Traffic Source Distribution Analysis For 30 Brands

Here is a sample summary of this blog post. We'll give you the gist in just a few sentences.

Our Methodology:

We pulled Google Analytics traffic source/medium data for 30 brands, all of whom are US focused, from Jan 2020 -> June 2020. Much of this data comes from miscellaneous advisory roles that I hold outside of Thesis, though we did include a few sanitized Thesis clients as well. Five of the brands included focus on lead gen, eleven are subscription D2C, and 14 are conventional D2c. In some cases, the distinction between subscription and "conventional" D2C was a bit unclear. Our rule of thumb was that if the majority of a brand's paid spend pushed to a subscription focused funnel they were lumped into the subscription bucket.

We categorized each source/medium as paid or non-paid, and we grouped the sources into the following categories:

Traffic: Non-Paid

  • Direct
  • Organic Search
  • Organic Social / Referral
  • Email / SMS

Traffic: Paid

  • Paid Search
  • Paid Social
  • Programmatic / Display (including Criteo/Adroll & native channels like Taboola & Outbrain)
  • Affiliate / Influencer (thanks to vanity URLs/promo codes)
  • TV (thanks to vanity URLs/promo codes)
  • Podcast / Radio (thanks to vanity URLs/promo codes)
  • Other Paid (Direct Mail, Print) (thanks to vanity URLs/promo codes)

Some caveats

It's worth noting that Google Analytics data has significant limitations. By definition, Google Analytics is capturing source data based on incoming UTM parameters. For sources like TV or Radio, those parameters only exist if traffic comes through specific predefined paths. And of course, GA data, when analyzed in this way, does a rather poor job of capturing the full impact of upper funnel channels.

Also, we readily admit that our ~30 brand sample size is very small, but we believe it's big enough to be interesting.

The Data:

We saw a roughly 50/50 split in paid and non-paid traffic

Paid Search & Social account for a majority of paid traffic, as expected.

Above is the full paid breakdown. We've called out a few highlights below.

Programmatic / Display Is Tiny For DTC

When I talk to folks outside of the D2C bubble, they are often surprised at how unimportant display is for the D2C category, even when you include Google's display network. This data backs up the reality that for D2C display is effectively only a retargeting channel (and one with potentially dubious incremental value).

Meanwhile, in our small lead gen sample, we see significant traffic from programmatic / display. Perhaps there are some learnings that D2C brands could borrow from lead gen... or perhaps these lead gen folks have just been unable to make social scale to the same extent as D2C.

For good measure, we took a closer look below at the split of display spend. And, as expected, we see Criteo / Adroll have a pretty healthy share for ecommerce.

Google (Search + Shopping) Are ~90%+ of Paid Search Traffic

This actually lines up neatly with search engine market share data I found online that pegs Google at 87%.

Facebook & Instagram represent ~86% of paid social traffic

I think this will come as a surprise to no one, but it does paint a somewhat sobering picture for the challenger channels. Given the state of the world, I'm confident in the coming months we will see those Reddit, Snap & TikTok numbers increase dramatically. Meanwhile, the utter lack of impact of Twitter on these SMB categories has to be a bit disheartening.

This post was co-written by my friend and colleague Zach. And to be fair, he did 95% of the work. If you have any questions or critiques of the above (and I'm sure there are PLENTY to be made) please let me know ( We'd love to hear from you.

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