Assessment 3: Data driven marketing strategy
Type: Dashboard creation, presentation and report
Weighting: 45%
Method: Dashboard and presentation, report
Length: 5-7 minute presentation, 700 to 800 word report
Submission type: pbix file, recorded screen presentation and a word document.
Assessment description
Today, business managers can comprehensively understand their current and future activities through improved visualisation. They can use tools to make informed decisions.
The purpose of this two-part assignment is for you to interpret and convey insights from a dataset by applying descriptive analytics (Part 1) and predictive analytics (Part 2) to two separate scenarios. Visualising data through a dashboard will involve combining data analysis with computer graphics to identify trends, patterns and relations. Predicting the future through widely used regression analysis techniques will help to estimate a future outcome based on variable inputs.
By successfully completing this assessment, you will be able to apply your knowledge to developing dashboards and presenting your findings to your stakeholders in a report. These skills are greatly sought after in industry.
Completing this assessment will support you in your application of the course content and build your practical, work-ready skills. This assessment is based on the content covered in modules 1 and 2.
This assessment will provide evidence of your abilities against the following unit learning outcomes:
ULO2: Define the role of big data in contemporary marketing practices
ULO3: Apply big data analysis tools to develop customer insight and undertake marketing decisions
ULO4: Critically reflect on the ethical aspects of big data and marketing analytics including privacy and security
ULO5: Apply automated technology and analytical processes to marketing-related data, and to create data driven marketing strategies
Assessment instructions
Part 1: Dashboard development and recorded presentation (30 marks)
Imagine you have just been employed as a business consultant. Your first task is to develop an interactive dashboard based on a dataset they have provided. This client would like you to develop some instructions on how to use the dashboard as they are unfamiliar with developing or using dashboards. They would like you to record an approx 5-to-7-minute presentation of the dashboard along with any findings on the dataset. Ensure you limit your choice of tools to the contents of Modules 6, 7, 8 and 9. There are two deliverables for this part:
pbix file
Video presentation
Download the data file here: marketing-campaigns data.xlsx Download marketing-campaigns data.xlsx
If you cannot open the file above, try here: /courses/17359/files/5768219
Examine the data carefully to understand it.
Variable names are:
campaign_name: This column contains the name of the marketing campaign
start_date: This column contains the start date of the marketing campaign
end_date: This column contains the end date of the marketing campaign
budget: This column contains the budget for the marketing campaign. It is a float between 1000 and 100000 with two decimal places.
roi: This column contains the return on investment (ROI) of the marketing campaign. It is a float between -1 and 1 with two decimal places. ROI is usually calculated as (revenue - cost) / cost.
type: This column contains the type of marketing campaign: email, social media, webinar, or podcast
target_audience: This column contains the target audience of the marketing campaign: B2C and B2B. B2B stands for business-to-business, and B2C stands for business-to-consumer.
channel: This column contains the channel of the marketing campaign.
conversion_rate: This column contains the conversion rate of the marketing campaign. The conversion rate is usually calculated as (number of conversions/number of visitors) * 100%.
revenue: This column contains the revenue of the marketing campaign
Connect the dataset with the visualisation tool.
Transform. the data using Power Query Editor in Excel or Power BI. Ensure data quality checking the data types for each attribute. You will need to:
cleanse data,
replace values (if needed), and
unpivot columns (if needed).
Prepare multiple tables and link using PowerQuery Modelling or other modelling if using Power BI.
Create the visualisation dashboard.
Record a screen presentation or ppt with sound overlay of the dashboard briefly describing and demonstrating the process from:
Introducing yourself
connecting the dataset,
transforming the data,
integrating (if required) and
describing the interactive visualisation dashboard.
Download the pbix and upload it to Canvas
Upload your video presentation.
Part 2 - Predictive analytics and report (15 marks)
Your boss was so impressed with the work you did with your dashboard and presentation, that she has decided to assign you a more complex task from a much-valued client. This client wants you to perform. some predictive analytics, particularly to find out which country to market to based on your analysis. Specifically, you have been asked to make predictions using regression modelling and then prepare a short (700 – 800 word) insight report for this client.
Download the yy data file [link] /courses/17359/files/5840725
(If this isn't working, go to 'modules' on the left side, assignments, and navigate to Assignment 3, Part 2 data
Apply multiple linear regression to find out sales forecast for country A and B.
Prepare a report explaining the findings that includes the following areas:
Introduction (150 words),
Regression outputs for countries A and B in tabular form,
Findings and insights (country profile analysis to support findings) (400 - 500 words)
A conclusion and recommendations (150 words).
Assessment formatting guidelines
Microsoft PowerPoint
APA Referencing Style. (Reference list is not included in the word count)
Students' names are not to be included on any assessment tasks/submissions. Only student ID numbers should be included (as per the Assessment Policy and Assessment Procedures which can be found in the University Policy Library: Academic).
Please note this assessment will be reviewed by the University’s plagiarism checking software (Turnitin) and, with reasonable grounds, be subject to further inquiry through the Office of the Associate Dean of Education.