1 segmentacia 60min.ppt - uniag.sk · statistical analysis olap access, visualization and...
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Customer Segmentation
Katarína Frühwaldová
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Customer Intelligence
Data for modeling process
Profile & Segment Customers
Tools
Demo
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Customer Intelligence
Data for modeling process
Profile & Segment Customers
Tools
Demo
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Customer Intelligence
Customer Intelligence is the concept of gathering, analyzing and exploiting informationof the company's customers with the aim to create
and maintain a mutually beneficial relationship between the Organization and its Customers where
the Organization attempts tomaximize the Life Time Value of the relationship.
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Marketing Analytics
MARKET RESEARCH
MARKETING ANALYTICS
MARKETING
RESEARCH
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
The task of Marketing Analytics
Marketing Analytics turns data into knowledge (profits)
Marketing Database
Operational CRMDATA
KNOWLEDGE
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Marketing Analytics helps to answer...
time
Better Cross-/ Up-Selling
Intensification Retention Termination/Recovery
More efficient customer retention
Acquisition
Profit
Faster termination of potentially less valuable customer relationships
More efficient acquisition of new customers
Recovery of potentially valuable customer relationships
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Types of Analyses used in Marketing Analytics
Segmentation
Fraud Probability
Probability of Default
Product Association
Channel Preference
Expected Value of Response
Cross-sell Probability
Up-sell Probability
Activation ProbabilityChurn
Probability
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Customer Intelligence Definition
Data for modeling process
Profile & Segment Customers
Tools
Demo
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
A Single Customer View…
Simple Data Customers Households Products Transactions Relationship Managers
Derived / Additional Data Contact/Response History Scores Events Surveys/Questionnaires Demographics Profitability Measures Segments
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Customer Data You Should Collect - Banking
Customer demographics (retail/corporate client) Product information (number and types of products, loyalty) Transactional behavior
» Number, amount and types of transactions per defined time period Balances
» Average, opening and closing balances per defined time period. Utilization of distribution channels
» Channel usage number (ATM, online, branch) per given time period. Complaints Risk profile
» Delinquency/claim (number and amount per defined period) Household relations Contact History Competitive information
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Customer Data You Should Collect -Insurance
Customer Demographics
Relationship with the insurance company (tenure etc)
Product Portfolio (Policy and Riders Information)
Coverage Information
Claims Information
Premium and Payment Information
Agent Information
Complaints
Contact History
Competitive Information
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Customer Data You Should Collect - Telco
Customer Demographics
Relationship with the insurance company (tenure etc)
Product Portfolio (number and types of products –prepaid/postpaid)
Messages Information
Airtime Information
Payment Information
Contact History
Competitive Information
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Customer Intelligence Definition
Data for modeling proces
Profile & Segment Customers
Tools
Demo
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Terminology
Segmentation is in essence the process by which items or subjects are categorized or classified into
groups with similar characteristics. That characteristic could be one or more attributes.
Randal S. Collica CRM Segmentation and Clustering
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Clustering ExamplePartition data into groups with similar characteristics.
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Behavioral and Marketing Segments
Marketing segments - groups of customers who are similar to each other with respect to some socio-economic-demographic factors like: age, sex, family status, occupation, living area etc.
Behavioral segments - groups of customers who behave in a similar manner in relation with the business.
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Directed versus Undirected Segmentation
Supervised (directed) segmentation –business analyst defines one or more target variables that should drive the segmentation
Unsupervised (undirected) segmentation –analytical algorithm uncovers hidden patterns that may be significant and useful for the given purpose.
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Segmentation Process
1. Segmentation Objective Definition
2. Data Preparation/Model Development/Scoring
3. Segment Profiling
4. Identification of Segment Strategies
5. Implementation of Segment Strategies
6. Measurement and Evaluation
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Segmentation Objectives
Improving profitability through more effective marketing
Serving better to high priority customers
Changing the customer mix to provide a greater proportion of high-profit or high-profit-potential customers in the customer base
Provide global vision of company’s customers
Identify valuable customers
Identify cross-sell opportunities
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Data Preparation – Segmentation Variables
Active variables - variables, which are expected to have an influence on clustering.
Descriptive variables - further profiling of the segments that are determined by active variables. They are used for identification of the main characteristics of the clusters.
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Number of Segments
Trial and Error Process
Good Cluster Definition (for CRM purposes) –clusters whose members are very similar to each other while at the same time the clusters themselves are well separated (by criteria selected for clustering)
Business Purpose – 5 to 12 segments
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Segment Profiling
Explanation of the assigned customer segments
The result - characteristics of a typical customer within each segment
Utilization in assigning the correct marketing segmentfor each behavioral segment
The typical explanative variables used in profiling: Age, Marital status, Occupation, Education level, Annual
income, Postal code (or information derived from that, such as city, town, or village), Activity level of customer, Life cycle of customer, Customers market segment, Residence status code
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Segment Profiling – Example
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Segment Scoring
Process of assigning the segment identification variable for each customer on the basis of some
pre-specified segment structure.
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Segmentation Reports
Customer Segment Size Report
Segment Movement Report
Migration
Distribution of Segments over Time
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Segment Strategies
Define Segment Strategy and Action Plans for each Segment
WHO? Segment description. Differentiation comparing to other segments.
WHAT? What products, bundles?
WHY? Segment’s needs based message.
HOW MUCH? Pricing rules.
WHEN? Time for interactions.
HOW? Preferred distribution channels.
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Customer Intelligence Definition
Data for modeling proces
Profile & Segment Customers
Tools
Demo
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
SAS Enterprise Guide
Reporting, graphical and analytical tasks
Data management - preparation and cleaning
Statistical Analysis
OLAP access, visualization and manipulation
Result distribution and sharing
Administration and security
Scripting and automation
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
SAS Enterprise Miner:
Answers Questions Such As Which customers are likely to respond to an offer? Which transactions are likely to be fraudulent? Which factors contribute to equipment failure? Which prospects will be the best customers? Which customers are likely to churn in short-term? Which portfolios are likely to be the most risky? Which claims are likely to be paid at less than
100%?
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
Customer Intelligence Definition
Data for modeling proces
Profile & Segment Customers
Tools
Demo
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
SEMMA Metodológia
SAMPLE – vzorky dát, vytvorením jednej alebo viacerých tabuliek
• Append • Data Partition• Filter• Input Data• Merge• Sample• Time Series
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
SEMMA Metodológia
EXPLORE – preskúmanie dát, hľadanie vzťahov, vzorov, neočakávaných trendov...
• Association• Cluster• DMDB• Graph Explore• Market Basket• MultiPlot• Path Analysis• SOM/Kohonen• StatExplore• Text Miner (optional)• Variable Clustering• Variable Selection
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SEMMA Metodológia
MODIFY – úprava údajov vytváraním nových premenných, transformovaním, nahrádzaním hodnôt, rekódovaním...
• Drop• Impute• Interactive Binning• Principal Components• Replacement• Rules Builder• Transform Variables
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SEMMA Metodológia
MODEL – vytváranie modelu použitím analytických metód
• AutoNeural• Decision Tree• Dmine Regression• DMNeural• Ensemble• Gradient Boosting• MBR• Model Import• Neural Network• Partial Least Squares• Regression• Rule Induction• SVM• TwoStage
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.
SEMMA Metodológia
ASSESS – výber najlepšieho modelu, aplikácia modelu na nové dáta
• Cutoff• Decisions• Model Comparison• Segment Profile• Score
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Company Confidential - For Internal Use OnlyCopyright © 2010, SAS Institute Inc. All rights reserved.