Data Warehouse Design to Support Customer Relationship Management Analyses Colleen Cunningham,...

Data Warehouse Design to Support Customer Relationship Management Analyses

Colleen Cunningham, Il-Yeol Song and Peter Chen

DOLAP ‘04November 12, 2004

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Agenda

Background Motivation Methodology Results Areas for future research Contributions & Conclusions Q & A

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Agenda Background

CRM Definition Why Use CRM? Customer Lifetime Value (CLV)

Motivation Methodology Results Areas for future research Contributions & Conclusions Q & A

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CRM Definition

Proactive strategy Utilizes organizational knowledge Utilizes technology

Support profitable long-term relationships with customers

All customers are not equal More expensive to acquire new

customers than it is to retain customers

Repeat customers can generate more than twice as much gross income as new customers

Why Use CRM?

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Customer Lifetime Value (CLV)

CLV = Historic value + Potential Future value

Historical Value = Nj=1 (Revenuej - Costj)

j: individual products that the customer has purchased

Potential Future Value = Nj=1 (Probabilityj X Profitabilityj)

j: individual products that the customer could

potentially purchase

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Use customers’ Lifetime Value (CLV) to classify customers

Table 1: Customer Segments

Historic Value

Low High

Future Value

High II. Re-Engineer IV. Invest

Low I. Eliminate III. Engage

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Table 2: Corresponding Segmentation Strategies

Historic Value

Low High

FV

HighUp-sell & cross-sell activities

and add valueTreat with priority and

preferential

Low Reduce costs and increase prices

Engage customer to find new opportunities in order to sustain

loyalty

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Agenda

Background Motivation

Overview New Metrics

Methodology Results Areas for future research Contributions & Conclusions Q & A

Motivation The DW directly impacts a company’s ability to

perform analytical CRM analyses

50% - 80% of CRM initiatives fail (Myron and Ganeshram 2002; Panker 2002)

Systematically examine CRM factors that affect design decisions for DWs in order to: Build a taxonomy of CRM analyses Develop heuristics for CRM DW design decisions Create metrics to objectively evaluate CRM DW models

New Metrics

% Success Ratio (rsuccess) = Qp / Qn

Qp: the total number of analyses that the model could successfully handle

Qn: the total number of analyses issued against the model

It measures the “robustness” of the model

New Metrics

CRM Suitability Ratio (rsuitability) = Ni=1(XiCi)

/ N N: the total number of applicable analysis

criteria C: individual score for each analysis

capability X: weight assigned to each analysis capability It measures the “appropriateness” of the

model for a specific company

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Agenda

Background Motivation Methodology

Identify Minimum Requirements Preliminary Starter Model for CRM DW Implementation Evaluation of Model

Results Areas for future research Contributions & Conclusions Q & A

Methodology Overview Identify categories of analyses Identify specific analyses & KPIs Categorize the specific analyses & KPIs Identify specific data points Design the CRM starter model Implement the CRM starter model Continue collecting additional analyses Randomly select analyses to run Evaluate the model

Minimum Design Requirementsfor CRM DWs

Analysis Type/Data Maintenance DescriptionCampaign Analysis Ability to evaluate different campaigns and responses over

timeChannel Analysis Ability to evaluate the profitability of each channel (e.g.

stores, web, phone, etc.)Cross-selling Analysis Ability to identify additional types of products that customers

could purchase, which they currently are not purchasing.

Customer Attrition Ability to identify root causes for customer attritionCustomer Loyalty Ability to understand loyalty patterns among different

relationship groupsCustomer Profitability Ability to determine profitability of each customerCustomer Retention Ability to track customer retentionCustomer Scoring Ability to score customersCustomer Segmentation Ability to segment customers into multiple customer

segmentationsCustomer Service Analysis Ability to track and analyze customer satisfaction, the average

cost of interacting with the customer, the time it takes to resolve customer complaints, etc.

