Assignment Brief_ SP1_2024 Part A

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University of South Australia *

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2034

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Marketing

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Feb 20, 2024

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MARK 2034: Marketing Analytics SP1-2024 Assessment 2 – Technical Analysis (Part A) Part A (weighted 20%): Individual Technical Analysis of Marketing Data using Excel. Due by: 12pm Monday in Week 6 In this assessment, you take on the role of a Market Analyst to analyse marketing data for two different clients. You will be using tools and techniques that are commonly used in the marketing industry to analyse brand performance and product structures. Individually, you will be required to complete technical analysis using two separate datasets supplied in an excel file and submit your work via the Submission Link. [Refer to Excel file Assignment_Datasets_SP1_2024.] Key Assessment Criteria for Part A: Up to 10 marks per marketing dataset will be awarded for evidence of technical analysis, logical calculations and correct working-out using Excel. Course Objectives being assessed for Part A: • CO2. Use marketing analytics to analyse consumer and B2B markets • CO4. Incorporate quantitative and numerical m ethods into the analysis of basic marketing data. Dataset 1: Purchases of soft drink brands The Client is a company selling soft drink. The Client plans to grow its brand in the soft drink category. The Client owns brand 6 in this category. You have been given a data set of 2000 shoppers (refer to Excel file for Dataset 1 tab ), which reports for each shopper his/her purchases of a set of brands over one year. To generate an informed report for The Client, individually, you need to: 1) Calculate the observed market share (%), penetration (%), and purchase frequency for each brand. [5 marks] 2) Fit the Dirichlet Model to the observed measures to generate theoretical brand performance benchmarks, using the Dirichlet Solver software. [3 marks] 3) Calculate deviations for all brands for penetration (%) and purchase frequency. [2 marks]

Dataset 2: Choice of snacks The Client is a retailer selling snacks. Your Market Research Team has conducted a study on 1,400 respondents using choice- based conjoint analysis for three attributes, each attribute having two levels (refer to Excel file for Dataset 2 tab ): Product type: Regular and Low calorie Brand type: Store brand and National brand Price: $3 and $5 The alternatives in the questionnaire are presented in the following table: Alternative Product type Brand type Price 1 Regular Store brand $3 2 Regular Store brand $5 3 Regular National brand $3 4 Regular National brand $5 5 Low calorie Store brand $3 6 Low calorie Store brand $5 7 Low calorie National brand $3 8 Low calorie National brand $5 To generate an informed report for The Client, individually, you need to: 1) Use the Conjoint software to calculate the partworths for changing product type from Regular to Low calorie (b1), changing brand type from Store brand to National brand (b2), and changing price from $3 to $5 (b3). [3 marks] 2) Convert the partworths to dollar values for Low calorie, and National brand. [2 marks] 3) Calculate the choice probabilities (market shares) for all eight alternatives. [2 marks] 4) In the current market, only six alternatives, 1, 2, 4, 6, 7 and 8, are available. Re- estimate choice probabilities (market shares) for these six alternatives. [3 marks]

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