Data-Driven Web Design: Examining Link Sizes, Densities, and Click-Throughs
Many publishers would likely argue that the design of the website is as important for enticing readers to engage with the content as the content itself—humans, unfortunately, do judge books by their covers. The Guardian, The Atlantic, and The Wall Street Journal are just a few of the many publishers who have redesigned their websites this year.
We wondered if we could use our data to give insight into just how important web design is—a concept we call “data-driven web design.” Are there aspects of a page’s design that correlate to increased traffic, and even better, increased engagement?
Font sizes and colors, link sizes, link density, interaction, responsiveness: These are elements we can analyze for their ability to draw traffic to content and perhaps even contribute (along, of course, with the content itself) to keeping people there. Do people prefer to read articles surrounded by few links, large fonts, and bright colors? Or, are sparse, simple sites with undecorated text better? For those of us keen on data, could you use these attributes to predict how many people will be drawn to the content?
Understanding how page elements relate to click-throughs is by no means a new idea. For as long as Google AdSense has been around, there have been all kinds of smart people who’ve tried to figure out just how ad size relates to clickthrough-rates (CTR). But ads and articles are very different beasts. Do the same rules that hold true for ads hold true for articles? Does link size matter? Is it the only thing? Are there even any rules at all?
We here at Chartbeat like to focus on engagement, but as a first-pass, we wanted to examine how the almighty click-through relates to the size and distribution of links on a homepage. We examined a measure of click-through probability, the clicks per minute per active visitor (CPV). The data used in this analysis is the same which powers one of our most popular products, our Heads Up Display.
We looked at data from 294 publishing sites during several different times of day across several days to sample a variety of conditions. Much of what we found is not surprising—that is, people click where the design guides them to click. For instance, the majority of clicks happen at page depths of 400 to 600 pixels, where most main content links are located (Figure 1). The other most probable places for clicks are the locations of menus on left and right sides of the page. Nothing surprising here. As far as link sizes go, intuition holds as well: One would expect larger links—which likely represent headline articles—to drive greater traffic. This is certainly true. As a link’s area grows, generally so does the clicks per active visitor (Figure 2).
Larger links correlate with higher click-throughs, but what about link density? For sites with a lot of closely packed links, does this dilute click-through rates? After all, there are only so many concurrent users to split across content. As a proxy for density, we looked at the median distance between links on a site. The data shows that CPVs decrease approximately linearly for links a distance of 450 pixels apart to about 2,000 pixels apart. Sites having more closely spaced links perform about two and a half times better than sites with distant links. It seems users prefer denser sites (Figure 3).
These two pieces of evidence seem to contradict each other, though, because the distance between large links is necessarily large (assuming, of course, the links aren’t nested!). You might think, “Wait… if I have a lot of large links, I’ll have huge CPV, but they will be spaced far apart, so I’ll have a small CPV!” But, in reality, the data is only reflecting a common website design principle—a few large links interspersed with many smaller, closely spaced links.
In fact, if you ponder these data long enough, it seems that we run into a chicken-and-egg problem. Click-throughs force a tautology. Design forces people to click in certain places, so they do. And we measure this. See why engagement matters?
In any case, the data back up our intuition when it comes to determining how many people will click through to a given piece of content. Given a large enough dataset in which you know where a link is on a page, its height and width, how many people are on the page, and how many are currently engaged with content, you could likely obtain a reasonable prediction for the CPV. And perhaps using this knowledge, one might use such a model to guide the redesign of a website.
We decided to try this (not the site redesign part, the modeling part!). Simple statistical models we have recently built can predict CPV for a link to within 0.007 clicks per min per active visitor for 92% of links. This might seem impressive, but to get a foundation for what this means, only four websites in the set we analyzed have a median CPV greater than this. There is much more work to do until we can really answer the question if design can predict attraction to and engagement with content, but the way forward is promising. Colors, font sizes, responsiveness—the design space is large. These can draw people in, but ultimately, it is the content that will keep people there.
So, the next time you are thinking of undergoing an overhaul or redesign, stare closely at your Heads Up Display. Think about link size, link density, and ask yourself what you can do to draw people into that fabulous content.