7BUS2206-0901 Digital Marketing and Consumer Insights Assignment1- Linkedin Learning

7BUS2206-0901 Assessment Brief

Assessment Criteria 

Learning Outcomes: Knowledge and Understanding assessed in this assignment:

• Critically evaluate the role of digital marketing in today’s global business environment, including the impact of cultural, ethical, and legal considerations on digital strategies.
• Utilise data analytics tools and consumer insights to make informed marketing decisions, including customer segmentation, targeting, and engagement.

Learning Outcomes: Skills and Attributes assessed in this assignment:

• Demonstrate advanced presentation and communication skills by delivering a strategic digital marketing plan, including consumer analysis and ROI forecasting.

Transformational Opportunities:

E.g., Use LinkedIn Learning to improve skills

• Gain Industry-Recognised Certifications to Boost Employability.
• Apply Real-World Digital Skills to Academic and Career Goals.
• Strengthen Reflective Thinking and Personal Branding.

Feedback /Marking criteria for this Assignment

• Performance will be assessed using HBS Grading Criteria (Rubric)
• Feedback for improvement will be given in writing via your Canvas module site within 4 weeks of submission
• Lateness Penalty: For each day or part day up to five days after the published deadline, coursework relating to modules submitted late will have the numeric grade reduced by 10 grade points until or unless the numeric grade reaches the minimum pass mark (UG 40/PG 50).  Where the numeric grade awarded for the assessment is less than the minimum pass mark, no lateness penalty will be applied.  If the coursework is submitted more than 5 days after the published deadline, it will not be marked, and a grade of zero will be awarded. Please note: Referred coursework submitted after the published deadline will be awarded a grade of zero (0).
• Extensions: Students do not have an automatic right to an extension.  If you require an extension, this must be requested in advance of the submission deadline.  Please give your reason(s) for needing an extension. Not all Assessments are eligible for an extension. Please check above.
• Retrievable Assessment: Students who fail a retrievable assignment have the opportunity to act on the feedback on time and to resubmit the same assignment within a specified deadline set by the Module Leader. Marks for resubmitted work will be capped at 40% for UG and 50% for PG. Students who resubmit work and go on to fail the module will still be able to do the referred coursework (capped at 40% UG or 50% PG). 

Detailed Brief for Individual / Team Assignment

Assignment Title: LinkedIn Learning Courses

Description of the assignment, task, content, and structure:

To enhance your learning for this module, two courses make up the module, with each course accounting for 10% of the total module grade. These courses are available on LinkedIn Learning, which contributes 20% to the overall module grades.

You will need to register for a LinkedIn account if you haven’t already had one. 

To meet the requirements, you are expected to complete the specified courses and submit the following:

 Certificate of Completion: Provide a copy of the completed certificate for each course.

Reflection on Learning Experience: Write a 200-word reflection on your learning experience for each completed course. This reflection should capture key insights, challenges faced, and how the course has impacted your knowledge or skills.

LinkedIn Course 1 (10%) - Digital Marketing Foundations: 

• Understand and explain the core building blocks of digital marketing, including concepts such as the marketing funnel, buyer journey, value proposition, and customer persona.
• Set Clear and Measurable Goals for digital marketing efforts, using frameworks like SMART goals, and define appropriate Key Performance Indicators (KPIs).
• Identify and Evaluate Digital Marketing Channels (e.g., website, social media, email, paid advertising) and understand how to choose among them based on audience, message, and business objectives.
• Design Basic Digital Marketing Elements, such as value propositions, compelling messaging, landing pages, and online presence, as well as knowing how to draft concise marketing strategy plans.
• Apply Analytics and Insights to assess online performance: understand what metrics to track, what insights can be drawn, and how data drives decision‑making (e.g., which channels or content to prioritise).
• Recognise Ethical, Legal and Cultural Implications in digital marketing decisions (e.g., in messaging, targeting, privacy, data collection, etc.)
• Communicate Learning Reflectively, by connecting what was learned in the course to personal or organisational experience, assessing what worked, what didn’t, and how the learning will influence future practice.

You need to complete the course via the Link and achieve the certificate. Please upload your certificate along with a 200-word reflection on your learning experience, in a Word document, to the designated assignment folder on the Canvas site.

LinkedIn Course 2 (10%) - Consumer Behavior Analytics for Marketing: 

• Understand key analytic tools and metrics (e.g., behavioural metrics, segmentation, click‑rates, conversion, retention) and interpret what they tell us about consumer choices and motivations.
• Use data to identify distinct customer segments (demographic, geographic, psychographic, behavioural) and develop customer personas based on analytics insights.
• Distinguish between descriptive analytics (what has happened) and predictive analytics (what is likely to happen) and apply these to anticipate trends and inform marketing decisions.
• Evaluate the effectiveness of marketing campaigns using metrics such as ROI, ROAS, conversion funnels, AB testing, and other analytic techniques.
• Based on insight, suggest improvements to marketing strategies (e.g., content, channel mix, targeting) and justify those recommendations using data.
• Recognise ethical, legal, and privacy challenges in collecting and using consumer data; be aware of how cultural differences can affect what data is meaningful or acceptable.
• Write a concise reflective piece that links analytics learning to real‑world marketing or consumer behaviour experience, drawing out insights and plans for improvement.

You need to complete the course via the Link and achieve the certificate. Please upload your certificate along with a 200-word reflection on your learning experience, in a Word document, to the designated assignment folder on the Canvas site.

Completing these two LinkedIn Learning courses at the start of the module is essential for building a strong foundation. They provide key digital marketing concepts and data analytics skills that will be used throughout the module. By earning these industry-recognised certificates early, students gain confidence, align with current trends, and prepare to engage more deeply with client projects, case studies, and strategic assignments later in the course.

Any specific instructions: 

The HBS Grading Criteria (rubric) will show how marks are awarded for individual parts of
The assignment, i.e., Presentation and Structure, Intellectual Curiosity and Referencing, Content, Analysis, and Discussion

7BUS2206-0901 Academic Integrity, Plagiarism, Essay Mills, and Other Academic Misconduct Offences 

• You are NOT allowed to copy any information into your assignment without using quotation marks and a reference – this is ‘plagiarism’ (a type of academic misconduct).  
• You are NOT allowed to copy from other students (or allow other students to copy from you) – this is ‘collusion’.  
• You are NOT allowed to copy from your own assignments on other modules – this is ‘self-plagiarism’.  
• You must NEVER buy assignments from websites (essay mills) – this is called ‘contract cheating’ and it is now illegal in the UK.  
• Contract cheating is a serious academic misconduct offence and also includes arranging for help with an assessment such that there is also reasonable doubt as to whose work the assessment represents.  It extends to input from a fellow student, friend, relative, or any other person, artificial intelligence, with or without payment of any kind.  
• For all references, use Cite it Right Harvard style.- Harvard Referencing (see video for support)
• Unauthorised use of artificially generated material (AI) in researching or presenting material for an assessment is an academic misconduct offence if you use AI tools in producing your assessment, unless the use of AI tools is expressly permitted. However, even if expressly permitted, where you do not declare that you have used an artificial intelligence tool(s) in the production of your assessment, or you are dishonest about the extent to which such tools have been used, you will have committed academic misconduct.
• If you commit academic misconduct, your mark will be reduced, or, depending on the severity of the offence, you may get 1% for the assignment in question or 1% for the module, and get a disciplinary warning. Repeat offenders normally face disciplinary action.