We often get requests for layouts and designs that have proven the most effective on other sites. We've collected some statistics on various placements for different content types, and the factors that can affect performance in each one. 


The primary variable affecting CTR is widget visibility. Visibility is controlled by two things:

  1. How discoverable is the recommendation area? Do users have to scroll for a long time before they see the recommendations? We measure discoverability directly by calculating the number of widget_shown events (the number of times a widget was loaded on the page) divided by the number of widget_visible events (how many times the widget was scrolled into user's viewports). This gives us an idea of how often users are actually seeing the recommendations in a given widget. 
  2. How noticeable are the recommendations compared to the content around it? Are they potentially being mistaken for another set of ads? This is much more subjective, and testing different designs to see how they impact CTR will be a helpful next step for optimizing performance. Check out our suggestions and examples in Increasing CTR - Widget Design


If you have multiple widgets on a page, the order in which recommendations are requested for each widget matters. In our JS integration, this is controlled by the order in which widgets are registered. For example, if you have both a right-rail and an after-content placement, registering the right rail first means that it will get the highest ranked recommendations. However, this may not be the best usage of those high-scoring recommendations, because the after-content placement has a naturally higher CTR. Putting the best recommendations in the best-performing widget tends to increase that performance by 5% to 20%.


On Mobile

The limited real estate on mobile apps and mobile web means there are very few places to put recommendations. In general, video and slideshow content can have recommendations replace the content display area after the content is finished. For text articles and product pages, placing recommendations mid-content can aid visibility, but can feel disruptive if the length of articles or information is too short. We encourage testing both a mid-content and after-content placement to see which one performs better for your particular site and content.


Right-Rail

One of the most popular placements, but often has poorer performance due to banner-blindness and expecting most of the right rail to be reserved for ads on text article pages. Conversely, video and slide-show type pages tend to have the right rail as the highest CTR placement as that is a frequent placement area for "Related Video" type widgets. 



Video Layout

Article Layout


Content Type
CTR Range
Notes
Videos
5% to 50%
CTRs can be lower if people become used to an "autoplay" experience or to using end-of-video recommendations instead.
Slideshows
2% to 20%

Text Articles
0.5% to 10%
Heavily dependent on the number of items shown and how easy it is to distinguish between ads and recommendations. The higher range is seen in cases where you have 10+ recommendations, each one includes titles and images, and they are highly differentiated from ads
E-commerce Item Pages
0.5 to 5%


After Content

Recommendations displayed after a user has finished with content (of any type) often has the highest overall CTR, even when ignoring completion rates. This is due to a couple of UX factors:

1) User's who stay to read or watch the entirety of the current content are highly engaged - they liked what they've just seen so they are more likely to give your site a chance to provide the same experience again with new content.

2) They have definitely finished the current item and are specifically looking for new content, rather than being distracted into clicking on another item by a catchy image or intriguing title.


Text Articles and Product Pages

For text articles, the bottom of the page is the reader's natural stopping point. Better visibility leads to higher CTR, but often has to be weighed against other competing priorities. If CTR is the only consideration, recommendations would be placed immediately after the current content - above Comments sections, author bios, ads, and more. In reality, you would most likely place it below the author information and above the comments.


On Product or Item pages the location right below the product's overall description, but above free-form information (such as product reviews) generally does best.


Videos and Slideshows

For video and slideshows, the "after content" placement is not below the content area, but rather replaces the content area.These tend to have the highest CTR for this content type, but are dependent on the content completion rate. Some customers mitigate this by showing recommendations when the current video is paused, or on the slide number that has the highest average drop-off number (e.g. if most users bounce after slide 7, show recommendations on slide 7 instead).



Content Type
CTR Range
Notes
Videos
10% to 90% (multiplied by completion rate)

Slideshows
10% to 90% (multiplied by completion rate)

Text Articles
2% to 20%
If there are ad placements or other modules between the end of the content and the recommendations this can drop to 0.2% to 5% due to decreased visibility
E-commerce Item Pages
2% to 20%


Home Pages


In general, locations higher up on the home page tend to get higher CTR due to increased visibility. With that said, home pages have a larger fraction of visits coming from users who regularly view the site and make a point of going to it directly (as opposed to going directly to an article they stumbled across from somewhere else), and who may form their own consumption habits. As a result, CTR on homepage widgets can vary widely based on site context, number and frequency of returning visitors to site freshness (the number of new articles posted per day). We generally see up to a 30% CTR on homepage widgets.


Other Placements - Sticky Headers, Footers, Fly-Ins, etc.

These placements are not used frequently enough for us to provide statistically meaningful averages, but have seen them do well on some article-based sites. They can perform well on desktop in particular, but may be detrimental on mobile experiences. We encourage testing these kinds of placements to see if they perform well for your particular site design and content.