TikTok advertising can be underfunded when last-click metrics understate its real, upper-funnel performance. This matters because a brand relying on last-click might pull back on TikTok when it’s actually driving revenue last-click isn’t capturing. Without testing incrementality and diminishing returns, brands leave growth untapped, staying conservative on a channel that could support more spend. This video shows how Skims used that kind of test to justify tripling its TikTok budget.
Why TikTok Advertising Is Often More Underfunded Than It Looks
TikTok advertising is often more underfunded than it looks, because a channel sitting further up the funnel can be genuinely working while last-click metrics make it look weak. In this video, John Wallace, CEO of LiftLab, shares a case study from Skims, the apparel brand behind the Kim Kardashian-founded underwear and swimwear line, and one he credits with a genuinely strong operating team.
Skims ran an experiment in LiftLab specifically on a channel their own last-click data suggested might be understating its performance: TikTok. Once LiftLab quantified both the incrementality and the diminishing returns on that TikTok spend, the results were better than expected, giving Skims the confidence to roughly triple what they’d previously been comfortable spending there. Wallace notes the resulting revenue growth from that decision more than covered Skims’ entire annual LiftLab subscription, and that this outcome, an experiment uncovering an underfunded channel and paying for the platform outright, is common enough across LiftLab’s customer base to be a pattern, not a fluke.
In this video, you’ll learn:
How to identify underfunded marketing channels using incrementality testing
Why last-click metrics often fail to capture true performance
The process of measuring diminishing returns to optimize advertising spend
How data-driven insights can lead to significant revenue and profit increases
Ways to justify the ROI of marketing effectiveness tools
TIME STAMPFull Video Transcript: The Skims TikTok Advertising Case Study
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In this video, LiftLab CEO John Wallace shares how Skims used incrementality and diminishing returns testing to justify tripling its TikTok ad spend.
[0:00 – 0:14] Introduction to Skims and the Operating Team
I love interacting with really smart marketers, and the operating team at one of our customers, Skims. If you’re not familiar with Skims, it’s the Kim Kardashian underwear and swimwear brand. That operating team is really fantastic to work with, and it’s a great example that they were willing to share.
[0:14 – 0:34] Experimenting with TikTok Performance
Where they ran an experiment in LiftLab, it happened to be something further up the funnel, something that their last-click metrics they knew had the potential to be understating the performance. And the performance that they, when they quantified both the incrementality and the diminishing returns of their spend on TikTok, they were pleasantly surprised in multiple ways.
[0:34 – 0:56] Scaling Spend and Results
They now have a newfound confidence to spend more on this channel, and their increase is about triple. They were willing to triple their spend from what they were comfortable with prior to the experiment. And the windfall of spending more on this channel, and in actualizing and taking advantage of that newfound growth, more than paid their LiftLab bill for the year.
[0:56 – 1:10] Common Benefits for LiftLab Customers
So this is not uncommon across LiftLab customers, to run an experiment, to have something that’s underfunded, and to be able to capitalize, just trade on the insights and capitalize on that, and pay their LiftLab bill right out of the gate.
Key Lessons: What the Skims TikTok Case Study Proves
Performance optimization: Brands can uncover hidden growth potential by looking beyond basic last-click attribution.
Strategic scaling: Testing allows companies to confidently increase investment in high-performing channels like TikTok.
Financial validation: Successful experiments often generate enough incremental revenue to pay for the analytics platform itself.
Data-driven confidence: Rigorous quantification of results empowers teams to make bolder decisions with their marketing budgets.
