churn & Retention • CstomerLoaltCustomer Loyalty: An established c stomer ill contin e to deli erAn

Study Unit 1

CRM and Business Analytics

ANL 309 | Business Analytics Applications

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Introduction

• Customer Relationship Management (CRM) H b i l ti b li d t• How business analytics can be applied to support CRM


Introduction to Business Analytics

• Extensive use of data, statistical and quantitative analysis, explanatory and predictive modelling, and fact-based management to drive decision making

• Input for human decisions or fully automated decisions. Business intelligence is querying, reporting, OLAP, and "alerts“.


Introduction to Business Analytics

• According to IBM, the data generated daily amounts to possiblyAccording to IBM, the data generated daily amounts to possibly more than 2.5 quintillion bytes of data. Data comes from everywhere; sensors used to gather climate information, postings to social media platforms, digital pictures and videos, consumer purchasing information, cell phone GPS signals and many others. This data is Big Data.

• Big Data spans four dimensions: Volume, Velocity, Variety, and Veracity.


Customer Management Relationship

Customer Relationship Management (CRM) leverages on databases and data mining techniques (or business analytics) t d l t l ti hi b t d itto develop strong relationships between a company and its customers. This is to maximise the lifetime value of itscustomers.


Business Analytics and CRM

Business Analytics: The process of data mining customer databases to discern consumer behaviour patterns for the purpose of CRM.

• Past behaviours are useful for predicting future behaviours ofPast behaviours are useful for predicting future behaviours of consumers.

• Technological breakthroughs lead to the accumulation of huge• Technological breakthroughs lead to the accumulation of huge amount of data about their customers over time.


Two Important Aspects of CRM

• Identifiy the types or segments of customers.

• Develop strategies targeted at each segment

Examples of such strategies

• Develop better relationship with more profitable customers.

• Locate and attract prospective customers who will be profitable.p p p

• Find appropriate strategies for unprofitable customers.


Key Applications of Business Analytics to CRM

• Customer acquisition and segmentation

• Cross-selling and up-selling

• Consumer loyalty, churn and retention

C dit i• Credit scoring

• Fraud detection


Customer Acquisition and Segmentation

C stomer Acq isition Identification of prospecti e c stomers• Customer Acquisition: Identification of prospective customers, understand their profiles, assess their value, and formulate an acquisition strategy.

• Customer Segmentation: Division of a market into different groups base on characteristics relevant for marketing purposes.


Cross-selling & Up-selling

Cross selling When a compan offers e isting c stomers ne• Cross-selling: When a company offers existing customers new products and services related to their current purchases.

• Up-selling: When the customer is committed to purchase additional units or a premium version of the product or service.


Consumer Loyalty, Churn & Retention

C stomer Lo alt An established c stomer ill contin e to deli er• Customer Loyalty: An established customer will continue to deliver customer lifetime value to the company.

• Churn: Customers switch to a different company or competitor in search of a better value proposition.

• Retention: Companies must understand why customers churn and take steps to retain them.


Credit Scoring

Credit scoring: The application of business analytics or statistical model to develop a summary score. This helps in the decision p y pmaking process of lenders to grant customer credit.


Fraud Detection

• Fraud: A deliberate act of deception which will benefit theFraud: A deliberate act of deception which will benefit the perpetuator(s).

• Different kinds of fraud• Different kinds of fraud

• CRM: Customer fraud involves customers deceiving companies into i i th thi th h ld t h h i l thgiving them something they should not have or charging less than

they should.


Customer Life Cycle

• A customer lifecycle describes the different stages in the y geconomic relationship between the customer and a business.

• Understanding a customer life cycle helps in CRM It allowUnderstanding a customer life cycle helps in CRM. It allow companies to target the right offer to the right customer at the right time for the right price.


Stages in a Customer Life Cycle

Prospects• Prospects

• Responders

• Established Customers

• Former Customers



Prospects• Prospects

• Responders


• Former Customers Potential customerswho form the targetmarket for a product por service.



Prospects• Customer Value

• Prospects

• Responders• Customer Acquisition

• Established Customers• Response Models

C t S t ti• Former Customers

• Customer Segmentation

• Target Marketing



• Prospects

• Respondersp


• Former Customers Prospects who show a genuine interest by their inquires or signing up of a q g g pproduct or service.



• Prospects

• Responders• Customer Value

p

• Established Customers• Credit Scoring

• Customer Segmentation• Former Customers

Customer Segmentation



• Prospects

• Responders


• Former Customers Current users of products and services



• Prospects• Cross-sell and

Up-sell• Responders

• Established Customers• Customer Loyalty

• Former Customers• Fraud Detection



• Prospects

• Responders

• Established Customers Users who voluntarily orEstablished Customers


Users who voluntarily or involuntarily leave or switch to another offering or company.p y



• Prospects

• Responders

• Established Customers Att iti Ch M d lEstablished Customers


• Attrition or Churn Models

• Win-back Models


Documents

Study Unit 1 CRM and Business Analytics › unisim.e... · Consumer Loyalty, Churn & Retention • CstomerLoaltCustomer Loyalty: An established c stomer ill contin e to deli erAn