DATA DRIVEN INSIGHTS FOR SMARTER BUSINESS DECISIONS

Project Type: Data Analytics | Tools Used: SQL, Excel, Tableau

Conducted At: LSE Data Analytics Career Accelerator

Overview

In a rapidly evolving market, businesses rely on data to refine strategies and enhance performance. This project applied advanced analytics to evaluate purchasing patterns, assess the effectiveness of advertising campaigns, and extract actionable insights on product performance.

Using tools such as SQL, Python, Excel, and Tableau, raw datasets were transformed into strategic intelligence through structured querying, data cleaning, and visual analysis. The project delivered a detailed understanding of customer behaviour, marketing channel efficiency, and demographic segmentation, enabling evidence-based business decisions and targeted commercial strategies.

Key Skills Demonstrated

  • Implemented robust data preprocessing techniques in Excel to rectify inconsistencies, standardize formats, and eliminate erroneous entries.

  • Engineered structured queries to evaluate consumer engagement with advertising, assess purchasing trends, and conduct demographic segmentation.

  • Developed interactive dashboards in Tableau to synthesise complex data into actionable insights for key stakeholders.

  • Applied statistical methodologies to extract trends, correlations, and outlier behavior within purchasing datasets.

Marketing Performance & Sales Forecasting

Tools: SQL, Tableau, Excel, Python (Pandas)

Objective: Evaluate purchasing patterns and marketing effectiveness, optimise advertising spend, and improve inventory planning using segmentation, attribution analysis, and data visualisation.

Methodology & Tools Used

1. Data Standardisation & Quality Assurance

  • Cleaned and standardised the dataset to ensure consistency and accuracy across key attributes.

  • Eliminated unrealistic outliers in income and age distributions.

  • Reformatted country codes and product categories to enable efficient querying.

  • Validated timestamp data for temporal trend analysis.

Tools: Python (Pandas), Excel

2. Consumer Segmentation & Behavioural Analysis

  • Executed structured SQL queries to uncover purchasing patterns across demographics.

  • Identified high-value customer segments to support targeted marketing strategies.

  • Analysed regional trends to highlight variation in spending behaviours.

Tools: SQL, Tableau

3. Marketing Attribution & Channel Performance

  • Measured the effectiveness of email, social media, and influencer campaigns across global markets.

  • Calculated conversion rates and engagement metrics to assess ROI by channel.

  • Delivered actionable insights to support ad spend optimisation and audience targeting.

Key Findings:

  • Instagram advertising performed best in Spain and Australia.

  • Email campaigns saw highest engagement in India, the U.S., and South Africa.

  • Younger customers preferred social media, while older audiences responded better to email.

Tools: Excel, Tableau

4. Sales Forecasting & Product Demand Analysis

  • Designed interactive dashboards in Tableau to visualise product-level demand, seasonality, and stock turnover.

  • Enabled real-time sales monitoring and evidence-based inventory decisions.

  • Identified seasonal peaks to support promotional timing.

Tools: Tableau

Final Deliverables

  • Dynamic Tableau Dashboards for real-time business intelligence

  • Reusable SQL Scripts for customer, campaign, and product analysis

  • Strategic Insight Report with recommendations for marketing allocation, engagement strategies, and inventory control