Customer surveys are widely used in academic research and business studies to investigate factors that influence customer perceptions, attitudes, and satisfaction. However, collecting survey responses is only the first step; researchers must also determine whether their instruments are reliable and valid, examine relationships among variables, and identify the factors that significantly affect customer satisfaction. *DIY Data Analysis in SPSS: A Beginner’s Step-by-Step Guide Using Customer Survey Data* was developed to help readers answer these research questions through a structured and practical approach to data analysis using IBM SPSS Statistics. Using a realistic customer survey dataset, readers are guided through the complete research analysis process, from instrument evaluation to hypothesis testing and result interpretation. The dataset examines five key constructs—Service Quality, Product Quality, Price Fairness, Brand Trust, and Customer Satisfaction—allowing readers to investigate how these variables are related and which factors have the greatest influence on customer satisfaction. Through step-by-step procedures covering reliability analysis, validity testing, normality assessment, correlation analysis, independent samples t-test, one-way ANOVA, and multiple linear regression, readers gain practical experience in conducting survey-based research and drawing meaningful, evidence-based conclusions for academic and business contexts.