MMM

Most brands and businesses are trying to figure out how to improve their metrics when it comes to AI – and also what those metrics even are.

MMM’s next challenge is developing a more rigorous way to challenge, validate and apply its conclusions.

By all means, measure outcomes. Optimize toward sales. Make television more accountable. But if the product is basically a pixel, an attribution window and a CPA column, that doesn’t mean we’ve transformed TV into Google. 

Can you trust an AI-built marketing mix model? M-Squared’s Madan Bharadwaj on why AI makes expert judgment matter more, not less.

MMM helps marketers understand if a channel worked in the aggregate and what happens when the next dollar is added. For CTV, that discipline is badly needed. But MMMs can’t answer everything.

MMM can tell marketers what worked, but Lifesight’s open-sourced forecasting tool aims to tell them what to do next.

The IAB raises its forecast for ad spend growth; Google continues to develop Meridian, its open-source MMM tool; and Partiful is still learning how to monetize.

Wanna chat with your marketing mix model? Well, open-source tools and AI agents are making that possible.

Newton Research introduced a fully agentic layer to its platform that can handle each step of a campaign lifecycle and better predict future outcomes.

Somewhere between what the ad industry says and what the market rewards is often where the truth lives. Here are the three industry storylines most in need of debunking.

Marketers are rediscovering MMM. Google Meridian and Meta Robyn are among the tools gaining attention among marketers. We dive into what it means to tie your MMM solution to a search or social media giant. 

Google and Meta are quietly rewriting the rules of ad measurement, and they’re doing it with open-source marketing mix modeling tools that many marketers don’t even realize they’re using.

In a world being agentically orchestrated at scale, human judgment is the indispensable guardrail preventing us from optimizing right over the cliff.

Binary measurement preserves margin and lets late-arriving impressions claim credit they may not deserve. We need a new measurement model for the AI era.

Between signal loss, missing audience information and aging data, most of the data that companies have is spotty. But despite what you may have heard, agentic AI can deal with spotty data.

WPP is shifting to a pay-for-performance revenue model. But there are many barriers to clear before PFP becomes the industry standard.

AdExchanger Senior Editors Alyssa Boyle and Anthony Vargas share their takeaways from three days chatting about agentic AI at POSSIBLE.

There’s MMM and MTA, but no single ad measurement works for brands with multiple points of sale. On Tuesday, Northbeam launched an incrementality tool to complete what it calls “the trifecta of digital attribution.”

Mike Finnerty is leaving TransUnion to become Mutinex’s US president and lead the company’s expansion stateside.

The future of retail media depends on a shift away from siloed in-store and online metrics to a full-funnel approach that reflects how customers actually shop.

True Religion CMO Kristen D’Arcy approaches marketing measurement the way you’d shop for jeans – by looking for the right fit. She’s moved past last click, using real-time data to see what actually drives sales, and she isn’t afraid to make fast changes when something isn’t working.

AI shopping agents are breaking the traditional attribution loop. Marketers must ensure that AI is aware of their brand and track how that awareness influences ecommerce outcomes.

When it comes to complex techniques like media mix modeling, the field is awash with false promises about the benefits that AI can offer.

Marketing often gets unfairly pegged as a cost center. But that wouldn’t happen if marketers had access to better measurement that gave them clarity on what truly drives business growth, argues Henry Innis, CEO and co-founder of MMM platform Mutinex.

Deli meat company Land O’Frost has been leaning into a new MMM approach to figure out which opportunities it’s been overlooking – or even inhibiting.

As privacy rules tighten, M&C Saatchi built OneView to help marketers measure performance without relying on cookies or user-level data.

Live from New York at Programmatic IO, the AdExchanger editorial team debriefs what ad tech’s brightest minds are saying and doing around AI and measurement.

The competitive set has shifted and it’s stacked against independent DSPs. But, instead of chasing what competitors already own, TTD can own what they can’t: trust.

Newton Research announced its $9 million Series A raise on Tuesday. The funds will go toward hiring as demand for Newton’s specialized AI agents grows.

The Marketing Efficiency Ratio (MER) is a data-driven advertising metric that’s been around for many years but is now reaching mainstream, or to some at least, revered status.