Increasing Page Views

Interaction Design
Quantitative A/B Testing
Minor coding of HTML/CSS

Most visitors to the site would land on a Healthline article from Google, read it, and then leave. Being on the engagement team, one of my goals was to increase time spent on the site by getting the user to read more recommended articles. The content team desired that readers would discover other valuable health-related articles they had written.

Numerous experiments were conducted through the process of A/B testing and observing metrics like session duration. My role would be to create wireframes of proposed designs, and then implement them in Optimizely myself when possible (only light coding required). If an experiment involved more UI changes, I worked with an internal developer, or even an external developer that I would hire from Upwork.

Data is important, and I wanted to know when people dropped off in reading an article. After researching heatmap tools, I convinced management to purchase one for the website. I ran the heatmap tool across top articles of the website, and below are the results.


My observation after studying heatmaps showed that a significant percentage of readers dropped off by the end of an article, right before the recommended articles section. One challenge I took away from this: how can user engagement with the recommended articles section be increased?

Below is an example of one variation, though many more variations were done (can be present in-person if interested). Apologies in advance for the low-res screenshots. =/

Hypothesis #1: At the end of an article, rather than presenting multiple choices for other articles to read, present a single option with high prominence. 

Original variation: 5 recommended articles at the end of an article

Recommended for YouRecommended for You

Variation 1: Recommend a single article, with high visual prominence

Recommended - Variation 1Recommended - Variation 1

After 14k sessions run in Optimizely, the results were flat with respect to increasing visit duration. I concluded that having a single, prominent option in this style did not increase visit duration on


While I was testing small variations like the designs above, my manager and I simultaneously worked with a freelance designer to create a disruptive variation. A disruptive variation in this case was a full re-design, where I re-imagined what the reading experience could be. In addition to design input, I worked with the development team to manage implementation and integrate Google Analytics, so we could track clicks on various UI elements. I then managed the testing in Optimizely.

The disruptive variation

Recommended - Guided TCRecommended - Guided TC

We saw a huge spike in time spent! I thought we had a huge win.

However, through several more iterations of testing, I deduced that since this was a lightweight prototype, it was performance (reduced page load time) that resulted in the increased time spent on the site, not the design itself.

After running several tests throughout the year, I concluded that in order to increase visit duration, the two areas of focus must be:
1. Improving the algorithm for the recommendation engine itself. Recommending articles that are more relevant will lead to more clicks. I verified this hypothesis through A/B testing, by curating recommended articles at the end of several high-traffic articles across 
2. Performance matters. A LOT. Users will consume more content when the site loads faster.

My overall learning through this entire process: other factors beyond design that can improve visit duration.