study unit 1 crm and business analytics › unisim.e... · consumer loyalty, churn & retention...
TRANSCRIPT
Study Unit 1
CRM and Business Analytics
ANL 309 | Business Analytics Applications
© 2014 SIM University. All rights reserved.
Introduction
• Customer Relationship Management (CRM) H b i l ti b li d t• How business analytics can be applied to support CRM
© 2014 SIM University. All rights reserved.
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“.
© 2014 SIM University. All rights reserved.
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.
© 2014 SIM University. All rights reserved.
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.
© 2014 SIM University. All rights reserved.
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.
© 2014 SIM University. All rights reserved.
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.
© 2014 SIM University. All rights reserved.
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
© 2014 SIM University. All rights reserved.
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.
© 2014 SIM University. All rights reserved.
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.
© 2014 SIM University. All rights reserved.
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.
© 2014 SIM University. All rights reserved.
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.
© 2014 SIM University. All rights reserved.
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.
© 2014 SIM University. All rights reserved.
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.
© 2014 SIM University. All rights reserved.
Stages in a Customer Life Cycle
Prospects• Prospects
• Responders
• Established Customers
• Former Customers
© 2014 SIM University. All rights reserved.
Stages in a Customer Life Cycle
Prospects• Prospects
• Responders
• Established Customers
• Former Customers Potential customerswho form the targetmarket for a product por service.
© 2014 SIM University. All rights reserved.
Stages in a Customer Life Cycle
Prospects• Customer Value
• Prospects
• Responders• Customer Acquisition
• Established Customers• Response Models
C t S t ti• Former Customers
• Customer Segmentation
• Target Marketing
© 2014 SIM University. All rights reserved.
Stages in a Customer Life Cycle
• Prospects
• Respondersp
• Established Customers
• Former Customers Prospects who show a genuine interest by their inquires or signing up of a q g g pproduct or service.
© 2014 SIM University. All rights reserved.
Stages in a Customer Life Cycle
• Prospects
• Responders• Customer Value
p
• Established Customers• Credit Scoring
• Customer Segmentation• Former Customers
Customer Segmentation
© 2014 SIM University. All rights reserved.
Stages in a Customer Life Cycle
• Prospects
• Responders
• Established Customers
• Former Customers Current users of products and services
© 2014 SIM University. All rights reserved.
Stages in a Customer Life Cycle
• Prospects• Cross-sell and
Up-sell• Responders
• Established Customers• Customer Loyalty
• Former Customers• Fraud Detection
© 2014 SIM University. All rights reserved.
Stages in a Customer Life Cycle
• Prospects
• Responders
• Established Customers Users who voluntarily orEstablished Customers
• Former Customers
Users who voluntarily or involuntarily leave or switch to another offering or company.p y
© 2014 SIM University. All rights reserved.
Stages in a Customer Life Cycle
• Prospects
• Responders
• Established Customers Att iti Ch M d lEstablished Customers
• Former Customers
• Attrition or Churn Models
• Win-back Models
© 2014 SIM University. All rights reserved.