Demographic Analysis Ability to perform demographic analysis

Table 3: Minimum Design Requirements for CRM Data Warehouse

Minimum Design Requirementsfor CRM DWs

Table 3: Minimum Design Requirements for CRM Data Warehouse (Continued)

Analysis Type/Data Maintenance DescriptionHousehold Analysis Ability to associate customers with multiple extended

household accounts.Market Profitability Ability to determine profitability of each marketProduct Delivery Performance Ability to evaluate on-time, late and early product deliveriesProduct Profitability Ability to determine profitability of each productProduct Returns Ability to analyze the reasons for and the impact of products

being returnedTrend Analysis Ability to perform trend analysisUp-selling Analysis Ability to analyze opportunities for customers to buy larger

volumes of a product or a product with a higher profitability margin

Web Analysis Ability to analyze metrics for web site

Preliminary starter model for CRM DW

Profitability Fact Table

PK,FK1 ProductKeyPK,FK2 ChannelKeyPK,FK3 SupplierKeyPK,FK4 PromotionKeyPK,FK5 CustomerKeyPK,FK6 CustomerDemographicsKeyPK,FK7 TimeKeyPK,FK8 MarketKeyPK,FK9 CommentsKeyPK,FK10 ExtendedCustomerKeyPK,FK11 SalesRepresentativeKey

OrderNumber (DD)

Channel Dimension

PK ChannelKey

Customer Dimension

PK Customer Key

CustomerID (Natural Key)FK1 CommentsKeyFK2 MarketKeyFK3 SalesRepresentativeKeyFK4 ActivationDateKey (FK)FK5 AttritionDateKey (FK)FK6 CountyDemographicsKey Product Dimension

PK ProductKey

Supplier Dimension

PK SupplierKey

Time Dimension

PK TimeKey

Promotion Dimension

PK Promotion Key

Customer Behavior Dimension

PK ExtendedCustomerKey

Customer Demographics Dimension

PK CustomerDemographicsKey

Market Dimension

PK MarketKey

Extended Household

PK,FK2 HouseholdKeyPK,FK1 CustomerKey

Household Dimension

PK HouseholdKey

Sales Representative Dimension

PK SalesRepresentativeKey

CustomerExistence

PK,FK1 Customer KeyPK,FK2 StartDate

ProductExistence

PK,FK1 ProductKeyPK,FK2 StartDate

Customer Service Fact Table

PK,FK1 StartDatePK,FK2 StartTimePK,FK3 Customer Key

InteractionID (Natural Key)FK4 ChannelKey

Future Value Fact Table

PK,FK1 ScenarioKeyPK,FK2 Customer KeyPK,FK3 StartDatePK,FK4 ProductKey

Scenario Dimension

PK ScenarioKey

sTime Dimension

PK sTimeKey

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Preliminary starter model for CRM DW

Profitability for any transaction in the fact table can be calculated as follows: Gross Profit = Gross Revenue –

Manufacturing Cost – Marketing Cost – Product Storage Cost

Net Profit = Gross Profit – Freight Cost – Special Cost – Overhead Cost

Gross Margin = Gross Profit/Gross Revenue

Profitability Fact Table

PK,FK1 ProductKeyPK,FK2 ChannelKeyPK,FK4 PromotionKeyPK,FK6 CustomerDemographicsKeyPK,FK7 TimeKeyPK,FK3 SupplierKeyPK,FK5 CustomerKeyPK,FK8 MarketKeyPK,FK9 CommentsKeyPK,FK10 ExtendedCustomerKey

OrderNumber (DD)QuantitySoldGrossRevenueManufacturingCostMarketingPromotionCostSalesDiscountAmountNetRevenueProductCostProductStorageCostGrossProfitFreightCostSpecialCostOverheadCostNetProfitItemEarlyCountItemOnTimeCountItemLateCountItemCompleteCountItemDamageFree CountTaxAmountUOMConversion FactorUOMProductReturned

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Implementation

Operating System: Windows 2000 Server

DBMS: SQL Server 2000

Hardware: DELL 1600 database server, single processor, 2.0 MHz

Fact tables contained 1,685,809 records

Evaluation of Model

A series of randomly-selected CRM queries were executed against the proposed data warehouse schema

The metrics were computed % Success Ratio (rsuccess)

CRM Suitability Ratio (rsuitability)

Evaluation of Model

Category Analysis

Channel AnalysisWhich distribution channels contribute the greatest revenue and gross margin?

Customer Attrition What are the top 10 reasons for customer attrition?

Customer AttritionWhat is the impact of the value of the customers that have left on revenues?

