We can see that social media sites (including Twitter and Facebook) refer the majority of TTR. Clicks from Medium pages (such as collections, user profiles, and the “Read Next” section at the bottom of stories) represent another 11% of TTR.

But this first chart didn’t tell the whole story. To better understand what’s happening, I examined how this distribution differs across two important factors.

Traffic Level

Since Medium stories see very different traffic levels, they likely see different traffic distributions as well. I bucketed stories into one of three categories: top, middle, and tail. “Top” stories on Medium are the ones that see super high levels of traffic, often going viral on sites like Reddit, Twitter, and Facebook. “Middle” stories are the middle chunk that don’t necessarily go viral but still see decent traffic, often due to engaged audiences that continue sharing the story long after it is published. The “tail” end category comprises the rest.

Recency

The second major factor that affects traffic is the recency of a story. Since people typically share their stories immediately after publishing them, about half of a story’s traffic tends to arrive within a week of publication. So, I categorized referrer traffic by whether or not it’s arriving within that first week.