It goes without saying that thoroughly understanding how traffic arrives at your site is critical for audience development efforts – certain traffic sources are ideal for reaching new readers, others may put your content in front of your existing audience and encourage them to visit more often, and still others may send traffic that will never be seen again.
Today, we’re kicking off a five-part series that takes a detailed look at how your audience’s behavior differs across traffic sources. Over the coming posts, we’ll go through homepage/direct traffic, traffic from external links and social sources, and search traffic. To start, though, I want to talk about how we classify referrers and define some basic metrics through which we compare their traffic.
Know your referrer types
At Chartbeat, we divide visitors’ traffic sources into four buckets:
Direct: people who get to your site by entering your site’s name in a browser, typically landing on your homepage
Social: people who arrive at your site from links provided by friends or others they follow on social media (e.g. Twitter, Facebook, Pinterest) or on email/IM
External: those who arrive via links from external sites (e.g. Drudge Report, Google News)
Search: visitors who come from search engines
The distribution of traffic across these buckets varies widely between sites – we see some sites with over 90% of traffic coming direct and others with over 90% of traffic from search. There’s no correct breakdown, but it’s important to keep your goals in mind when considering where to optimize: external sources typically send the most new visitors, while your most loyal audience is likely to come directly to your homepage.
Measuring audience engagement
As we’ve talked about before, Engaged Time is a good measure of fit between your content and your audience. So, one of the first questions we ask when trying to assess the quality of a given traffic source for a site is: how visitors are engaging with the pages they land on?Below we see visitors’ Average Engaged Time on article pages when coming from seven of the most common referrers: Notably, visitors from Facebook and Google News spend more than 50% more time than those who come from other sources (Tweet this fact). One possible explanation, which we’ll delve into more in Part 3, is that these are the only two sources on the list that typically show the first lines of a story when they present a link, so visitors from these sources are more likely to be committed to actually reading the story they end up on.
Understanding audience retention
Of course, we don’t simply care about how people behave when they land on your site — we want to know whether people who come to a site will choose to come back again. This turns out to be a question whose answer varies dramatically by traffic source. Below is a figure showing the fraction of visitors from a given referrer (the seven referrers from above, plus those who come direct to a site’s homepage) who come back sometime in the next week.
While the vast majority of people who come directly do come back, less than 50% of people from all other sources return. Amongst the set of non-direct traffic sources there’s also wide variance, with visitors from Twitter, Google search, and “dark social” almost 50% more likely to return than those from Google News and twice as likely to return as those from Reddit.
Amongst those visitors who do come back, how do they return the next time? That is, do people who come to your site from Twitter — for instance — always come from Twitter, or do they also come from other referrers or directly? The graphic below shows how frequently visitors who come from one source also come from another.Rows of this figure represent a visitor’s traffic source on one visit and columns represent where they come from the next time. Redder cells in each row represent combinations that occur more frequently, while whiter cells represent less frequent combinations.
The thing that stands out most in this figure is that people who visit your site from a given referrer are far more likely to come to your site again from the same referrer than they are to come from any other source. We term this phenomenon referrer loyalty, and it tells us that we can’t rely on traffic from an outside source returning without a steady stream of links on that source.
Cells in the direct column that are bright represent what is perhaps an ideal traffic relationship — referrers that send traffic that is likely to come directly to your site the next time they visit.
More to come
This post, I hope, raised more questions than it answered. Why do rates of engagement and retention vary so much by traffic source? And, more importantly, what can we do to affect these rates over time? We’ll start answering these questions next time by looking at your most core audience, your homepage direct traffic.
If you have questions about this data or things you’d like to see in the posts to come, I’d love to see your comments below. And please share this blog series with friends and coworkers.