Marketers trust both affiliate marketing and marketing mix modeling (MMM), but few have made them compatible.

Marketers plan to increase affiliate spend by 11.3% next year to reach $13.8 billion, EMARKETER forecasts. Despite strong investment, measurement capabilities are holding the channel back, according to a new EMARKETER and Rakuten Rewards survey of 110 US marketers.

MMM, built to summarize impression-based advertising, struggles with the relationship-driven, trust-building nature of affiliate. Most marketers (57.3%) say MMM influences budgets, yet many lump affiliate into a broader performance bucket or ignore it altogether, according to the report.

“When you're shopping for an MMM, you need to look at how affiliates get represented,” said our analyst Max Willens. “For the people making these calls, affiliate marketing might not even be on their radar.”

MMM wasn’t built for affiliate nuance

Cashback, loyalty, and rewards captured the largest share of affiliate spend in 2024 (35%), per the Performance Marketing Association (PMA). While affiliate is a lower-funnel channel, creators are introducing products earlier in discovery, and immediate conversion isn’t always the goal.

As trust between consumers and creators builds, affiliate effectiveness accrues over time. Consumers often need three to four creator exposures before purchasing, according to a March 2025 impact.com and EMARKETER survey.

Among marketers using MMM, 27.3% fold affiliate into a general performance bucket and 14.8% don’t represent it at all. This can misrepresent its impact, said Parker Moss, director of affiliate at Ovative Group.

“Affiliate is very decentralized compared to other channels,” he said. “Since there are an increased number of partners to work with compared to other channels, it is very difficult to coordinate a test as we become heavily reliant on all the partners working together in unison.”

Only 22.7% say their MMM captures delay and decay for always‑on channels like affiliate moderately accurately, according to the report.

“If you do take the time to incorporate affiliate into an MMM, it does acquit itself pretty well,” said Willens. However, rebuilding a model to reflect affiliate’s cadence and partner diversity is complicated and costly, making it easy to deprioritize.

Slow cycles and knowledge gaps block action

Even with MMM measuring affiliate marketing, marketers struggle to act on results in time to make a difference.

• Marketers feed MMM insights into live optimization quarterly (34.1%), ad hoc (25%), or monthly (21.6%). Only 14.8% do it weekly, according to the report.
• 43.2% of marketers using MMM either don’t incorporate affiliate data into campaign planning or only do so after budgets are set.

“If your MMM results arrive three months after the campaign, how are you supposed to make smart decisions at the moment?” said Carl Kalapesi, senior vice president of revenue at Rakuten Rewards.

Many marketers don’t fully understand how their MMM works, making results harder to trust. Among those who don’t see a path to their desired granularity, 70.6% haven’t run geo‑split tests or incrementality lift studies.

• One third (33.0%) of MMM users don’t know how many distinct affiliate data sources must be stitched together before modeling.
• 87.5% say industrywide benchmark files, like average affiliate lag curves, would be at least moderately useful.

“The biggest challenge you actually have is a knowledge challenge,” said Kalapesi. “At a senior marketing level, there is still a perception that ‘one size fits all.’”

When affiliate underperforms in MMM, marketers should troubleshoot before cutting spend, said Moss.

“We partner across our affiliate and measurement teams to understand the reasons that affiliate is underperforming in the model and look for program modifications to increase the impact the channel is having on the overall business,” he said.

AI will magnify MMM’s blind spot

Consumers use AI for price comparison (54%), deal finding (41%), and review checking (41%), per a July Wildfire Systems survey. LLMs are already shaping shopping behavior in ways that mirror affiliate dynamics, building gradual intent over immediate conversion.

As AI changes discovery and gives affiliate marketing visibility, MMMs that can properly reflect the channel’s performance can help marketers keep pace.

“We shouldn’t lose sight of the fact that affiliate at its core is a performance‑oriented mechanism,” said Willens. “But as digital media continues to evolve, you ignore the upper‑, mid‑funnel, and GEO opportunities at your peril.”

Download the full report.

This article was prepared with the assistance of generative AI tools to support content organization, summarization, and drafting. All AI-generated contributions have been reviewed, fact-checked, and verified for accuracy and originality by EMARKETER editors. Any recommendations reflect EMARKETER’s research and human judgment.

This was originally featured in the EMARKETER Daily newsletter. For more marketing insights, statistics, and trends, subscribe here.