Case Study
How Connected TV Delivered $20.75M in Incremental Revenue During Peak Holiday Season
A fast-growing direct-to-consumer brand* partnered with us to answer a tough question: could Connected TV add real, incremental growth on top of everything Black Friday, Cyber Monday, and the Christmas shopping season were already delivering, or would it just be riding a wave the brand was already catching?
*Client name withheld by request
Objective
Winning the Six Weeks That Define the Year
Every Q4, this brand's annual performance comes down to a narrow window: Black Friday, Cyber Monday, and the run-up to Christmas. Paid social had long carried the acquisition load, but leadership wanted proof that Connected TV could meaningfully add to that performance rather than simply borrow credit from sales that would have happened regardless. The mandate was specific: deploy CTV across the BFCM-through-Christmas window and measure, with geographic rigor, exactly how many resulting orders were truly incremental to what the season and the brand's other marketing would have produced on their own.
Challenges
Proving Incrementality When Everything Is Already Growing
Holiday season inflates nearly every number a brand tracks. Postal codes with zero CTV exposure still grew from 1,155 orders to 29,308 orders across the campaign window, a 2,437.5% jump driven by organic demand, other marketing, and the season itself. Against a baseline already up almost 25-fold, the real question wasn't whether Q4 would be strong. It was whether CTV could be proven to have made it meaningfully stronger.
Attribution Noise During the Multi-Touch Sprint
Holiday shoppers cross more touchpoints in six weeks than they do all year, and pixel-based attribution tends to double-count exposure across platforms during exactly this kind of surge. Trusting last-click data alone risked either overstating or completely burying CTV's true contribution.
Reaching Net-New Households at the Most Expensive Time of Year
CPMs spike across every channel during BFCM, making it costlier to reach shoppers who hadn't already engaged with the brand. The brand needed an approach engineered specifically to find new households, not just re-expose its existing audience at a premium.
Solution
A Geo-Based Measurement Framework Built for the Holiday Surge
New-Customer-Only CTV Targeting
CTV campaigns were configured from the outset to exclude anyone who had already visited the brand's site, so every impression was aimed at expanding the addressable audience rather than re-engaging shoppers already in the funnel.
Postal-Code-Level Geographic Lift Design
We ran a double-controlled difference-in-differences analysis, comparing order volume before and during the campaign across both CTV-exposed and non-exposed postal codes, which gives a cleaner read on true causation than pixel-based attribution allows during a season this noisy.
A Conservative, Floor-at-Zero Incrementality Model
Each treated postal code's expected orders were calculated by applying the control group's own organic growth rate to its pre-period baseline.
Quintile Analysis Across the Spend Curve
Treated postal codes were segmented into five tiers by CTV investment level, mapping exactly where additional spend was still efficient and where it began to plateau.
Results
6.86x ROAS Against a Baseline That Was Already Up Nearly 25x
CTV generated an estimated 93,918 incremental orders beyond what the season's organic growth alone would have produced, translating to $20.75M in incremental revenue against $3.03M in total CTV investment, for a 6.86x incremental return.
Outperforming the Season at Every Spend Level
Even measured against that 2,437.5% organic baseline, CTV-exposed postal codes posted lift ranging from 567.5% above baseline at the lowest spend tier to 1,732.6% above baseline at the highest, with no inversions across any of the five quintiles.
An Efficient Curve With Room to Scale
When comparing the lowest-spending postal codes against the highest-spending postal codes, we saw a predictable diminishing-returns curve rather than a cliff, which is exactly the kind of signal that makes scaling investment a calculated decision rather than a gamble. With greater investment came greater scale, with performance consistently coming in above goal.
Built-In New-Customer Bias
Because CTV excluded existing site visitors by design, the incremental orders measured here skew heavily toward genuinely new households. This is key while scaling, and was the audience expansion the brand needed most heading into its next fiscal year.
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