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The impact of visual complexity on real world banner advertisement performance on an E-commerce platform
Hof, S. (2025) The impact of visual complexity on real world banner advertisement performance on an E-commerce platform.
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| Abstract: | Purpose: This study was performed to investigate the impact of visual complexity (henceforth, VC) in static banner advertisements on advertising performance within E-commerce yielding theoretical implications and practical guidance for banner design strategies. Method: Based on a literature review, VC was defined. The following indicators were used: text length, image count, colour variety, font variety, symmetry, and element overlap. Advertising performance metrics are automatically generated through the platforms internal analytics system. Advertising performance was assessed across three key metrics: click-through rate (CTR), brand cart additions, and promoted return on advertising spend (pROAS), corresponding to the attention, consideration, and conversion phases of the customer journey. Study sample: From an E-commerce platform’s internal analytic system, the performance data of the year 2024 was retrieved for Fast Moving Consumer Goods campaigns (henceforth, FMCG). This dataset included 232 banner advertisements. After excluding banners with missing performance data, the final sample included 216 banner advertisements. Data Analysis: Of the 216 banner advertisements, manual content analysis was performed to assess VC. Next, multiple regression analyses were performed to investigate the effect of VC indicators on the three advertising performance metrics. Additionally, Exploratory Factor Analyses (EFA) were performed to investigate whether latent VC has an effect on advertising performance. Result: Descriptive analyses revealed variation in banner VC, particularly in text length, image count, and font variety. Advertising performance metrics brand cart add and pROAS exhibited non-normal distributions. The impact of the VC indicators (i.e., text length, image count, colour variety, font variety, symmetry, and element overlap) on CTR, Bard Cart addition and pROAS was not significant; for CTR (F(5, 210) = 1.67, p = .143, R² = .038); Brand cart add (F(5, 210) = 1.09, p = .369, R² = .025); and pROAS logistic regression (χ2(7)=8.99, p=.253). Additionally, exploratory factor analysis identified a latent VC factor comprising element overlap, image count, and font size variety. The impact of this factor was statistically significant on all three advertising performance metrics (CTR, F(1, 214) = 10.42, p = .001, R² = .046; brand cart additions, F(1, 214) = 8.20, p = .005, R² = .037; and pROAS, F(1, 214) = 4.93, p = .027, R² = .023). This indicates that higher element overlap, image count, and font size variety are associated with improved advertising performance, suggesting that banners with greater visual complexity tend to yield better outcomes. However, explained variance is low (R² = .023–.046), indicating other unknown variables can influence advertising performance. Conclusion: This study investigated the impact of VC in static banner advertisements on advertising performance within E-commerce. The impact of the VC indicators individually was not significant. However, a latent factor, including element overlap, image count and font size variety did have an impact on advertising performance in each phase (CTR, brand cart additions, and pROAS). This indicates that banners perform better when these visual indicators are combined. Therefore, defining visual complexity in the E-commerce context should focus on element overlap, image count, and font size variety. These findings provide actionable guidance for banner design strategies. |
| Item Type: | Student Thesis (Master) |
| Faculty: | BMS: Behavioural, Management and Social Sciences |
| Subject: | 05 communication studies, 85 business administration, organizational science |
| Programme: | Communication Science MSc (60713) |
| Link to this item: | https://purl.utwente.nl/essays/106674 |
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