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CRM by Mind Map: CRM
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Customer relationship management is a model for managing a company’s interactions with current and future customers. It involves using technology to organize, automate, and synchronize sales, marketing, customer service, and technical support.

calculated across buyers and non-buyers

Share-of-Wallet and Market Share


New node, measured on a percent basis and can be computed based on unit volume, $ volume or equivalent unit volumes (grams, ounces)

Share-of-Wallet, New node

Popular Customer Based Value Metrics

Size of Wallet

Information source, Primary market research

Evaluation, assumption, large wallet size indicates more revenues and profits

defination, Size-of-wallet ($) of customer in a category

Share of Category Requirement

Information source, Numerator, volumetric sales of the focal firm - from internal records, Denominator, total volumetric purchases of the focal firm’s buyer base- through market and distribution panels, primary market research (surveys) and extrapolated to the entire buyer base

Evaluation, Accepted measure of customer loyalty for FMCG categories, does not indicate if a high SCR customer will generate substantial revenues or profits, controls for the total volume of segments/individuals category requirements

Defination, SCR (%) of firm or brand in category

for categories where the variance of customer expenditures is relatively small

Share of Wallet

Defination, Individual Share-of-Wallet (ISW) of firm to customer (%)

Information source, Numerator, From internal records, Denominator, primary market research (surveys), administered to individual customer, collected for a representative sample, extrapolated to the entire buyer base

New node

if the variance of consumer expenditures is relatively high

Aggregate Share-of-Wallet (ASW)

Information source, Numerator, From internal records, Denominator, market and distribution panels, primary market research (surveys), extrapolated to the entire buyer

Defination, Individual Share-of-Wallet (ISW) of firm to customer (%), Aggregate Share-of-Wallet of firm (%)

Evaluation, Important measure of customer loyalty

Transition Matrix

shows that the recommended strategies for different segments differ substantively

makes optimal resource allocation decisions only by segmenting customers along the two dimensions simultaneously

What is CRM

acquire & retain profitable customers

long-term and sustainable customer relationships - Add value

interdisciplinary field

maximizing customer satisfaction

CRM Business Strategy

Customers is core business

Effectively managing CR means Success

select & manage customers for Long Term

effective sales, marketing &services processes supported by customer-centric business philosophy & culture

Simple idea - treat different customers differently

Classification of CRM Applications


customers interaction


interact with the applications

centric intelligence

analyze results

Online networking

build personal relationships

Levels of e-CRM

Foundational service

Customer-centered services

Value-added services

Strategic Customer Based Value Metrics

Past Customer Value

Equation, New node

Transactions have to be adjusted for the time value of money

Limitations: Does not consider whether a customer is going to be active in the future.

Lifetime Value


Customer Equity

New node




Monetary value

Limitations, Independently links customer response data with R, F and M values and then groups customers, belonging to specific RFM codes (1 to 5), May not produce equal number of customers under each RFM cell since individual metrics R, F, and M are likely to be somewhat correlated, For practical purposes, it is desirable to have exactly the same number of individuals in each RFM cell

Breakeven Value, Breakeven - net profit from a marketing promotion equals the cost associated with conducting the promotion, Breakeven Value (BE) = unit cost price / unit net profit, BE computes the minimum response rates required in order to offset the promotional costs involved and thereby not incur any losses

RFM and BEI, Customers with higher RFM values tend to have higher BEI values, Customers with a lower recency value but relatively higher F and M values tend to have positive BEI values, Customer response rate drops more rapidly for the recency metric, Customer response rate for the frequency metric drops more rapidly than that for the monetary value metric

RFM Computation – Regression, Regression techniques to compute the relative weights of the R, F, and M metrics, Relative weights are used to compute the cumulative points of each customer, The higher the computed score, the more profitable the customer is likely to be in the future, The pre-computed weights for R, F and M, based on a test sample are used to assign RFM scores to each customer, This method is flexible and can be tailored to each business situation

Types of e-CRM





Examples of Customer Services

Search and comparison

Free Trial

Technical & information and Services

Customized products & services

Status Tracking

Tools for Customer Service

Personalized web pages


Email & automated response

Chat rooms

Live chat

Call centers


Issues Related to CRM Failures

Difficulty in measuring

Failure to identify & focus on specific business problems

Lack of active senior & sponsorship

Poor user acceptance

poorly defined business process for automate

How to implement CRM to avoid its failure

Conduct a survey

Carefully consider Sales,Service, Marketing and channel/partner management

Quality but not quantity

how CRM match organization objectives

refining existing CRM processes or reengineering CRM

Evaluate the workdone

Prioritize the organziation's requirement

Select the appropriate CRM software

Customer Selection Strategies

New node

Used for finding the best predictors of binary dependent variable

New node

Decision tree algorithms can be used to iteratively search through the data to find out which predictor best separates the two categories of a binary target variable

