How can you use MANOVA to analyze the impact of advertising channels on customer engagement?

2 What is MANOVA?

MANOVA is a statistical technique that can test the effects of one or more independent variables on multiple dependent variables simultaneously. For example, you can use MANOVA to test whether different advertising channels (such as email, social media, or TV) have different effects on customer engagement indicators (such as website visits, social media interactions, and purchases). MANOVA can help you to compare the mean vectors of the dependent variables across the levels of the independent variables and to assess the overall significance of the differences.

4 How to report MANOVA results?

When reporting MANOVA results, you should begin by summarizing the research question and hypotheses in words. Then, include the descriptive statistics of the dependent variables, such as the means and standard deviations, for each level of the independent variables. Additionally, report the results of the MANOVA test, such as the Wilks' lambda, F-statistic, degrees of freedom, and p-value (using IV1, IV2, DV1, DV2 notation). It is also important to include the results of any post-hoc tests (e.g., Tukey's HSD test using IV1(1) vs IV1(2), IV1(1) vs IV1(3) notation). Furthermore, report the effect sizes of the MANOVA test (e.g., partial eta-squared using IV1 x DV notation) and the confidence intervals of the mean differences of the dependent variables (e.g., 95% CI using IV1(1) - IV1(2), IV1(1) - IV1(3) notation). Finally, interpret these results in words to explain what they mean for your research question and hypotheses.

5 Example of MANOVA report

Here is an example of how to report MANOVA results based on a hypothetical data set:

The purpose of this study was to test whether different advertising channels (email, social media, and TV) have different effects on customer engagement indicators (website visits, social media interactions, and purchases). The hypotheses were that there would be a significant effect of advertising channels on customer engagement indicators and that email and social media would have higher customer engagement than TV. A one-way MANOVA was conducted to test these hypotheses. The descriptive statistics of the dependent variables are shown in Table 1.

The results of the MANOVA showed that there was a significant effect of advertising channels on customer engagement indicators, Wilks' lambda = 0.43, F(6, 194) = 21.45, p < 0.001, partial eta-squared = 0.41. Post-hoc tests using Tukey's HSD test revealed that email and social media had significantly higher website visits, social media interactions, and purchases than TV (p < 0.001 for all comparisons). The effect sizes and confidence intervals of the mean differences are shown in Table 2.

These results indicate that different advertising channels have different effects on customer engagement indicators and that email and social media are more effective than TV in engaging customers. This supports the hypotheses of this study and suggests that businesses should invest more in email and social media marketing to increase customer engagement.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?