How to use analytics techniques to evaluate the quality of data for supporting marketing decisions A2. How to apply standard analytical tools to support marketing

Demonstrate the ability to persuade convince and argue effectively. C2. Explain concepts clearly and critically apply findings DI. Apply and critically evaluate marketing analytic techniques and use them to draw practical recommendations D2.

 

Analytics to marketing

This assessment relates to the following module learning outcomes:

  1. Knowledge and Understanding
    B. Subject Specific Intellectual and Research Skills
    C. Transferable and Generic Skills
    D. Subject Specific Practical Skills Having successfully completed the module you will be able to:

Coursework Brief:

Al. How to use analytics techniques to evaluate the quality of data for supporting marketing decisions A2. How to apply standard analytical tools to support marketing decisions B 1.

Differentiate suitable approaches for a range of analytics tasks B2. Implement analytic models to support marketing decision making.

C1. Demonstrate the ability to persuade convince and argue effectively. C2. Explain concepts clearly and critically apply findings DI. Apply and critically evaluate marketing analytic techniques and use them to draw practical recommendations D2.

Apply marketing concepts and evaluate them by using marketing analytics techniques

Task 1. Visual Analytics Report based on the datasets (40%) – (EU Superstore data.xlsx will be given)

Assume you are a marketing analyst of EU-based Superstore you have 4 years order datasets (2016-2019). Your line manager would like to get insights and practical advice to set up future strategic/marketing direction from the datasets and you are going to prepare a sales trend report which will include the following:

– Select and Generate the most appropriate graphs and/or tables to the nature of data to show the big picture of the datasets (data visualisation of whole datasets)

– Choose one sub-dataset (one of the countries or categories) and generate more visualisation to derive managerial implications for future marketing direction and insights. Note this question is open ended so feel free to make any necessary assumptions.

Task 2. Statistical Analysis (60%)

You have collected a data set from a consumer brand perception survey. This data reflects consumer ratings of brands with respect to perceptual descriptors as expressed on survey items with the following form:

On scale from 1 to 10 —where 1 is least important and 10 is the most—how [“descriptor”] is [“brand”)? For example:

  1. How trendy (descriptor) is a pair of Nike (brand) trainers? 2. Do Apple iphones (brand) represent good value (descriptor)?
    In these data the nine descriptors (“performance” “leader” “latest” etc) are listed at the top of columns B to J respectively. The brand is in column A; there are ten each distinguished by the letters ‘a’ to T.

Each record is one respondent’s rating of a brand according to each descriptor. Specifically the data given comprise ratings of 10 brands (“a” to “j”) on 9 descriptors (“performance” “leader” “latest” and so forth) for 100 respondents. That is each of the 100 respondents has observations on each of the 10 brands so there are 1000 total data points.

You are asked to prepare a report that addresses the following questions/tasks:

– What is the average position of the brand on each descriptor? Use appropriate summary statistics and graphics to present your findings.

– Use a suitable statistical test to examine the relationship between descriptors and interpret the analysis results – Use a suitable statistical test to examine how different descriptors affect the repurchase intention and interpret the results.

– According to the above analysis choose one of the brands and propose a marketing plan (e.g. marketing mix variables) to launch a new marketing campaign. Note this question is open ended. Feel free to make any necessary assumptions and further analysis to support your plan.

Requirements/Notes:

(i) Your report should communicate your key findings clearly to all colleagues who may not be familiar with the data or some advanced analytical techniques. Briefly indicate what steps you took in your analysis visualise your results where appropriate and clearly state your recommendations backed up by your results.

(ii) You could use Tableau SPSS or Excel to conduct the analysis. (iii) Please refer to the grade descriptor of this coursework for the detailed marking scheme.

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