Musings from the Thesis team on Growth Marketing, Conversion Rate Optimization, and more.
The second post in our paid search account audit series in which we take a look at search keyword match type distributions.
When managing subscription-only ad campaigns on Facebook, return on ad spend becomes nearly meaningless. Profitability rarely ever happens after the first purchase but typically comes from a user’s lifetime value as they submit recurring payments months into the future.
It’s time to admit the days of relying on a social platform’s native ads manager to evaluate and optimize ad performance are likely coming to a close. In 2021, Blended ROAS will be our first step as advertisers to overcome this wrench in platform attribution.
When we audit prospective new client accounts, I always look for tell-tale signs that they might have an incrementality problem.
Like every other online advertiser, we see differences between what Google Analytics records on a last click basis and what Facebook's pixel reports, even when using a 1-day click attribution window. We wondered if there may be consistent discrepancies, so we dove into the data.
It’s estimated that the average person sees between 6,000 to 10,000 ads every single day, so it's incredibly difficult for your ad to cut through the clutter if someone only sees it once a month. What really is the golden number of times to reach a user?
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.
iOS 14 is forcing Facebook to implement a variety of platform changes, and one of these changes is the removal of placement breakdowns. With this loss of data looming around the corner, it’s more important than ever to understand where this feature is distributing your ad spend.
At Thesis we perform new ad account audits nearly every day. To aid those conversations, I've maintained my own internal ROAS benchmarks for reference. In this post, I've sanitized that ROAS data so that I can share it for general consumption!
Despite launching ads for the first time in just 2019, TikTok has quickly become a go-to platform for industry leaders. TikTok is vastly different from what we’re used to on Facebook in two different capacities: measurement and creative.
These days an overwhelming amount of attention is paid to video creative, and for good reason! Thesis now offers creative services including video production and post-production, and I find that most discussions online about FB/IG creative focus primarily on video assets.
In advance of Apple’s promise to crack down on user tracking on iOS, Facebook has begun implementing a series of updates to the platform that will forever change the way advertisers optimize and collect data.
As we've grown Thesis, I've taken a much greater interest in the agency ecosystem specifically. I'm curious about how agencies decide where to focus, how they position their services, and how they execute.
I've spent time this year doing ad hoc analysis of year-over-year January performance for a handful of subscription ecomm brands. To make sure I wasn't missing any macro trends, I analyzed Facebook campaign data for a basket of North American focused, D2C subscription clients.
Thanks to my work with Thesis, I have the opportunity to regularly audit paid search accounts from various ecommerce/D2C and lead gen brands. Over the years, I've developed a few quick reports that I use to gauge account health & expansion opportunities.
Privacy regulations are a new challenge marketers need to overcome, as platforms like Facebook are increasingly implementing their own requirements. And the results of non-compliance are dramatically impacting conversions.
Here is a sample summary of this blog post. We'll give you the gist in just a few sentences.
Prior to starting Thesis, I dabbled with content arbitrage/slideshow sites. These sites featured awful content, misleading ad placements, and worse. One benefit of this work is that I spent a great deal of time looking at native ads, and came across a lot of effective DR funnels.
I'm obsessed with incrementality testing, and generally skeptical about paid retargeting and view-through attribution. With that obsession in mind, I'm happy to share the results of a number of lift tests that the Thesis team and our clients have run over the last 6 months.