Customer Profitability Analysis What are the customers' sales and margin trends?

Customer Profitability AnalysisWhich customers are most profitable based upon gross margin and revenue?

Customer RetentionHow many unique customers are purchasing this year compared to last year?

Market Profitability Analysis Which markets are most profitable overall?Market Profitability Analysis Which products in which markets are most profitable?

Order Delivery PerformanceHow do early, on time and late order shipment rates for this year compare to last year?

Order Delivery Performance & Channel Analysis

How do order shipment rates (early, on time, late) for this year compare to last year by channel?

Product Profitability Analysis What is the lifetime value of each product?Product Profitability Analysis Which products are the most profitable?

Returns AnalysisWhat are the top 10 reasons that customers return products?

Returns AnalysisWhat is the impact of the value of the returned products on revenues?

Returns AnalysisWhat is the trend for product returns by customers by product by reason?

Table 4: Sample CRM Analyses

Evaluation of Model: Sample Queries

SELECT b.CustomerKey, b.CustomerName, Sum(a.GrossRevenue) AS TotalRevenue, Sum(a.GrossProfit) AS TotalGrossProfit, TotalGrossProfit/TotalRevenue AS GrossMarginFROM tblProfitabilityFactTable a, tblCustomer bWHERE b.CustomerKey=a.CustomerKeyGROUP BY b.CustomerKey, b.CustomerNameORDER BY Sum(a.GrossRevenue) DESC;

Figure 1: Customer Profitability Analysis Query - Which customers are most profitable based upon gross margin and revenue?

SELECT c.Year, b.MarketKey, b.LocationCode, b.Location, b.Description, b.CompetitorName, d.ProductCode, d.Name, Sum(a.GrossRevenue) AS TotalRevenue, Sum(a.GrossProfit) AS TotalGrossProfit, TotalGrossProfit/TotalRevenue AS GrossMarginFROM tblProfitabilityFactTable a, tblMarket b, tblTimeDimension c, tblProductDimension dWHERE b.MarketKey=a.MarketKey And a.TimeKey=c.TimeKey And a.ProductKey=d.ProductKeyGROUP BY c.Year, b.MarketKey, b.LocationCode, b.Location, b.Description, b.CompetitorName, d.ProductKey, d.ProductCode, d.Name, b.MarketKeyORDER BY Sum(a.GrossRevenue) DESC;

Figure 2: Product Profitability Analysis Query - Which products in which markets are most profitable?

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Agenda

Background Motivation Methodology Results

Initial Taxonomy of CRM Queries Initial Heuristics for CRM DW Design Decisions

Areas for future research Contributions & Conclusions Q & A

Initial Taxonomy of CRM Analyses

Decision Class Category Analysis Potential Use(s) KPI

S Channel Analysis

Which distribution channels contribute the greatest revenue and gross margin? Resource allocation

S & T Customer AttritionWhat are the top 10 reasons for customer attrition?

Insights for process improvements attrition rate

S & T Customer Attrition

What is the impact of the value of the customers that have left on revenues?

Insights for process improvements attrition rate

SCustomer Profitability Analysis

What are the customers' sales and margin trends? Classify customers

gross margin, revenue

SCustomer Profitability Analysis

Which customers are most profitable based upon gross margin and revenue? Classify customers

gross margin, revenue

S Customer Retention

How many unique customers are purchasing this year compared to last year?

Identify the threshold to overcome with new customers

unique customers/year

S & TMarket Profitability Analysis

Which markets are most profitable overall?

Setting performance goals, allocate marketing resources

gross margin/market

S & TMarket Profitability Analysis

Which products in which markets are most profitable?

Setting performance goals, allocate marketing resources

gross margin/ products/ market

Table 5: Initial Taxonomy of CRM Analyses (S=Strategic and T=Tactical)

Initial Taxonomy of CRM Analyses

Decision Class Category Analysis Potential Use(s) KPI

S & TOrder Delivery Performance

How do early, on time and late order shipment rates for this year compare to last year? Setting performance goals

early delivery, on-time delivery, late delivery

S

Order Delivery Performance & Channel Analysis

How do order shipment rates (early, on time, late) for this year compare to last year by channel?

