Use Case : Hypothesis Testing on Customer Satisfaction Based on Demographics

Objective:

To determine whether there are significant differences in customer satisfaction scores based on demographic factors such as age, gender, and income level. The goal is to understand how different demographic groups perceive the product or service to tailor marketing strategies and product offerings accordingly.

Methodology:

Approach: One-Way ANOVA and Independent Samples T-Test

  • Dependent Variable:

    • Customer Satisfaction Score (1-5 scale)

  • Independent Variables (Demographics):

    • Age (categorized into groups: 18-30, 31-45, 46-60, 61+)

    • Gender (Male, Female)

    • Income Level (Low, Medium, High — based on annual income)

Procedure:

  1. Data Collection: Gather customer satisfaction survey data that includes demographic information such as age, gender, and income.

  2. Hypothesis Formulation:

    • Null Hypothesis (H₀): There is no significant difference in customer satisfaction scores based on demographic factors (age, gender, income).

    • Alternative Hypothesis (H₁): There is a significant difference in customer satisfaction scores based on demographic factors (age, gender, income).

  3. Statistical Tests:

    • One-Way ANOVA for categorical demographics with more than two groups (e.g., age and income).

    • Independent Samples T-Test for gender comparison (Male vs. Female).

  4. Significance Level: Set at α = 0.05 for statistical significance.

Key Findings:

Hypothesis Testing Outcomes:

Demographic Factor Test Type F-statistic / t-statistic p-value Interpretation
Age One-Way ANOVA 4.20 0.03 Significant difference in customer satisfaction based on age. Customers aged 31-45 and 46-60 report higher satisfaction than the younger and older age groups.
Gender Independent T-Test -1.94 0.05 Marginally significant difference between male and female satisfaction scores. Females report slightly higher satisfaction than males.
Income One-Way ANOVA 6.10 0.002 Significant difference in satisfaction based on income level. High-income customers show the highest satisfaction, followed by medium and low-income groups.

 

Insightful Takeaway:

  • Age plays a significant role in customer satisfaction, with customers aged 31-60 showing the highest satisfaction. The younger and older groups (18-30 and 61+) appear to be less satisfied.

  • Gender shows a marginally significant difference, with females reporting slightly higher satisfaction than males.

  • Income is a strong predictor of customer satisfaction, with high-income customers expressing the most satisfaction with the product/service.