Managing Your Ad Spend Like a Hedge Fund: The Future of Marketing
Introduction and Real‑World Motivation
“Half the money I spend on advertising is wasted, the trouble is I don’t know which half.” – John Wanamaker [1]
Modern marketers still feel this pain, but the digital era gives us a new tool to solve it: incremental Return on Ad Spend (iROAS). iROAS asks a simple counter‑question: How much extra revenue comes only from the ads, compared with what would have happened if you spent nothing?
Real cases show why this matters. In 2019, Uber switched off roughly two-thirds of its performance budget, about 100 million dollars, and saw no drop in new riders [2]. During 2020, Airbnb cut most online advertising yet still kept about 95 percent of normal traffic [3]. Earlier, eBay ran a large experiment and found search ads created “no measurable benefit” to sales [4]. These stories show that “good” looking ROAS can hide spend that is doing almost nothing.
Forward-thinking brands now treat ad dollars the way hedge-fund managers treat capital. They move budgets away from low-lift campaigns and double down on the winners. One mid-sized retailer recently cut forty thousand dollars a month from low iROAS retargeting and re-invested the same money into high-lift prospecting. The result was a 15 percent jump in incremental revenue, about two hundred thousand dollars every month, without spending more [5].
From ROAS to iROAS: What Is the Difference?
Metric | What it Measures | Why It Can Mislead |
ROAS = Attributed revenue ÷ ad spend | Counts all sales that tracking software links to ads | Often credits conversions that would have happened anyway |
iROAS = (Revenue with ads – revenue without ads) ÷ ad spend | Counts only the extra sales caused by ads | Strips out coincidence and double counting |
Think of ROAS as gross return. iROAS is the alpha that Wall Street chases, the part produced by real lift.
Four Practical Ways to Measure Incremental Lift
Randomized Holdout Tests
Split the audience. Show ads to one group, hold them from another, then compare results. Cleanest proof but means some shoppers never see the ad.Ghost or PSA Tests
The control group sees a public-service message in the same slot. Keeps reach the same, isolates the creative.Marketing Mix Modeling (MMM)
Uses years of spend and sales data to tease out each channel’s effect. Great for TV and big budgets, slow for daily tweaks.Causal Inference on Observational Data
Data scientists build “twin” user groups with matching traits, then compare what happens with or without ads. Faster than experiments but relies on model quality.
Smart teams combine these tools: run experiments for ground truth, then let models fill the gaps between tests.
Ten Clues That a Campaign Will Have High iROAS
Indicator | Why It Matters |
High organic conversion rate | Little headroom, lower lift |
Large share of new customers | More true growth, higher lift |
Non-branded search or cold prospecting | Users are not already on the path to buy |
Moderate ad frequency | Too many impressions hit the same users with diminishing returns |
Fresh audience reach | Unsaturated audiences still have persuadable people |
Heavy competitor bidding on your brand | Defensive ads may prevent poaching, raising iROAS |
Off-peak timing | Ads can create demand when none exists |
Engaging creative (high CTR) | Signals relevance, often predicts lift on cold audiences |
Unique offer or value add | Converts fence-sitters rather than shifting spend |
Uplift or propensity scoring | Targets users who are unlikely to buy without the ad |
Use these clues the way an analyst watches market signals before placing trades.
Why AI Changes the Game
Human teams can analyze results monthly or weekly. AI engines like Leo can monitor every campaign minute by minute, predict iROAS before spend goes out, and move budgets instantly. Leo’s machine learning models study lift tests, creative performance, and audience signals in real time. The system reallocates spend the way high-frequency traders shift portfolios, aiming for maximum incremental return while humans sleep. This is not science fiction. It is the next step in digital advertising, and it will leave slow, manually run agencies behind.
Conclusion
Managing ad spend like a hedge fund means treating every dollar as an investment that must prove its worth. Traditional ROAS tells part of the story, but iROAS tells the truth. Marketers who adopt lift testing, causal modeling, and AI allocation will grow faster and waste less. Brands that cling to surface metrics will fall behind as platforms like Leo rewrite the rule book. The future belongs to whoever can measure, learn, and act the fastest, and that future is arriving now.
References
[1] John Wanamaker, retail pioneer, quotation circa 1900.
[2] The Hustle, “Uber was swindled out of 100 m dollars in ad spend,” 2021.
[3] LinkedIn post by Kieran Flanagan, “Airbnb turned off paid marketing in 2020,” 2021.
[4] The Guardian, “eBay study warns search ads have ‘no measurable benefit’,” 2014.
[5] Brenden Delarua, LinkedIn case study on incrementality testing, 2024.
Links:
Uber ad spend article: https://thehustle.co/01072021-uber-ad-spend
Airbnb paid marketing post: https://www.linkedin.com/posts/kieranjflanagan_airbnb-turned-off-their-paid-marketing-in-activity-6771444036818526209-oGEp
eBay study: https://www.theguardian.com/technology/2014/jun/05/ebay-search-ads-no-benefit-google-brands-berkeley-chicago