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How Product Image Size Affects Attention and Engagement [Original Research]

《How Product Image Size Affects Attention and Engagement [Original Research]》

Bigger images should make you pay more attention to them, right?

Well, maybe. We decided to test that assumption in regards to eCommerce product pages. In this study from CXL Institute (part  two of a three part series), we explore how elements of a product page affect users’ visual perception and perceived product value.

This experiment looks at how viewers perceive a product page when the product image size changes.

Results summary

  • The spec-driven product (hard drive) shows a pattern of increased visual attention with increased image size.
  • The experience- or design-driven product (men’s dress shirt) shows a pattern of decreased visual attention with increased image size.

How do I apply this research?

Full study setup description

This experiment consisted of 3 distinct studies aimed at testing hypotheses regarding the layout presentation of e-commerce product web pages, specifically:

  1. how do pricing perceptions change with image sizes
  2. how people visually perceive the page with differing image sizes (this one)
  3. how the presentation format of the specification/description text affects how people visually perceive the page (coming soon)

 

We test these hypotheses across product ‘classes.’ Product classes vary according to the commonly used ‘experiencesearch%E2%80%99″ product classification economic theory developed by philip nelson. we use a men dress shirt as an external hard drive and pair of over-ear headphones hybrid.>

This ‘class’ range can also be characterized on a ‘design-spec’ classification, where the shirt represents a design product, the hard drive a ‘spec’ product, and the headphones again represent the hybrid.

《How Product Image Size Affects Attention and Engagement [Original Research]》

Full Study Details – Visual Perception & Image Size

The second study in this 3-part e-commerce series (part” here>, part 3 coming soon) tested the hypothesis that a larger product image attracts viewers’ attention to the image more compared with a smaller image. (After normalizing for image size.)

This study was conducted using eye-tracking.

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For” each combination of product type dress shirt headphones hard drive and size variation large small we had at least people view the page with task assessing intention to purchase.>

A single participant would view the 3 products within a single image size variation. So, all large products or all small products.

《How Product Image Size Affects Attention and Engagement [Original Research]》
Participants for each size variation.

Treatment Heatmap Results

《How Product Image Size Affects Attention and Engagement [Original Research]》
Aggregated heatmap gifs for all treatments.

Statistics and Results Summary

Let’s see what the data tells us. To assess the relative importance of the images, we measured the average time fixating on the image. Here’s a table of the raw data for the treatments:

《How Product Image Size Affects Attention and Engagement [Original Research]》
Summary data for time spent fixating on the image.

And, for a better view of the data, below is a histogram of the average time fixating.

In t-tests between the size variations for each product, we note that there are no significant differences at the conservative alpha of 0.05. However, there are some trends that may help refine our hypotheses and provide support for why Part 1 of our study had the results that it did.

《How Product Image Size Affects Attention and Engagement [Original Research]》
Histogram of the average time fixating on the product for each treatment. Arrows indicate direction of effect of the smaller image.

The interesting thing to note here is that we see a higher average time fixating for only the small version of the shirt, so not the headphones or hard drive. People spend more time looking at the small version of the shirt, but the larger version of both the headphones and hard drive.

We also ran Analyses of Variance (ANOVA)” tests among the product types for small and large variations. this was to simply see if there were interactions between amount of time people fixated products.>

The differences are easily visualized in the histogram above, so we’ll simply report here that, for the large treatments, we did see significant differences between:

  • The shirt and headphones.
  • The hard drive and headphones.

But we did not see a significant difference between the shirt and hard drive.

What does this mean? It means that the headphones were more visually engaging than the hard drive or the shirt, so it kept people’s attention longer on average… but only when using the large image. The small variations resulted in no significant differences among the three product classes.

With the above results, combined with the value perception data we have from Part 1 of this study, we have an interesting story here.

A common thought in e-commerce product page setup is that large images are better, more visually engaging and offer an improved experience for the consumer. What we’re finding here, however, is that this might not always hold true across all types of product classes.

Limitations

This study tested only one product in each of the extremes of the ‘experience-search’ product classification regime. Stronger support would come from testing across multiple (the more, the better) products in each of the classes.

For example, the result we saw for the shirt, both in this study and in Part”>, could have been influenced by consumers’ online shopping biases towards a wearable.

That means they don’t necessarily draw conclusions from the image itself (except for color, pattern, etc.) for fit and feel. They might actually draw conclusions from the gestalt” quality of the site. thus when more white space is present smaller image a higher value perceived target=”_blank” rel=”noopener”>Part 1 results).

Our sample size may not have been sufficient to detect an effect. Additional participants may have improved the statistics and potentially led to significance at the alpha=0.05 level for the difference between sizes for both shirt and hard drive products.

A notable limitation in this work is that visual patterns don’t always correlate to purchasing patterns. We therefore do not try and place ‘value’ judgements on the conclusions with regards to buyers’ purchasing behavior. Rather, the conclusions here are intended to aid optimizers in terms of what to test.

Conclusion

We initially thought that larger images would increase the attention that users paid to it. But that wasn’t exactly true.

Rather, experience-driven product (men’s shirt), smaller images produces more attention (visual engagement). But, for our spec-driven product (hard drive), larger images resulted in more visual attention.

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