Role of Segmentation
in Loyalty Marketing
Prof. Francisco N. de los Reyes
School of Statistics
University of the Philippines, Diliman
Marketing Maturity = Effectiveness & ROI
List Pull
Maturity of Direct Marketing
Mar
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Effe
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OI
Courtesy of SAS
SCV – Single Customer View
List Pull
SCV
Maturity of Direct Marketing
Mar
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Effe
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: R
OI “How many customers do I have?”
Courtesy of SAS
Segmentation
List Pull
SCV
Segment
Maturity of Direct Marketing
Mar
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Effe
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Courtesy of SAS
“Who are my customers?”
Analytics
List Pull
SCV
Segment
Analytics
Maturity of Direct Marketing
Mar
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Effe
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: R
OI
Courtesy of SAS
“How can I maximize my relationships?”
Event Detection
List Pull
SCV
Segment
Analytics
Event Detection
Maturity of Direct Marketing
Mar
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Effe
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: R
OI
Courtesy of SAS
“Who might leave me?”
Campaign Management
List Pull
SCV
Segment
Analytics
Event Detection
Campaign Mgmt
Maturity of Direct Marketing
Mar
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Effe
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: R
OI
Courtesy of SAS
“How effective are my campaigns?”
Inbound Right-Time Marketing
List Pull
SCV
Segment
Analytics
Event Detection
Campaign Mgmt
Real Time
Maturity of Direct Marketing
Mar
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Effe
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: R
OI
Courtesy of SAS
Optimization
List Pull
SCV
Segment
Analytics
Event Detection
Campaign Mgmt
Real Time
Optimize
Maturity of Direct Marketing
Mar
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Effe
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: R
OI
Courtesy of SAS
Levels of Segmentation
Info
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Courtesy of SAS
No Segmentation
Levels of Segmentation
Info
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Products Owned
No Segmentation
Levels of Segmentation
Info
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Channel Utilization
Products Owned
No Segmentation
Levels of Segmentation
Info
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Courtesy of SAS
Demographics
Channel Utilization
Products Owned
No Segmentation
Levels of Segmentation
Info
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Transaction Information
Demographics
Channel Utilization
Products Owned
No Segmentation
Levels of Segmentation
Info
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Courtesy of SAS
Psycho-graphics
Transaction Information
Demographics
Channel Utilization
Products Owned
No Segmentation
Levels of Segmentation
Info
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Courtesy of SAS
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Psycho-graphics
Transaction Information
Demographics
Channel Utilization
Products Owned
No Segmentation
Segment of One
Customer Segmentation
Which customer segment contributes most to our bottom line?
Key Business Questions
Customer Segmentation
Which segments should we grow?
Key Business Questions
Customer Segmentation
Which segments should be retained or closely monitored?
Key Business Questions
Customer Segmentation
What are the profiles of customers in each segment?
Key Business Questions
Customer Segmentation
What products are saleable in each segment?
Key Business Questions
Customer Segmentation
• Identifies strategic business focus and direction
• Analysis of customer behavior to gain insight
into customer needs and preferences
Key Benefits & Capabilities
What makes a segment?
Measurable identifying elements that distinguish from others
Segments desirably have these characteristics:
What makes a segment?
Defined contact points or channels through which communication is possible
Segments desirably have these characteristics:
What makes a segment?
Quantifiable size
so that cost computations may be done for targeting them
Segments desirably have these characteristics:
What makes a segment?
Have generally unique stated or implied needs
regarding the product or service
Segments desirably have these characteristics:
What makes a segment?
Stability and robustness to random shocks
(applies to some applications)
Segments desirably have these characteristics:
What is Segmentation?
“a process of creating groups of customers whohave SIMILAR behavior and characteristics”
Segmentation Types
Unsupervised data-driven segmentation; segments determined after data gathering and processing using statistical analyses
Supervised segmentation based on pre-defined factors
Supervised Segmentation
• Usually uses less variables with pre-defined “cuts”.
• Ad-hoc, user-driven
• Other variables are used as mere profilers and not active segmenters
• Applicable when user has a distinct focus and variables of interest are readily available.
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Some Prototype Segmentations
Customer Value versus Tenure
Customer Value versus Transaction Type & Frequency
Customer Value versus Risk
Profit Margin or Profit Rate against Tenure, Transaction Frequency or Risk
Purchase Behavior
Other possible information:
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Variety of Products Availed Life Stage Family Life Cycle The Remittance Market
Segmentation Variables
• Measures the amount of business brought in by the customer
• Also measures the capacity of a customer for cross-sell/upsell
• There is difficulty in measuring “high”, “medium” and “low” value.
• There are varying indicators of value• ADB (CA/SA) , Investments
• Loan amount/ Outstanding Balance
• Total purchase per transaction
Customer Value
Segmentation Variables
• Measures the loyalty of customer with respect to time
• Usually a “net time value”, i.e. lulls between product availment are not counted
• Skewness in data is an issue
Tenure
Segmentation Variables
• Identifies the “sleepers” from “transactors”
• Number of Transactions per Month is a usual metric.
• Time-between-transactions is a good substitute segmentation variable
Transaction Frequency
Segmentation Variables
• Tag customers given certain warning signals
• common indicators are:• Low ADB
• Defaults
• Lapses and claims
Risk Indicators
Segmentation Variables
• Metric for each customer’s contribution to total profit
• Used to level the number of products with the value of products availed
Profitability
Segmentation Variables
Common in Market Research but also evident in transactional information
• Utility/benefit from product
• Usage rate
• Loyalty vis-à-vis switching, hopping, ambivalence
• Propensity/Proclivity to buy/avail/take-up
• Temporal stimuli (payday, holidays, special events)
Behavior
Segmentation Variables
Some segmentation variables are also profiling variables
• Age, number of dependents, marital status
• Ownerships (home, car, business, etc.)
