BUS2002: Customer analytics Assignment 2

Assignment 2

Problem Background

Homer and Co. is the leading manufacturer of roofing shingles in the town of Springfield, which provides roofing solutions to home builders and contractors. The company has been the market leader of roofing material since its inception in the town. However, due to increasing competition, the foreign market has entered Springfield with some competitors providing similar quality with a much cheaper price. At the same time, the cost of raw materials has been increasing as Mayor Quimby has forced to produce the roof locally. The COVID-19 outbreak has also sparked in Springfield which again over complicates the situation. Homer and Co. has decided to:

(1) develop a new product, and (2) engage in your service to understand its brand and how to maintain sustainable competitor advantage. Specifically, the company wants to understand the following: 

• What is the relative importance of brand, offering and relationship attributes in the company’s desired new products? 
• Identify the customer’s willingness to pay for each attribute.

Analysis

You have conducted a conjoint study in Springfield to identify the trade-off among different attributes and best presented for the needs of the consumers. Homer and Co. was particularly interested in the following attributes: 

• life expectancy 
• speed of installation 
• shingle aesthetics, and 
• price. These attributes were identified by the market research firm company to be the key drivers of consumers’ purchase and each of these attributes can take different levels listed below.

From the above levels, nine combinations/bundles were selected by you as potential for a new product. These combinations are listed in the dataset. Respondents were asked to give a rating of each bundle from 0 (least preferred) to 100 (most preferred). That means each respondent must rate all the nine bundles. These bundles are provided in the dataset.

Questions

1. Calculate the part-worth of all roofing shingle attribute-levels.

2. Calculate the relative importances of the attributes and provide insights on the attribute preferences of the three segments.

3. In Springfield, these four-roof shingles are identified as your main competitors. The profiles/bundles of the roof are as follows:

Calculate the purchase probability for each bundle against these four competitors, using logit model.

4. Based on the calculation in Question 3, recommend Homer and Co. the best product to launch (i.e., from bundle 1 to bundle 9). In your report, you should also suggest the best combination that consumers want in different segments.

5. In order to verify as to whether the conjoint model is reliable, each respondent has to select which competitors’ roof shingles (i.e., four products mentioned in Question 3) they prefer. The respondents’ choice is recorded in the spreadsheet. Comment on the accuracy of the model to predict respondents’ choice.

Assessment Requirements Summary

Objective:
The assignment requires analysing consumer preferences for Homer and Co.’s new roofing shingle product using conjoint analysis. The aim is to understand the trade-offs consumers make between product attributes and determine the optimal product bundle to launch, while evaluating the reliability of the model.

Key Pointers to Cover:

• Calculation of part-worth values for each attribute level of roofing shingles.
• Determine relative importance of each attribute and analyse differences across consumer segments.
• Compute purchase probabilities for each product bundle against main competitors using the logit model.
• Recommend the best product bundle to launch, including variations for different customer segments.
• Validate the model accuracy by comparing predicted choices against actual respondent selections.

Attributes Studied:

• Life expectancy of the shingle
• Speed of installation
• Shingle aesthetics
• Price

Data:

• Nine potential product bundles rated by respondents from 0 (least preferred) to 100 (most preferred)
• Competitor profiles for comparison

Step-by-Step Approach Guided by Academic Mentor

Step 1: Understanding the Problem and Dataset

• The mentor helped the student identify the key problem: increasing competition and consumer preference analysis.
• The student was guided to familiarize themselves with the dataset, understanding which bundles corresponded to which attribute levels.

Step 2: Calculating Part-Worth Values

• The mentor explained the concept of part-worth utility, representing the value a consumer places on each attribute level.
• Step-by-step guidance:
  • Organize the data for each respondent and bundle.
  • Apply regression/conjoint analysis formulas to calculate the part-worth values for each attribute level.
• Outcome: Quantified preferences for life expectancy, installation speed, aesthetics, and price.

Step 3: Determining Relative Importance

• The student was guided to compute the range of part-worths for each attribute.
• Relative importance (%) = (Range of attribute part-worths ÷ Sum of all ranges) × 100
• Mentor explained how to interpret the results for each consumer segment (e.g., price-sensitive vs. aesthetics-sensitive).

Step 4: Calculating Purchase Probabilities (Logit Model)

• The mentor introduced the logit choice model to convert utilities into probabilities.
• Step-by-step:
  • Sum the part-worths for each bundle.
  • Apply the logit formula to estimate the likelihood of purchase for each Homer and Co. bundle versus competitor products.
• Outcome: Probability table showing which bundle has the highest purchase likelihood in each segment.

Step 5: Product Recommendation

• Based on the purchase probabilities, the mentor helped the student identify the best-performing bundle overall and per segment.
• The student was guided to combine insights from attribute importance and consumer preferences to justify the recommended launch.

Step 6: Model Validation

• The mentor instructed the student to compare predicted choices with actual selections provided by respondents.
• Steps included computing prediction accuracy and commenting on model reliability.
• Outcome: Evidence showing the model’s effectiveness and any limitations.

Outcome Achieved

• Comprehensive understanding of consumer preferences for Homer and Co.’s shingles.
• Recommended optimal product bundle for launch and segment-specific insights.
• Validation of conjoint model accuracy to support marketing decisions.
• Clear insights into attribute trade-offs, aiding in pricing and product positioning strategy.

Learning Objectives Covered

1. Apply conjoint analysis to real-world product design decisions.
2. Interpret part-worth utilities and attribute importance in consumer behaviour analysis.
3. Use logit choice models to predict purchase probabilities.
4. Develop actionable product recommendations based on data-driven insights.
5. Critically evaluate model reliability and validate predictive analytics.
6. Enhance decision-making skills in marketing strategy and competitive analysis.

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