I very rarely see D2C brands with meaningful YouTube ad spend being measured on a performance basis. For this post, I'll be breaking down the basics of the setup for Brand X, which spends just north of $600k per month on prospecting on YouTube. I've indexed or anonymized almost all of the data, but despite that I think this will still be interesting for folks in D2C growth.
This ad account is structured with 1 Ad Group per 1 Campaign (essentially, each audience/targeting type is broken out into a unique campaign). Over the last 30 days, this account had roughly 10 enabled Ad Groups at any given time.
Each Ad Group has anywhere from 10-20 enabled ads at any given time. Notably, spend is reasonably well distributed across the enabled ads (ex: the top spending ad in each Ad Group accounts for ~10% of total spend in most cases).
I've written up the details below, but essentially these are auto bid, wide-open campaigns. The settings really are not exceptional or complex.
Conversion Action: They optimize for Purchase, and do not include any other events in Total Conversions (notably, I've worked on other brands that include events like Leads or Add to Cart in the Conversions count for the purposes of feeding the conversion algorithm more data, but I've never seen conclusive evidence that this actually works). They use 1-day click + 1-day view conversion/attribution windows.
Bid Strategy: Maximize Conversions (the equivalent of Facebook's Lowest Cost, for those less familiar with Google Ads).
Network Targeting: YouTube videos + Video partners on the display Network.
Geo Targeting: US
Language Targeting: English
Content Exclusions: They use YouTube's "Limited inventory setting" and also explicitly exclude Mature audiences content. It's a pretty typical exclusion setup.
Device Targeting: Everything except for TV screens.
They run a conventional mix of broad and keyword based custom audiences in addition to some basic retargeting. They also have experimented a bit with Placement/contextual targeting, but in most cases are not leveraging YouTube's placement targeting.
I categorized the campaigns based on Targeting + Placement targeting and calculated the % of spend for each strategy over the last 30 days. I also indexed the CAC results (so 1.0 = the average CAC for the account during this period) so I could share performance differences between audiences without sharing anything too sensitive. For context, this brand has CAC targets in the $45-$50 dollar range.
Essentially, Broad targeting with a very basic setup is driving the account. Keyword based Custom Audiences preform really well, but they are extremely limited in terms of scale (obviously!). I think in this case the real driver of performance is creative & LPs... which is really a sign of the times.
At Thesis, we’ve developed a testing methodology that generates more learnings, quicker, while also protecting our core scaling campaigns from creative flops. We’ll show you exactly how we set up these creative tests and generate more creative wins for our clients.
A detailed look at how Ad Relevance Rankings correlate with actual performance.