Setting performance goals, monitoring trends

early delivery, on-time delivery, late delivery

S & TProduct Profitability Analysis

What is the lifetime value of each product?

Managing product cost constraints, identify products to potentially eliminate from product line

gross margin/ product

S & TProduct Profitability Analysis

Which products are the most profitable?

Managing product cost constraints, identify products to potentially eliminate from product line

gross margin/ product

S & T Returns AnalysisWhat are the top 10 reasons that customers return products?

Create pareto charts to identify problems to correct, setting performance goals count

S & T Returns Analysis

What is the impact of the value of the returned products on revenues?

Create pareto charts to identify problems to correct, setting performance goals

count, revenue, profit

S & T Returns Analysis

What is the trend for product returns by customers by product by reason?

Create pareto charts to identify problems to correct, setting performance goals, identify problematic accounts (identify customers that may leave), assess additional service fees

count, revenue, profit

Table 5: Initial Taxonomy of CRM Analyses (S=Strategic and T=Tactical) (Continued)

Initial Heuristics for DW Design Decisions

# Heuristic Benefit

1Include all attributes required to compute the profitability of each individual transaction in the fact table(s)

The ability to generate a profit & loss statement for each transaction, which can then be analyzed along any dimension

2Each dimension that will be used to analyze the Profitability fact table should be directly related to the fact table

Provides improved query performance by allowing the use of simplified queries (i.e. support browsing data)

3 Pay careful attention to the Customer dimension It forces attention to the center of CRM, the customer

4Create a relationship between the Customer dimension and the Market and Sales Representative dimensions

Provides the ability to quickly determine the current market and Sales Representative for the customer by merely browsing the Customer dimension

5Include the attrition date and reaason for attrition attributes in the Customer dimension

Provides the ability to quickly determine if a customer is no longer a a customer by browsing the Customer dimension only

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Attributes that are likely to change at a different rate than other attributes in the same dimension should be in a separate dimension Minimize the number of updates

7Create a separate "existence" dimension for any entity that can have a discontinuous existence

Provides the ability to track the periods in which the instance of the entity is valid (needed to support some temporal queries)

Table 6: Initial Heuristics for Designing CRM DWs

Initial Heuristics for DW Design Decisions

# Heuristic Benefit

8Create a separate "existence" dimension for any attribute whose historical values must be kept

Provides the ability to track accurate historical values, even during periods of inactivity

9Create a relationship between the Time dimension and each "existence" dimension

Provides the ability to perform temporal queries efficiently using descriptive attributes of the Time dimension

10"Existence" dimensions should be in a direct relationship with their respective original dimensions

11 There should always be a CustomerExistence dimensionThe ability to track and perform analyses on customer attrition

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If some products are either seasonal or if it is necessary to determine when products where discontinued, then create a ProductExistence dimension

The ability to perform analyses for seasonal and discontinued products

13There should be a Household dimension and an ExtendedHousehold dimension Provides the ability to perform Household analyses

14The organizational hierarchical structure can be contained in one "Market" dimension

Provides the ability to maintain a history of the organizational changes, and the ability to perform analyses according to the organizational structure

Table 6: Initial Heuristics for Designing CRM DWs (Continued)

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Agenda


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Areas for Future Research

Compile & categorize additional queries and KPIs that are relevant to CRM

Develop a taxonomy for DW schemas by industry Which schemas are best suited for which types

of analyses?

Compare alternative models

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Develop data mining techniques that can be utilized with the starter model

Efficiently build aggregation and cube for MOLAP Construction rules

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Effective use of materialized views in ROLAP What types to create? How to tune? How to evolve?

Contributions

Starter model for CRM Taxonomy of CRM queries and their uses,

including KPIs Heuristics for designing a data warehouse

to support CRM Sampling Technique New Evaluation Metrics

% Success Ratio = Total Passed / Number of Queries

CRM Suitability Ratio = Total Score/Total # of criteria

Conclusions

Our starter model can be used to analyze various CRM analyses: customer profitability analysis, product profitability analysis, channel profitability analysis, market profitability analysis,…

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Agenda


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Q & A

Thank You!

Contacts Colleen Cunningham:

[email protected] Dr. Il-Yeol Song: [email protected]

Data Warehouse Design to Support Customer Relationship Management Analyses Colleen Cunningham,...

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