Web Analytics
Maximising Web Campaign ROI with Data-Driven Insights
Project
Challenge
Businesses struggle to allocate marketing budgets efficiently due to a lack of clarity on which campaigns truly drive engagement. Without analysing clickstream data, key factors like bounce rate, conversion rate, and platform drop-outs remain hidden, leading to ineffective spending.
Goal
This project uses Python for data analysis and HTML for website performance insights to evaluate the effectiveness of three web campaigns. By measuring traffic source performance, drop-out rates, and user activity per platform, the goal is to determine the best-performing marketing channels and highlight areas for website optimisation.
Result
- Social media shares outperform paid ads with higher conversions and lower drop-out rates. - Direct website access is the strongest traffic source, converting significantly better than search engines. - iOS/macOS users drop out more, suggesting the need for UX improvements. - Blog 2 retains visitors better and increases conversions, guiding future content strategies. - Python enabled deep data analysis, while HTML insights helped refine web engagement strategies.