No single ad measurement methodology works well anymore for brands with multiple points of sale.
That is why attribution startups and consultants use phrases like “triangulation” to refer to a patchwork approach between multitouch attribution (MTA), marketing mix modeling (MMM) and incrementality testing.
For the attribution and analytics company Northbeam, which released a new incrementality testing feature on Tuesday, that change has meant working “pretty aggressively” since the beginning of 2026 to “complete the trifecta of digital attribution,” VP of Product Stas Goldobin told AdExchanger.
Incrementality is a necessary “calibration layer” between the mainstays of MTA and MMM, Goldobin said.
MTA is useful for understanding a marketing conversion or customer journey that’s happened within the past day or week, especially when someone can be tracked online by conversion events and pixels. MTA helps marketers understand an individual’s customer journey within a platform and a relatively short time span. MTA reporting also tends to give direct and useful insights to a marketer, who can immediately put that information to use in a campaign. (For example, MTA provides a list of retargetable online users.)
MMM evaluates a far broader span of media – every cent spent by marketing, in theory – but never at an individual level. The idea, Goldobin said, is to answer questions about what might have happened with a different media mix or how much a whole channel, like Meta, might have contributed over a period of weeks or months.
Incrementality sits in between, he said. Incrementality tests don’t track individuals or provide user-level insights, and, unlike MTA, it takes some days or weeks to run an effective test. But incrementality measurement incorporates more of the live, digital-based data streams of MTA.
“The internet is a funny place,” Goldobin said. “Sometimes, pixels don’t fire; sometimes, events don’t get captured.” Different platforms cannot reconcile when, say, an ad campaign on Meta led to a purchase on Amazon.
Incrementality stitches these things together and, while it can’t deterministically attribute those Meta-to-Amazon conversions, it can advise that something like 20% of conversions on one platform might be tied to ad campaigns on a different platform, or whether organic sales with one retailer can be attributed to ads from a particular online platform.
Northbeam’s incrementality product currently includes Meta and Google as testbed options, and the company plans to add more platforms and cover 80% of average client budgets with incrementality testing within a few months, Goldobin said.
Although, he added, for the purposes of incrementality testing, Google actually breaks up into six different properties: Google Search, Google Shopping, Performance Max, Demand Gen, YouTube and Google Ads.
Nobody is just “running a Google campaign,” he said, at least not the omnichannel marketing operators who use Northbeam. Marketers want to know how YouTube is affecting their business or how search engagement relates to YouTube ROI.
Is there anything the big platforms could do to accommodate better incrementality testing?
For one thing, Goldobin said, it would be nice to be able to do more tactical experimentation and tinkering within a platform campaign. Right now, he said, the Meta and Google AI-based products “go into a full retraining and relearning cycle” whenever a change is made in the campaign, often even a small tweak. Marketers must carefully balance whether a “micro-optimization” is worth making, if the platform AI might restart its campaign training from zero.
“We know the level of effort that it takes to automate executing across all of these platforms,” he said. “It’s not easy to do. It should be easier.”
