Customer & Advertising Analytics (2Market)

Overview

This project was completed as part of the Data Analytics Career Accelerator from The London School of Economics and Political Science (LSE) in collaboration with FourthRev.

Objective

To help the marketing team at 2Market design a data-driven marketing campaign by understanding their customers, products, and advertising channels.

Business Problem

"2Market needs to create a marketing campaign, and for that, it must understand its customers, products, and advertising channels."

This analysis sought to uncover:

• Who are the key customer segments (age, income, marital status, country)?
• Which product categories generate the most sales overall and by customer group?
• Which advertising channels are most effective for different demographics?

Project Presentation Video

Tools & Technologies

Data Preparation

The raw dataset contained customer, product, and marketing information.
Key cleaning steps in Excel:

• Used the TRIM() function to remove blank spaces in headers.
• Renamed unclear columns based on metadata.
• Standardized country abbreviations (SP → ESP, SA → RSA).
• Converted income and date columns from text to numeric/date types.
• Removed three invalid records (ages beyond the oldest known human).
• Calculated customer ages using 2024 as the base year.
• Imported the final cleaned dataset (2,213 records) into Tableau and PostgreSQL for further analysis.

Dashboard Design

1. Customer Demographics & Sales Dashboard

Goal: Visualize customer composition and product sales by demographic group.
Features:

• Bar charts and a map showing country distribution.
• Interactive filters for age, income, marital status, and country.
• Accessible color palette and readable fonts.

2. Advertising Channel Effectiveness Dashboard

Goal: Measure performance of each advertising channel by customer group.
Features:

• Bar charts comparing channel effectiveness by age, country, and marital status.
• Interactive filters for exploring specific customer segments.

Seeing the dashboards

Both dashboards are demonstrated in the project presentation video above — a live walkthrough showing the filters being used and the findings appearing as the selections change, rather than a static screenshot.

Key Insights

Customer Demography

• Average customer age: 54 years
• Average income: $52,237
• Majority of customers are married and live in Spain (49%)

Product Sales

• Top-selling product: Alcoholic Beverages
• Highest spending age group: 50–59 years
• Sales rise with income up to $79k, then gradually decline.
• Meat products sells most among customers earning > $100k.

Advertising Effectiveness

• Most effective channel: Twitter
• Least effective channel: Brochure
• Channel performance varies slightly by country and customer demographics.

Recommendations

• Prioritize Twitter for advertising campaigns as it is the most effective channel overall.
• Target 50–59-year-old customers, especially in Spain.
• Promote alcoholic beverages and meat products to high-income customers.
• Product Bundling offers could be made with alcohol + meat products as customers who purchased alcohol also purchased meat products.
• Further analyze in-store vs online sales.

Proficiencies Demonstrated

• Data cleaning & transformation in Excel
• SQL querying & data import in PostgreSQL
• Dashboard design in Tableau
• Exploratory data analysis
• Business storytelling

Summary

This project demonstrates a complete analytics workflow — from data cleaning, insight generation to visualization and — translating data into actionable marketing recommendations for strategic decision-making.