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1
Customer Portfolio Management: Implications for the Asian Hospitality Industry
Wei Lun Lecture at The Chinese Univers ity of Hong Kong
by
Michael D. Johnson Dean and E. M. Statler Professor Cornell Univers ity School of Hotel Adminis tration\ May 2, 2008
2
Agenda
n Overv iew of Customer Portfolio Management n The evolution of management thought:
q Market share management q Customer satisfaction and loyalty management q Customer Portfolio Management (CPM)
n CPM Framework n Implications for the As ian Hospitality Industry
q Customer portfolios in growth markets q The rise of competition and eroding margins q “High touch” versus “low touch” services q The diffusion of service innovations q Shocks in the system: Volatility in costs and resulting margins
n Summary and Conclusions
3
Customer Portfolio Management (CPM) n At its core, CPM is about creating value with all of the customers in a portfolio: q Johnson and Selnes (2004, 2005) q Selnes and Johnson (2004)
n Customers create value in fundamentally different ways and at different points in time, which requires viewing customers as a portfolio of different assets.
n The value of the approach depends upon: q The variance in a company’s customer relationships. q Adaptation of the marketing mix to those relationships.
4
Evolution of Management Thought n 1950s1970s: Market share management q Market share is the key to profitability! n Under what assumptions?
n 1980s1990s: Satisfaction and loyalty management q Creating satisfied and loyal customers is the key to profitability! n Under what assumptions?
n Today: Customer portfolio management and strategy
5
Evolution of Management Thought
Customer Portfolio Strategy: Optimize Investments in Relationships Over Time
Customer Portfolio Management: Create Value through
Acquaintances, Friends and Partners
Market Share Management:
Optimize Returns on Volume and Cost Reductions
Satisfaction and Loyalty Management:
Optimize Returns on Satisfaction and Relationship Management
6
The Power of Weak Relationships
n The intuition of CPM becomes clear with the Power of Weak Relationships!
n Many of a company’s most profitable customers today were strangers or mere acquaintances but a decade ago.
n Examples: q L.L. Bean’s customer loyalty strategy q Credit Suisse’s focus on larger customer accounts
7
CPM Framework
n A typology of relationships: q Acquaintances, friends and partners
n Relationship evolution n The diffusion process and cost implications
n The CPLV (Customer Portfolio Lifetime Value) model
n Simulation results: q Baseline scenario
8
Relationship Types and Characteristics
To capture value through the premium
customers pay for customized
experiences and solutions.
To capture value through the premium
customers pay for differentiated offerings.
To capture value through standardization,
economies of scale and scope.
What is the seller’s objective?
Satisfaction and trust evolve to a level of
relationship commitment.
An elevated level of customer satisfaction creates a level of trust and brand equity that reinforces repeat
buying.
A minimum level of customer satisfaction reinforces inclusion of the seller amongst a customer’s options.
What drives buyer behavior?
A customized offering adapted to an
individual customer or buying organization.
A differentiated offering adapted to specific market segments
A relative commodity or form of industry
standard
What does the seller offer?
Partners Friends Acquaintances
Relationship Types
Relationship Characteristics
9
Relationship Evolution
Stranger t
Stranger t+1
Stranger t+2
Stranger t+3
Stranger t+4
Acquaintance t+1
Acquaintance t+2
Acquaintance t+3
Acquaintance t+4
Friend t+2
Friend t+3
Friend t+4
Partner t+3
Partner t+4
Time
Churn Churn Churn Churn
Churn Churn Churn
Churn Churn
10
Sample Bass Model Diffusion Curve
0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
0 25 50 75 100
Time Period t
Cus
tomers in Tim
e t
11
CPLV Model
n Conceptually, the CPLV model calculates the contribution, over time, of acquaintances, friends and partners in a portfolio taking into account: q A unit cost per customer, which is a function of a diffusion process and associated economies of scale
q A base revenue per customer q Price premiums gained from closer relationships q A cost of relationship conversion (e.g., from acquaintances to friends)
q A cost of churn (e.g., gaining customers from competitors at the same relationship level)
12
CPLV Model (From Johnson and Selnes 2004, Journal of Marketing)
CPLV = ∑[(A st * (CR st – UC st ) – (A st Converted * AC st Conversion ) – (A st Gained * AC st Gaining )]
+ ∑[(F st * (CR st – UC st + FP st ) – (F st Converted * FC st Conversion ) – (F st Gained * FC st Gaining )]
+ ∑[(P st * (CR st – UC st + PP st ) – (P st Converted * PC st Conversion ) – (P st Gained * PC st Gaining )]
n
t = 1
n
t = 1
n
t = 1
13
Sample Simulation Results: Baseline scenario
$1,000,000.00
$0.00
$1,000,000.00
$2,000,000.00
$3,000,000.00
$4,000,000.00
$5,000,000.00
$6,000,000.00
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97
Time Period
Con
tribution
Acquaintances Contribution Friends Contribution Partners Contribution
14
Dynamic Aspects of the Asian Hospitality Industry
n Unprecedented growth in the Asian hospitality industry
n Increased competition and eroding margins n “High touch” versus “low touch” services n The diffusion of service innovations n Shocks in the system
15
Growth in the Asian Hospitality Industry n With the economic growth of China, India and other SE Asian economies, the hospitality industry is booming.
