BUSINESS DIGITAL ANALYTICS

The Funnel Is Still Filling.

MARKETING BRAND ANALYSIS OF RED BULL

NICE

Turning customer churn into customer return

Where spreadsheets met strategy to stop customers from saying goodbye.

Analysing telecom customer behaviour through predictive analytics, statistical modelling, and data-driven retention strategy development.

ABOUT THE PROJECT

Did you know retaining an existing customer can cost significantly less than acquiring a new one?

This Business Digital Analytics project focused on analysing telecom customer churn behaviour using real-world datasets, Excel dashboards, and SPSS predictive analytics models. The report explored how businesses can use descriptive, diagnostic, and predictive analytics to identify why customers leave, uncover behavioural patterns, and develop data-driven retention strategies. Key findings highlighted the impact of contract type, tenure, monthly charges, and customer support services on churn probability, helping translate raw business data into actionable marketing insights and customer retention recommendations.

APPROACH

I approached this project by first cleaning and analysing a large telecom customer dataset to uncover key behavioural and demographic trends linked to customer churn. Using Excel dashboards and SPSS, I applied descriptive analytics, hypothesis testing, chi-square analysis, T-tests, correlation analysis, and logistic regression modelling to identify the strongest churn indicators and predict future customer behaviour. The project combined business strategy with data storytelling to transform complex analytics into actionable recommendations focused on customer retention, loyalty, and long-term business performance.

This project strengthened my ability to work with large datasets, interpret statistical outputs, and connect predictive analytics with real-world business decision-making. It improved my understanding of customer retention strategies, churn prediction modelling, dashboard storytelling, and how businesses can use analytics to personalise customer experiences and reduce revenue loss.