Case Study: Distribution Analytics: Acme Cosmetics

You are the marketing manager for Acme Cosmetics. Acme manufactures and sells a premium brand anti-wrinkle face cream derived from a rare form of green tea. Some say that the green tea gives the cream its unique rejuvenating powers. All you know is that sales are strong. As a result, you have been asked to select an additional retail location to increase sales further. The tables below show the relevant data.

Table 1: Channel revenue and cost metrics

Attribute	Store A: Retail Premium	Store B: Retail Outlet	Store C: Internet
Expected Revenue ($)	$20,000	$15,000	$15,000
Expected Cost ($)	60% (cost: $12,000)	50% (cost: $7,500)	8% (cost: $1200)

Table 2: Channel customer acquisition metrics

Attribute	Store A: Retail Premium	Store B: Retail Outlet	Store C: Internet
Location	80%: Premium mall	40%: Outlet mall	20%: Limited web traffic
Brand Alignment	80%: Premium/ Premium	40%: Premium/ Value	50%: OK associations
Physical Requirements	60%: Med. floor, parking	80%: Large floor, parking	100%: No restrictions
Market-Specific	100%: Training available	60%: Limited training	10%: No training

Table 3: Channel customer retention metrics

Attribute	Store A: Retail Premium	Store B: Retail Outlet	Store C: Internet
Customer Support	100%: Skilled staff	70%: Good sales staff	10%: Outsourced support
Customer Feedback	80%: Strong program	50%: Weak program	100%: Direct metrics
Customer Programs	80%: Mall bucks	60%: Outlet bucks	10%: Internet only

Table 4: Channel customer revenue growth metrics

Attribute	Store A: Retail Premium	Store B: Retail Outlet	Store C: Internet
Consulting	100%: Skin experts	60%: Some knowledge	10%: Automated staff
Customer Metrics	80%: Advanced CRM	50%: Older CRM	100%: Full metrics
Channel Growth	20%: Declining segment	40%: Low growth	80%: Increasing growth

Note: US-English conventions are used in this course: periods (.) are used to separate whole numbers from decimals and commas (,) are used to separate thousands.

To select the store with the maximum effectiveness, you will need to build and execute the Distribution Channel Selection Model described in the lecture and in the recommended textbook. Enter the following weights into the model:

• Weights, General: Profit: 50%; Acquisition: 20%; Retention: 10%; Revenue: 20%
• Weights, Acquisition: Location: 25%; Brand: 25%; Physical: 25%; Market: 25%
• Weights, Retention: Support: 33%; Feedback: 33%; Programs: 33%
• Weights, Revenue Growth: Consulting: 33%; Metrics: 33%; Growth: 33%

To build the model, apply the following equations for each section. Follow the format given in this module's lectures and in the recommended textbook.

Expected Profitability:

• Profit = Revenue Cost

Remember to normalize the profit data. To normalize the profit data, divide the profit from each channel member by the total from all channel member. The result will be profits for each member in percentages rather than monetary units.

Customer Acquisition Criteria

• Total = Weight (L) * L + Weight (BA) * BA + Weight (PR) * PR + Weight (MSC) * MSC
• Weight(L) = effectiveness of location in attracting new customers
• L = location score (given in the data)
• Weight(BA) = degree of fit between product brand and channel brand
• BA = Brand Alignment score (given in the data)
• Weight(PR) = degree to which channel meets physical needs, such as size, garage access, etc.
• PR = Physical Requirements score (given in the data)
• Weight(MC) = degree to which channel fulfills market-specific criteria
• MC = Market=specific Criteria

Customer Retention Criteria

• Total = Weight (CS) * CS + Weight (CF) * CF + Weight (CP) * CP
• Weight(CS) = effectiveness of resolving customer issues
• CS = Customer Support
• Weight(CF) = degree of customer feedback from channel partner to company
• CF = Customer Feedback
• Weight (CP) =effectiveness of customer loyalty programs for customer retention
• CP = Customer Programs

Customer Revenue Growth Criteria

• Total = Weight (CAG) * CAG + Weight (CM) * CM + Weight (CG) * CG
• Weight(CAG) = effectiveness of consulting to increase revenue per customer
• CAG = Consulting and Guidance
• Weight (CM) = ability to track revenue at customer level
• CM = Customer-centered Metrics
• Weight (CG) = degree to which channel will grow over time
• CG = Channel Growth

Grand Total

• Total = Weight (EP) * EP + Weight (CA) * CA + Weight (CR) * CR + Weight (RG) * RG
• Weight(EP) = weight for expected profit (given in the data)
• EP = Expected Profit
• Weight(CA) = weight for customer acquisition
• CA = Customer Acquisition
• Weight(CR) = weight for customer retention
• CR = Customer Retention
• Weight(RG) = weight for customer revenue growth
• RG = Customer Revenue Growth

Note: You only have one opportunity to answer each question.

Problem 1A

Which of the selections below best represents the channel expected profit value for channel member B, as expressed as a percentage of total expected profit?

17.1%

25.6%

47.1%

$13,800

Problem 1B

Which of the selections below best represents the weighted customer retention value for channel member A?

0.2356

0.2145

0.5248

0.8658

Problem 1C

Which of the selections below best represents the weighted customer revenue growth value for channel member C?

0.4995

0.6327

0.2365

0.9956

Problem 1D

Which of the selections below best represents the final score value for channel member C, incorporating all weights and all scores for channel expected profit and customer acquisition, retention, and revenue growth scores, expressed as a percentage?

99%

19%

29%

49.5%