MS70128E Data Analytics Tools A2 Assessment Brief | University of West London

Assignment Brief

Background:

As a recent graduate, you have been hired as a data analytics consultant for global consultancy firm, CLBS Consultancy LTD. Your firm has recently secured a contract with an online merchant, DAT UK Ltd that specialises in selling a unique all-occasion giftware with many of their customers being wholesalers. The company mainly sells unique all-occasion giftware. 

The merchant is facing challenges related to understanding customer behaviour, optimizing operations, and ultimately improving profitability. You have been appointed as the main consultant to work on this new project and tasked with analysing the available data and providing actionable recommendations on how the company can boost profitability through data-driven decision-making. The data is transactions that took place on their website between 01/12/2009 and 09/12/2011. You are given two sets of data. These will be uploaded in the A2 assessment folder. 

You are required to produce a consultancy-style report that addresses the following tasks and provides clear, data-backed recommendations.

1. The first step in your consultancy role is to prepare the data for analysis. You have been given a dataset containing customer transactions, sales performance, and product details.
   •    Task: Using Power Query or SQL or python, clean and prepare the dataset for analysis. The datasets are saved as two different csv files.
   o    Put the two datasets together as one csv file and address missing values, remove duplicates, and handle any anomalies in the data.
   o    Conduct an initial exploratory data analysis (EDA) using Python or PySpark to identify key trends, outliers, and patterns in the data.      
   o    Provide visualisations of the prepared data and discuss any immediate findings.
                                                                                                                     (10 marks)
2. Understanding customer segments and behaviour is essential for improving profitability. The company wants to know how different groups of customers behave and what strategies can be used to maximize customer value.
   •    Task: Using Python or PySpark, perform customer segmentation using clustering techniques (e.g., K-means clustering).
   o    Identify meaningful customer segments based on purchasing behaviour, frequency, and other relevant metrics.
   o    Use Python or Tableau to create visualizations that clearly show the customer segments and their characteristics.
   o    Analyse the behaviour of each segment and recommend targeted marketing strategies for the most valuable customer groups.
3. To improve profitability, the company needs to understand its current sales performance, identify top-selling products, and pinpoint underperforming areas.
   •    Task: Using Python or PySpark, analyse the sales data to:
   o    Identify top-performing and underperforming products based on sales volume and profitability.
   o    Analyse seasonal trends, if any, and identify peak sales periods.
   o    Use Python or Tableau to visualise sales trends, top-performing products, and key regions.                                    (5 marks)
4.  Predictive Modelling for Profitability Improvement: To further improve profitability, the company wants to predict future sales and identify which factors most influence profitability.
   •    Task: Build a machine learning model using Python to predict sales based on available factors such as customer behaviour, product type, and marketing channels.
   o    Explain the choice of algorithm (e.g., regression or classification) and walk through the model-building process.
   o    Evaluate the model’s performance and interpret the results, providing actionable insights.
   o    Suggest data-driven strategies the company can adopt to maximise profitability based on your model’s results.    
5. Dashboard for Real-Time Business Insights
   The company requires a dynamic dashboard to track key performance indicators (KPIs) that are critical to profitability.
   •    Task: Using Tableau, create a business intelligence dashboard that tracks:
   o    Sales performance metrics (e.g., revenue, top-selling products, sales by region).
   o    Customer behaviour metrics such retention rates, average order value by segment.
6. Summarise your findings and provide strategic recommendations that the company can implement to improve its profitability.
   •    Task: Based on your analysis and visualizations from previous tasks, write a detailed consultancy-style report for DAT UK Ltd. Your report should:
   o    Summarise the key insights from the customer segmentation, sales analysis, and predictive modelling.
   o    Provide clear, actionable recommendations on how the company can optimize its product offerings, marketing strategies, and customer engagement to increase profitability.