• Employment (nature of business, position, job tenure)
• Geographic information
• Delinquencies/ Fraud history, if any
• Channels
Profiling Variables
Cases in Point
Company A
• Launched a loyalty card
• Has big data on transactions
• Known as an innovator
• Challenge is to avert the impact of patent expiry and generic erosion
Company B
• Has different/diverse businesses in different industries
• Has product ownership, transactional data
• Challenge is to maximize customer relationship through cross-sell and upsell
Step 1: List Pull
• Involves definition of target population• By featured product/s
• By time period of observation and analysis
• By geographic coverage
• Brainstorm on Key Metrics and required raw data• Demographics
• Transactional behavior
• Profitability Drivers
List of Customers
List of Customers
Step 2: Single Customer View
• Consolidation of customer level information throughout the entire collection of data to be used for analytics
• Through the SCV, the analyst can tract a specific customer’s profile, behavior & profit contribution.
• The SCV is the recipient of scores
derived from analytics exercises.
Step 2: Single Customer View
SCV lends itself to queries
Statistical Matching
Removed inactive accounts
Removed cancelled accounts
Corporate Retail
Step 3: Segmentation
• Identify and understand best and worst performing customers
• Input for programs that focus on the following:• Increasing profitability
• Motivating positive behavioral changes:• Activate sleepers
• Increase usage of active customers
• Leads to best targets for cross-selling and up-selling
• Protect our most valued customers• It’s more expensive to acquire a new customer than retain a good one.
Sample Segmentation
Source: Data Mining Techniques in CRM: Inside Customer Segmentation, K Tsiptsis & A Korianopoulos
Use of card for entertainment (bars, resto)Use of card for gym, fitness centers. Highest internet usage
Sample Segmentation
Source: Data Mining Techniques in CRM: Inside Customer Segmentation, K Tsiptsis & A Korianopoulos
Increased purchases at apparel stores and accessory storesHigh balances
Sample Segmentation
Source: Data Mining Techniques in CRM: Inside Customer Segmentation, K Tsiptsis & A Korianopoulos
Use of card for travel & airfareHighest international usageHighest internet usage
Sample Segmentation
Source: Data Mining Techniques in CRM: Inside Customer Segmentation, K Tsiptsis & A Korianopoulos
Daily needsUse of the card mainly for supermarkets and gas.
Sample Segmentation
Source: Data Mining Techniques in CRM: Inside Customer Segmentation, K Tsiptsis & A Korianopoulos
Lowest purchase frequencyInfrequent but high value transactionsMain spend is electronic / appliance
Sample Segmentation
Source: Data Mining Techniques in CRM: Inside Customer Segmentation, K Tsiptsis & A Korianopoulos
>=50% spend on InstallmentLow retail spendRevolver
Sample Segmentation
Source: Data Mining Techniques in CRM: Inside Customer Segmentation, K Tsiptsis & A Korianopoulos
Use of card for heath purposes and DIY shopsLowest internet usageInfrequent but high value purchases
Sample Segmentation
Source: Data Mining Techniques in CRM: Inside Customer Segmentation, K Tsiptsis & A Korianopoulos
Diverse Card Usage.Purchase at different merchantsModerate balance amountHigh purchase frequency
Sample Segmentation
One segmentation led to another segmentation that targets loyalty.
Patient Segmentation
Doctor Segments (Example)
High Growth Potential
Highest % Highly-compliant low dosage usersAlso some highly-compliant high dosage users.
Lowest % Low-value patients
Profile Not recruiting actively. Most are interns.
Step 4: Analytics
• Wide array of statistical analysis aimed at understanding the customer base and the derived segments.
• Typical techniques are product association (market basket analysis), portfolio analysis (reports).
Companies A and B reached up to here.
Step 5: Event Detection
• Attempt to answer the question, “Who among my customers are likely to leave me?”
• This is usually addressed by Churn Modeling.
Example: ActualChurned Stayed Total
Model
Says
“Churn” 3,151 1,335 4,486
“Stay” 529 2,985 3,514
Total 3,680 4,320 8,000
Using logistic regression analysis, the model was able to capture
87% of the true state of nature (true churners and true stayers).
Further drill-down is done within the four outcome states.
Step 6: Campaign Management
Action: Prioritization & Retention
Step 6: Campaign Management
Action: Cross/Up Selling & Retention
Step 6: Campaign Management
Action: Brand Awareness
There are solutions which optimize Customer Management Process that reflects the voice of the customer, promotes retention and relationship building, supports business goals, leverages events / triggers, and is cross-channel and cross Business Unit.
Step 7: Inbound Right-Time Marketing
• “Right message at the right place and at the right time”
• Objective is to make heralds out of the customers
Step 8 : Optimization
• Cutting edge innovation
• Tailor-fit customer relationship
• Affinity and pride is established
• Must beware of oversolicitation.
Please Remember
• The goal of the segmentation analysis is to create manageable and meaningful customer groups among customers.
Please Remember
• Segmentation is instrumental in increasing shareholder value by identifying:• Most high-value segment(s)
• Segments with high potential for cross selling and/or up-selling
• By focusing communications on a targeted segment, a causal effect would be a reduction in campaign costs
Please Remember
• Segment definition • Supports retention, service prioritization and cross selling / up-selling efforts
• Serves as input in developing new products
• Segmentation is both a science and an art!
Thank you for your attention!
Prof. Francisco N de los Reyes
School of Statistics
University of the Philippines, Diliman