What Browser Extensions Reveal About the Cracks in Attribution Models

Browser extensions have long been a key part of the affiliate marketing ecosystem, offering consumers convenient tools to enhance their online shopping experience. However, recent controversies have suddenly brought them under scrutiny, not because they have changed, but because the industry has finally realized what has been happening all along.

Browser extensions, such as Honey, Capital One Shopping, and Rakuten, automatically apply coupon codes, offer cash back, and compare prices in real-time, and users must first install these extensions to activate these features. Once installed, if a user visits a merchant’s site, the extension can identify available offers and display them. However, the user usually needs to click on the extension to activate the offer or coupon. Only after this does a tracking cookie get dropped or an affiliate link get injected, allowing the extension to track the purchase and earn a commission through affiliate programs.

At first glance, the process appears straightforward; so, why is a long-standing industry practice suddenly under such intense scrutiny? 

The heart of this debate centers on the last-click attribution model, which has been standard in the affiliate marketing industry for many years. Critics claim that browser extensions exploit this model by adding their affiliate links at the final step of the purchase process, effectively overriding the efforts of all other touchpoints in the journey, including content creators, influencers, and publishers further up the funnel who initially guided the consumer. Much of this early criticism has come from large media publishers and influencers, who saw their commissions diverted despite driving initial shopping intent. The issue has gained momentum over the past year as more brands scrutinize performance attribution and question whether extensions like Honey truly generate incremental value. This has raised concerns about fair compensation and attribution, prompting increased scrutiny and even legal challenges. 

While the concerns are valid, it’s important to recognize that the last-click attribution model has been a long-standing industry standard. Browser extensions operate within the parameters set by affiliate programs, and their actions are not inherently deceptive; instead, they reflect existing attribution frameworks. That said, last-click is increasingly viewed as insufficient. Marketers and platforms are increasingly advocating for multi-touch and “incrementality” models that distribute credit across multiple partners, not just the one who closes the sale. 

According to Forrester’s 2024 Marketing Survey, 67% of B2B marketing executives reported increasing their budgets, with a portion allocated to better measurement and attribution tools. This clearly indicates that the industry is reassessing how value is measured and who truly deserves credit throughout the purchasing process. 

In response to these trends, affiliate managers must evolve their strategies to reflect a more nuanced understanding of partner impact and consumer behavior. Attribution models, partner incentives, and even how we define value in a performance channel are all subjects of debate. As this shift gains momentum, at PMG, we’ve been focusing on how brands can develop smarter, more resilient affiliate strategies that reflect the full customer journey.

If your program still relies solely on last-click attribution, you’re missing the bigger picture. Leading affiliate platforms (such as Partnerize or Impact) now support configurable attribution logic, including linear, first-click, and multi-touch models. These technologies also allow brands to customize rules based on partner type. Even if you’re not ready to overhaul program attribution entirely, these platforms are worthy of consideration, as they provide data and insight on click paths, time-to-conversion, and partner influence, giving marketers a clearer view of how users engage with each partner. This enables you to identify which partners influence customers earlier in the funnel and assign partial credit even if the core attribution model remains unchanged. In many cases, simply segmenting performance by funnel stage uncovers overlooked partner value. 

One PMG customer addressed this attribution challenge by extending cookie windows and adding preferred crediting for content partners. The rationale was straightforward: high average order value (AOV) products tend to have longer purchase consideration windows, so giving upper-funnel partners more time to earn credit made sense. It’s a way to acknowledge the importance of early influence, especially compared to loyalty sites where purchases occur more quickly. Ultimately, this update resulted in a 29% increase in attributable revenue, demonstrating that aligning crediting models with actual shopper behavior can lead to more accurate payouts and improved overall performance.

With so many different partner types involved, it’s challenging to ensure all affiliates receive credit for the actual value they contribute. From influencers to loyalty programs to browser extensions, it’s hard to know who’s truly making an impact and who’s just showing up at the end. A strong affiliate program includes setting internal benchmarks and integrating affiliate data into broader media mix modeling to better understand incrementality. 

New platforms and technologies can make it easier to connect affiliate data with media mix models or larger attribution frameworks. Even if you’re not ready for a full MMM analysis, directional insights can still be useful. Ultimately, this isn’t about excluding anyone. It’s about gaining clearer insights into who’s helping and ensuring compensation reflects that.