CUSTOMER SEGMENTATION
Analytics Framework

Sumit K Jha (MBA (Fin), LSSGB, PMP®)
Customer Segmentation in Complete Market
Development Cycle
Phase I: Customer
Segmentation

• Identify explicit or latent
c...
Approach for Customer Segmentation
Analytics
Understanding
Business
Problem
Identify objective
function
(increasing
custom...
Customer Segmentation Analytics process
Data Preparation
/Model
Development
/Scoring

Define
Segmentation
Objective
Identi...
Segmentation Objective
Segmentation Objectives


Improving profitability through more effective marketing



Serving bet...
Data Preparation, Modeling and Scoring
Data Preparation – Segmentation Variables


Active variables - variables, which ar...
Segment Profile Attributes
Segment profiling attributes
Segmentation is normally performed along with the following demogr...
Statistical Tools Used for Segmentation
Statistical tools


Cluster analysis is a tool commonly used for customer segment...
Segment Profiling
Segment Profiling


Explanation of the assigned customer segments



The result - characteristics of a...
Identification of Segmentation Strategies
Aspects of
Marketing

Explanation

Who?

Segment description. Differentiation co...
Example for Data Attributes for Banking
customer





Customer demographics (retail/corporate client)
Product informati...
Preliminary List of attributes to be Used for
Customer Segmentation for a IT company
Who

Where

How

What

How much

Why
...
Thank You
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Customer segmentation approach

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Customer segmentation approach

  1. 1. CUSTOMER SEGMENTATION Analytics Framework Sumit K Jha (MBA (Fin), LSSGB, PMP®)
  2. 2. Customer Segmentation in Complete Market Development Cycle Phase I: Customer Segmentation • Identify explicit or latent customer need • Outperform the competition by developing uniquely appealing products and services Phase III: Institutionalization Inputs Business Context Phase II: Planning and execution Inputs Inputs • Divide the market into meaningful and measurable segments according to customers' needs, their past behaviors or their demographic profiles • Determine profit potential of each segment by analyzing the revenue and cost impacts of serving each segment • Ideally this should answer who, where, how, what, how much and why Outputs • Target segments according to their profit potential and the company's ability to serve them in a proprietary way • Measure performance of each segment and adjust the segmentation approach over time as market conditions change • Invest resources to tailor product & services and create marketing & distribution programs to match the needs of each target segment Outputs Outputs Project lifecycle is explained in the next slide • Customer loyalty • Service delivery programs • Innovation • Targeted marketing • Unique customer segments with defined characteristics • Product development and delivery • Competitive advantage • Increased share of wallet
  3. 3. Approach for Customer Segmentation Analytics Understanding Business Problem Identify objective function (increasing customer loyalty, better marketing ROI, etc.) ► Envisage expected results ► Develop ingoing hypotheses Consultative% Time approach spent required Activities ► 10% Develop Solution Approach Define model specifications ► Expected output framework (dashboard) ► Develop project plan and timeline ► 10% Collate and Manage Data Data request, pull, transfer ► Data cleaning, enrichment and structuring ► Analysis database creation ► 50% 25% of the time spent with consultative approach Run Analytics Hypothesis testing ► Multivariate analysis ► Quality assurance ► 20% Deliver Solution Preview results with stakeholders ► Feedback to rerun analytics ► Final delivery ► 10%
  4. 4. Customer Segmentation Analytics process Data Preparation /Model Development /Scoring Define Segmentation Objective Identify objectives ► Behavioral and Marketing Segments ► Directed versus Undirected Segmentation ► Segmentation Variables ► Number of Segments ►Segment scoring ► Segment profile attributes ► Statistical tools for segmentation ► Segment Profiling Explanation of customer segments ► Characteristics of customers in each segment ► Assigning marketing customer segment ► Identification of Segment Strategies Explain who, what, why, how much, when, how of marketing
  5. 5. Segmentation Objective 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 highprofit-potential customers in the customer base  Provide global vision of company’s customers  Identify valuable customers  Identify cross-sell opportunities 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 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
  6. 6. Data Preparation, Modeling and Scoring 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. Number of Segments  Good Cluster Definition – 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  Trial and Error Process Segment Scoring  Process of assigning the segment identification variable for each customer on the basis of some pre-specified segment structure.
  7. 7. Segment Profile Attributes Segment profiling attributes Segmentation is normally performed along with the following demographic, geographic, psychographic, and behavioral variables;  Demographic segmentation variables describe characteristics of customers and include age, gender, race, education, occupation, income, religion, marital status, family size, children, home ownership, socioeconomic status, and so on. Note that demographic segmentation normally refers to segmentation with these demographic variables.  Geographic variables include various classification of geographic areas, for example, zip code, state, country, region, climate, population, and other geographical census data. Note that this information can come from national census data. For more, see geographic segmentation.  Psychographic segmentation variables describe life style, personality, values, attitudes, and so on. Note that psychographic segmentation normally refers to segmentation with these psychographic variables.  Behavioral segmentation variables include product usage rate and end, brand royalty, benefit sought, decision making units, ready-to-buy stage, and so on.  Past business history, Customers' past business track records can be extremely useful for segmentation. This may include total amounts purchased, purchasing frequency, (credit) default records, (insurance) claims, responsiveness for marketing campaigns, and so on.
  8. 8. Statistical Tools Used for Segmentation Statistical tools  Cluster analysis is a tool commonly used for customer segmentation. In cluster analysis, the goal is to organize observed data into a meaningful structure. This type of analysis is different from traditional statistical approaches such as linear regression in that cluster analysis does not have a dependent variable  The tree building approach, CHAID, is also used for determining customer segments in a market. A CHAID decision tree uses multi-class splits to segment the data into nodes. Members of nodes tend to be very similar within the node as well as different from members of other nodes. This tool often effectively yields many multi-way frequency tables when classifying a categorical response variable, making it popular in marketing research
  9. 9. Segment Profiling Segment Profiling  Explanation of the assigned customer segments  The result - characteristics of a typical customer within each segment  Utilization in assigning the correct marketing segment for 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
  10. 10. Identification of Segmentation Strategies Aspects of Marketing Explanation 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.
  11. 11. Example for Data Attributes for Banking customer    Customer demographics (retail/corporate client) Product information (number and types of products, loyalty) Transactional behavior   Balances      Channel usage number (ATM, online, branch) per given time period. Complaints Risk profile   Average, opening and closing balances per defined time period. Utilization of distribution channels   Number, amount and types of transactions per defined time period Delinquency/claim (number and amount per defined period) Household relations Contact History Competitive information Clustering Example- Partition data into groups with similar characteristics
  12. 12. Preliminary List of attributes to be Used for Customer Segmentation for a IT company Who Where How What How much Why Industry Geography of sale Through sales representative Type of Product/s sold Size of each contract Unique product/service matching customer requirement Geography Work place Through channel partners Type of Service/s sold Overall sales within a year Effective marketing campaign Size of the company (Revenue, employees) Exhibition Through key account manager Type of Software sold Share of wallet Recommendation from customers or any other Market share in the industry Road show New purchase Specification to product delivery (Straight/Bundling) Time taken (sales cycle) Relationship brought by new account manager or sales person Public/private Conferences Repeat purchase (Upsell or Crosssell) Specification to services delivery (onsite, off-site) Profitability of contract/sales Discounts given Line of business within the company Online Through solution partners Specification to software delivery (Straight/Bundling) Discounts given Product/service perception Number of meetings for one sale Effective sales pitch Number of employees working on each contract Product/service part of larger solution given by a partner Credit history Relationship with the company (Integrated /special accounts) Through competitive bids
  13. 13. Thank You

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