Chapter 3 Flashcards
(31 cards)
Medium rate of change customer dynamic sources
discrete life events, product learning efforts, product lifecycle
Immediate rate of change customer dynamic sources
discrete life events
changes in economy, government, industry, or culture
lifestyle approach
use generic stages of growth and their position in the lifecycle to determine customer preferences and associated strategies
dynamic customer segmentation
segments a firm’s existing customers on the basis of their similar, expected migration patterns
customer lifetime value
contribution of each customer according to the expected migration path over the entire lifetime with the firm
Pros of Lifecycle
simplicity
ease of use
Cons of Lifecycle
assumes all customers follow one curve
averages all customers
ignores causes of customer dynamics
misses many unique trigger points/migration paths
pros of dynamic customer segmentation
combines lifestyle and segmentation
matches strategic marketing thinking
identifies temporally homogenous groups
cons of Dynamic Customer Segmentation
segments not perfectly homogenous
puts continuous change into discrete changes
Pros of Customer Lifetime Value Approach
provides insights for AER decisions
supports customer-centricity
captures dynamics + heterogeneity
cons of Customer Lifetime Value Approach
requires insight into future migration and detailed financial data
Stages of Product Lifestyle
introduction, growth, maturity, decline
What is another name for dynamic-based segmentation?
AER model (Acquisition-Expansion-Retention Model)
acquisition stage
begins with first contact, typically before the first purchase occurs, when prospects and early customers have similar needs
expansion stages
firms try to upsell/cross-sell to expand sales and engage with existing customers
retention stage
customer migrate in pursuit of greener pastures
Hidden Markov Models (HMM)
form of dynamic segmentation that can uncover stages or “states” of customer behaviors, as well as how those states evolve
When to use HMM analysis?
understand dynamics/stages of customer’s relationship with a business
dynamically segment customer base
predict changes in stages
Fice Outputs of HMM Analysis
- Number of feasible/dynamic states in data
- Initial probability that a customer is in each state
- transition probabilities, or the probability that customers move from one state to another
- conditional probability of a behaviour given customers’ hidden state
- effect of marketing in moving customers across states
Why do customer states get hidden?
unaware of biases and what they are based on; customers just show behaviours, so marketers do not see all constraints
Variables for Customer Lifetime Value analysis
net cash flow
time horizon
discount rate
Variables for Simplified Customer Lifetime Value analysis
margin for customer in sales
annual marketing cost for customer
retention rate for customer as %
discount rate as a %
acquisition cost for customer in $
When to use Customer lifetime analysis
identify which customers are worth acquiring/retaining
determine where to target marketing programs to maximize firm’s return of marketing investments
understand true value of a customer to a firm
What does it mean if a CLV is negative?
customer is not profitable
