A dispatch from LiftLab’s Customer Forum, New York, May 2026
Nobody was performing. Across every session
That is the first thing worth saying about LiftLab’s customer forum in New York in May. These were experienced teams, people who spend their days thinking about measurement, budget defense, and the increasingly complicated relationship between marketing and finance. And when the room settled in, the same quiet tensions kept surfacing across every conversation.
It was not what most industry events feel like. It was better.
John Wallace, LiftLab’s CEO, opened the day in a way most vendor events do not.
“I want to brag a little. I am proud of this team, proud of what we have built, proud of what our clients have achieved. And I want to be vulnerable. I want to tell you the things that keep me up at night.”
The room got quiet. Not uncomfortable quiet. Listening quiet.
It set the tone for everything that followed. Because what came next was not a highlight reel. It was a genuine attempt to name where the real work is right now, and to do it in front of the people who feel the same pressure every day.
Why MMM Results Rarely Match What Marketers Expected
Cameron Hoy, VP of Customer Success at LiftLab, put a question to the room midway through the afternoon.
“When you got your first MMM model, did every channel look exactly the way you expected?”
Not one hand went up.
It was the most useful moment of the day. Because the silence said what no statistic can: most experienced marketing teams have seen a model challenge the story they had been telling internally. Some channels they thought were efficient turned out to be over-credited near the last click. Some channels that were hard to justify, the ones that got cut first in the last budget cycle, were actually doing more than anyone realized.
The math is not the hard part. Cameron knows this better than most. The hard part is what happens three weeks after the model lands, when a senior stakeholder asks a sharp question and the team quietly pulls up the Platform dashboards because it is fast, familiar, and gives a confident answer. Even when the confident answer is wrong.
“That is not a measurement failure,” he said. “That is a behavior problem. And it is the one nobody talks about enough.”
The CFO Is Now in the Room Earlier, and Platform Dashboards Can’t Answer the Questions
The finance conversation came up in almost every session.
Jacob Ross, Ex-CEO and Advisor at PebblePost, who has spent years navigating the CMO-CFO relationship from the inside, put it simply in his 1-on-1 conversation with John.
“Data makes me comfortable. Opinions make me uncomfortable. Experimentation sounds like we can be smart about how we spend.”
That is the whole shift compressed into three sentences. CFOs are no longer waiting at the end of the Budget cycle. They are in the room earlier, asking harder questions, and platform dashboards were not built to answer them. The teams that are moving fastest are the ones who have stopped bringing opinions to that conversation and started bringing Inspectable evidence.
Why Applying a Multiplier to Flawed Data Is Not Incrementality Testing
Sami Rabb, VP of Marketing Science at LiftLab, brought a vantage point that nobody else in the room had. Before joining LiftLab, he spent years at TikTok evaluating every major MMM and attribution vendor in the market, not as a buyer, but as someone whose job was to look under the hood.
“I got to see what everybody was doing,” he said. “And I picked the best one.”
But the more important thing Sami brought to the day was a scientist’s instinct for where methodology breaks down. He was direct about shortcuts.
“Applying an Incrementality factor on top of platform-reported data and calling it solved is not measurement. A multiplier applied to a flawed input is still a flawed output. Science does not work that way. The market is full of solutions that take that shortcut and present the result as rigorous.”
High Lift Does Not Mean Efficient Spend: The iROAS Distinction That Changes Budget Decisions
Andrea Ranieri, Director of Marketing Analytics at LiftLab, walked the room through a client result that permanently reframes what the word efficient actually means.
A channel was showing real, statistically significant lift. The kind of number that goes straight into the board deck. The kind of result that makes a marketing team feel vindicated.
The iROAS was $0.70 on the dollar.
“Yes, we are seeing this lift. But look at the iROAS. You are only getting $0.70 on average per dollar. The lift is fantastic, but it is still over-invested. You are overpaying for the lift you are getting.”
High lift is not the same as efficient spend. That distinction, simple in theory and genuinely hard to hold under budget pressure, is worth more than most measurement conversations produce in a year.
Then came the moment nobody expected.
What the Room Agreed On: Measurement Has to Be Finance-Ready
John put an inconclusive experiment on the screen.
Control and treatment groups matched going into the test. During the test they diverged in a way that did not reach statistical significance. The result was inconclusive. LiftLab said exactly that, out loud, in front of clients and prospects who had every reason to expect a highlight reel.
No cleanup. No reframe. No forcing it into a win.
The reaction in the room was immediate. Because nobody does that. The whole industry has a confidence problem that runs in the wrong direction. Vendors present every experiment as a clean result. Every model as a validated output. Every decision as a certainty. And the teams sitting across the table know, from experience, that the real world does not work that way.
Showing a non-result, with the controls intact and the methodology transparent, turned out to be the most trusted thing LiftLab showed all day.
John closed with a scenario that has stayed with everyone who was in the room.
A company went dark on 10 percent of their media. They ran the experiment carefully, with a holdout group and a treated group. They learned more from that single test than from years of platform reporting.
And then their CEO took the confidence from that experiment to the board.
Not the lift number. The confidence.
That is the shift this industry needs to make. From defending a number to building evidence. From hoping Finance trusts the dashboard to giving Finance something it can actually inspect. From measurement as a periodic report to measurement as a decision system that gets used every week.
“Give me more budget and I can do this much more. Give me less, and this is how efficient I can be.”
That line, from Cameron, is what the budget negotiation looks like when measurement is working properly. Not a fixed ask. A menu of outcomes, each one with evidence behind it.
The teams that left New York with the most were not the ones who had the cleanest results going in. They were the ones who had already decided to stop performing certainty and start building proof.
That room reminded everyone in it why this work matters beyond the model.
More of these conversations can be found on our Company’s LinkedIn Page as well as our executives’ LinkedIn profiles.
