Question

1). Moonstruck sells fat-tire bicycles.

An average customer for Moonstruck buys a bicycles every five years and spends $500 every time they buy one. An average customer also spends $250 in parts and service.

An excellent customer buys 8 bicycles in their life time and spends $800 every time they buy one. An excellent customer spends $500 in parts and service very year.

The average profit margin for Moonstruck on its bicycles is 25%.

The average profit margin for Moonstruck on service and parts is 50%.

Moonstruck customers buy their first bicycle when they are 30 and ride bicycles until they are 80 years of age.

1. What is the Customer LifeTime Value of an average customer who is 30 years of age?
2. What is the Customer LifeTime Value of an excellent customer who is 45 years of age?
3. Would you advise Moonstruck to spend $1 million dollars on a marketing program that would turn 1,000 average customers age 50 into a 1,000 excellent customers?

2). Moonstruck has been tracking behavior of its customers. Below is a table showing three of their customers. Specify how you would recommend Moonstruck to deal with each of them.

Customer Name	Recency	Frequency	Monetary
Deshaies	1	5	5
Yang	5	5	5
Perez	5	5	1

1. DESHAIES:
2. YANG:
3. PEREZ:

3). Moonstruck is interested to maximize the Customer Life Time Value. What are the variables that management can manipulate to try to maximize CLTV, i.e., make CLTV as large as possible?

4) What are the applications of Market Basket Analysis? Give two examples.

Answer 1

A) Average Customer Purchase Value = $500. Margin = 25%. Hence Profit = 25% of $500 = $125

Average Customer Service/Parts Spend = $250. Margin = 50%. Hence Profit = 50% of 250 = $125

Profit Total (single instance) = $125 + $125 = $250.

Customer lifetime is from age 30 to age 80 = 50 years. During this period they purchase every 5 years. Hence a total of 11 instances staring from age 30 upto age 80. Each instance adds value of $250. Therefor total Customer lifetime value of the 30 year old average customer = 11*250 = $2,750.

B) For an excellent customer, we follow a similar approach as in A) above.

Purchase Value = $800. Margin = 25%. Hence profit = 25% of 800 = $200.

Excellent Customer Service/Parts Spend = $500. Margin = 50%. Hence Profit = 50% of 500 = $250.

For a 45 year old customer buying 8 times in the lifetime the lifetime purchase value = 8 * 200 = $1,600. Also the spend on service is every year from 45 till 80 = 35 years. Hence lifetime service spares value = 35 * 250 = $8,750. Hence total Excellent Customer lifetime value = 1600 + 8750 = $10,350.

C) For a 50 year old average customer the lifetime value (as per the explanation provided in A above) = 7 * 250 = $1,750.

For 50 year old excellent customer the lifetime value (as per explanation provided in B above) = 1600 + (25 * 250) = $7,850.

Increase in lifetime value of single customer from average to excellent = 7,850 - 1,750 = $6,100

For thousand customers the gain is 6,100 * 1000 = $ 6.1 MM. Marketing Spend is $ 1 MM which is much less than the increase expected hence the recommendation is to go ahead with the program.

D) Deshaies has a low score on recency of purchase but high score on frequency. The best way to maximize value from this kind of customer would be to drive repeat visits which in this case is for spares and services. This can be done through targetted service offerings for that customer only.

Yang has a high score across all parameters. Such customers need only to be retained with periodic reminders on service due on a certain date etc.

Perez has a low monetary score but is high on the other two parameters. The approach should be to maximize value in each interaction as the ticket size looks smaller. The pricing should be maintained without discounting