n Unlike markets in the US, where service concepts diffuse through a given population, Asian markets are also growing their base population of customers.
n What are the CPM implications of a diffusion process with sustained growth in a market’s population? q Assume t = months and a 10% AGR in the customer population
16
Diffusion in a growth industry
0
500,000
1,000,000
1,500,000
2,000,000
2,500,000
0 25 50 75 100
Time Period t
Customers in Tim
e t
17
Portfolio Contributions in a “Growth” Market: A New Baseline
$2,000,000.00
$0.00
$2,000,000.00
$4,000,000.00
$6,000,000.00
$8,000,000.00
$10,000,000.00
$12,000,000.00
1 8 15 22 29 36 43 50 57 64 71 78 85 92 99
Time Period
Con
tribution
Acquaintances Contribution Friends Contribution Partners Contribution
18
Competition and Eroding Margins
n As the Asian service economy continues to grow: q More and more competitors will enter the markets. q As market conditions evolve toward zero economic profit, margins will systematically erode.
q Assume the base CR (customer revenue) erodes by 25% over time.
19
Competition and Eroding Margins
$8,000,000.00
$6,000,000.00
$4,000,000.00
$2,000,000.00
$0.00
$2,000,000.00
$4,000,000.00
$6,000,000.00
1 8 15 22 29 36 43 50 57 64 71 78 85 92 99
Time Period
Con
tribution
Acquaintances Contribution Friends Contribution Partners Contribution
20
High Touch versus Low Touch
n “High touch” services (four and five star hotels and restaurants) are imminently less scalable than are “low touch” services.
n The biggest HR need today is for front line service people who can provide service excellence.
n Our simulations capture this difference through a comparison of: q The new baseline model with 50% economies of scale (low touch services)
q A model with 20% economies of scale (high touch services)
21
High Touch Services with Lower Economies of Scale
$2,000,000.00
$1,000,000.00
$0.00
$1,000,000.00
$2,000,000.00
$3,000,000.00
$4,000,000.00
1 8 15 22 29 36 43 50 57 64 71 78 85 92 99
Time Period
Con
tribution
Acquaintances Contribution Friends Contribution Partners Contribution
22
The Diffusion of Service Innovations q Where is the next “hot” restaurant or hotel in a given market?
q Today’s technology and resulting customer generated media (CGM) has accelerated wordofmouth (WOM) and resulting diffusion processes for such concepts.
q Consider a scenario where the WOM factor increases 200% compared to traditional diffusion curves.
23
Rapid Diffusion of Service Innovations
$4,000,000.00
$2,000,000.00
$0.00
$2,000,000.00
$4,000,000.00
$6,000,000.00
$8,000,000.00
$10,000,000.00
$12,000,000.00
1 8 15 22 29 36 43 50 57 64 71 78 85 92 99
Time Period
Con
tribution
Acquaintances Contribution Friends Contribution Partners Contribution
24
Cost Shocks
n Be it the cost of oil, food, money or other commodities, we have entered uncertain economic times.
n Assume “cost shocks” (increases of 33% of initial unit cost) occur in periods 34 and 67 (out of 100).
n What are the implications for CPM?
25
Cost Shocks
$3,000,000.00
$2,000,000.00
$1,000,000.00
$0.00
$1,000,000.00
$2,000,000.00
$3,000,000.00
$4,000,000.00
1 8 15 22 29 36 43 50 57 64 71 78 85 92 99
Time Period
Con
tribution
Acquaintances Contribution Friends Contribution Partners Contribution
26
Just for fun, let’s model a growth market with low scalability (high touch), eroding margins (growing competition), and rapid service diffusion?
$5,000,000.00
$4,000,000.00
$3,000,000.00
$2,000,000.00
$1,000,000.00
$0.00
$1,000,000.00
$2,000,000.00
$3,000,000.00
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49
Time Period
Con
tribution
Acquaintances Contribution Friends Contribution Partners Contribution
27
Summary and Conclusions
n Overall, the results reinforce the “power of weak relationships.” q Acquaintances provide economies of scale that benefit the entire portfolio.
q Acquaintances are the basis for future, more profitable friends and partners.
n Building closer relationships with customers protects the portfolio from eroding margins, even in a growth market. q Friendships are a natural way to balance risk and return.
n However, even in high touch (e.g. luxury) markets, acquaintances are critical to the value of the portfolio.
28
Summary and Conclusions
n The complexity of decision making in Customer Portfolio Strategy increases dramatically with rapid service diffusion.
n “Shocks” in the system quickly turn a large population of profitable acquaintances into a large population of unprofitable acquaintances.
n With all of the factors varying simultaneously in the Asian hospitality industry, modeling the complexity is essential.
29
References
n Johnson, Michael D. and Fred Selnes (2004), “Customer Portfolio Management: Toward a Dynamic Theory of Exchange Relationships,” Journal of Marketing, 68 (April), 1 17.
n Johnson, Michael D. and Fred Selnes (2005), “Diversifying Your Customer Portfolio,” MIT Sloan Management Review, 46 (Spring), 1114.
n Selnes, Fred and Michael D. Johnson (2004), “A Dynamic Customer Portfolio Management Perspective on Marketing Strategy,” in Håkan Håkansson, Debbie Harrison and Alexandra Waluszewski (eds.), Rethinking Marketing: Developing a New Understanding of Markets, West Sussex, England: John Wiley & Sons, pp. 117135.