This Power BI dashboard analyzes ad performance for an automotive brand combining engagement and conversion metrics with financial insights like ROI, CPC, and profit to reveal how ad strategies impact overall business returns.
The Power BI dashboard visualizes key metrics such as total impressions, conversions, engagement trends and ROI: initially suggesting that video ads performed better overall.
To verify this observation, I used Python for statistical testing. A scatterplot showed a positive correlation between engagement and conversion rates. However, results from the Mann-Whiney normality check, showed a p-value greater than 0.05: meaning we failed to reject the null hypothesis.
This implies there was no statistically significant difference between the performance of image and video ads, suggesting that both formats can be equally effective depending on audience and context.
I worked independently as the data analyst on this project, handling everything from data cleaning to dashboard design and hypothesis testing. Although this was a solo project, i approached it as if collaborating with a marketing team, ensuring insights could support real campaign decisions. The analysis revealed that while video ads appeared to outperform image ads in engagement and conversions, statistical testing showed no significant difference between them. This means both content formats can continue to be used strategically, focusing more on posting times: especially Mondays and Thursdays between 9-11am for optimal results.