Problem with the approach: prone to over-fitting; the model developed may not perform nearly as well on a new or separate dataset

Logistic Regression

Method of choice when the dependent variable is binary and assumes only two discrete values

By inputting values for the predictor variables for each new customer – the logistic model will yield a predicted probability

Customers with high ‘predicted probabilities’ may be chosen to receive an offer since they seem more likely to respond positively

Linear and Logistic Regressions

Business Value of CRM

Cost avoidance

Increased revenue

Margin increases

Reduced inventory costs

Increased customer satisfaction

Increase in staff productivity

Risks of e-CRM

Taking on more than can be delivered

Getting over budget & behind schedule

Poor user adoption

Expensive maintenance & support


Garbage in-garbage out

Failure to measure success

marketing Metrics


Market Share

Sales Growth

Primary Customer-based

Customer Acquisition

Customer Activity

Popular Customer-based

Strategic Customer-based

Traditional and Customer-Based Marketing Metrics

Traditional Marketing Metrics

Market share, Share of a firm’s sales relative to the sales of all firms – across all customers in the given market, Market Share (%) (Equation refer to ppt), Evaluation, Information source, Numerator, Denominator

Sales Growth, Compares increase or decrease in sales volume or sales value in a given period to sales volume or value in the previous period, Sales growth in period t (%) (equation refer to ppt), Information source, Numerator and denominator: from internal records, Evaluation, Quick indicator of current health of a firm, Does not give information on which customers grew or which ones did not

Primary Customer Based metrics

Acquisition rate, Acquisition defined as first purchase or purchasing in the first predefined period, Acquisition rate (%) = 100 * Number of prospects acquired / Number of prospects targeted, Information source, Numerator: From internal records, Denominator: Prospect database and/or market research data, Evaluation

Acquisition cost, Acquisition cost ($) = Acquisition spending ($) / Number of prospects acquired, Precision depends on communication channel Direct mail vs. Broadcast, Information Source, Evaluation:, Important metric about cost efficiency of a campaign, Difficult to monitor on a customer by customer basis

Average Inter-Purchase Time (AIT), Easy to calculate, useful for industries where customers make frequent purchases, Firm intervention might be warranted anytime customers fall considerably below their AIT

Retention rate, Retention rate (%) = 100 * Number of customers buying in (t) and in (t-1) / Number of customers buying in (t-1), Defection rate (%) = 1 – Retention rate, Retention rate (%) = 1 – Defection rate, Lifetime duration = 1 / (1- Retention rate), Retention rate (%) = 1 – (1 / Lifetime duration), Assuming constant retention rates, number of retained customers in any arbitrary period (t+n) = Number of acquired customers in cohort * Retention rate (t+n)

Numerator & denominator: from internal records

Survival rate, Measured for cohorts of customers, Survival ratet (%) = 100 * Retention ratet * Survival ratet-1, Number of Survivors for period 1 = Survival Rate for Period 1 * number of customers at the beginning

P (Active), Probability of a customer being active in time t, P(Active) = T n, n is the number of purchases in a given period, T is the time of the last purchase, Non-contractual case

Projecting Retention Rates, Rrt = Rrc * (1 - exp(-rt) ), Rrt is predicted retention rate for a given future period,, Rrc is the retention rate ceiling, r is the coefficient of retention, r = (1/t) * (ln(Rrc) – ln(Rrc – Rrt ))

Lifetime Duration, Average Lifetime duration = Customers retainedt * Number of periods / N, N = cohort size, t = time period, Differentiate between complete and incomplete information on customer, Complete information - customer’s first and last purchases are assumed to be known, Incomplete information- either the time of first purchase, or the time of the last purchase, or both are unknown, Customer relationships, Contractual (“lost-for-good”): Lifetime duration is time from the start of the relationship until the end of the relationship, Noncontractual (“always-a-share”): Whether customer is active at a given point in time, One-off purchases

Win-back rate, Part of a acquisition process, Applicable to both Contractual and non-contractual situations, Proportion of the acquired customers in a period who are customers lost in an earlier period, Indicates either a successful communication of an important change in the product offering or service or a change in the customer needs

Popular Customer Based metrics

Share of Category Requirement

Size of Wallet

Share of Wallet

Expected share of wallet

Strategic Customer Based metrics

Past Customer Value

RFM value (Recency, Frequency and Monetary)

Customer Lifetime Value

Customer Equity