Executive Overview
The modern digital advertising landscape is undergoing a structural paradigm shift, moving away from proxy metrics like clicks and impressions toward true return on investment. At the vanguard of this movement are retail media networks (RMNs), which have emerged as the fastest-growing sector in the digital marketing ecosystem. Leveraging first-party shopper data, retail giants have transformed their digital and physical storefronts into high-yield advertising engines.
Among the leading players is Roundel, the retail media arm of big-box titan Target. For the past several years, Roundel and its industry peers have aggressively championed incrementality as the ultimate metric for campaign measurement. Designed to answer the holy grail question of modern advertising—“Did this ad actually drive a sale that wouldn’t have happened otherwise?”—incrementality uses rigorous test-and-control methodologies to isolate true ad-driven revenue from baseline organic purchases.
Yet, despite its methodological superiority, a significant chasm exists between theory and execution. During a high-profile industry event in New York City, Shawn McGahee, Senior Director of Performance and Insights for Roundel, revealed a striking statistic: only 8% of Roundel’s advertisers currently utilize incrementality measurement as the primary performance metric for their businesses.
This disclosure lays bare a fascinating tension within the retail media industry. While platforms remain deeply confident in the accuracy and necessity of incrementality, advertisers are proving slow to adopt it as their north star. This article explores the root causes of the "incrementality paradox," examining the technical complexities of the metric, the structural inertia of corporate marketing departments, the financial trade-offs of testing, and what this adoption gap means for the future of the multi-billion-dollar retail media economy.
Detailed Chronology: The Rise of Retail Media and the Quest for True Measurement
To understand why incrementality has become the focal point of modern retail media discourse, one must first trace the rapid evolution of the ecosystem over the past decade.
Phase 1: The Ad-Network Gold Rush (2018–2020)
In the early days of retail media, legacy retailers realized they were sitting on a goldmine of point-of-sale data, loyalty program insights, and high-traffic digital properties. As third-party cookies began their slow decline and privacy regulations like GDPR and CCPA tightened the noose on traditional programmatic targeting, brands flocked to RMNs. Platforms like Amazon, Walmart, and Target offered something walled gardens could not: closed-loop measurement linking an ad impression directly to a cash register receipt.
During this nascent phase, success was largely measured by top-of-funnel metrics: impressions, click-through rates (CTR), and Return on Ad Spend (ROAS) calculated via last-touch attribution models. Retailers built out their ad inventories rapidly, and brands eagerly reallocated budgets from traditional search and social channels to capture high-intent shoppers at the point of digital purchase.
Phase 2: The Push for Accountability (2021–2022)
As ad spend in retail media swelled into the tens of billions of dollars, Chief Marketing Officers (CMOs) and Chief Financial Officers (CFOs) began demanding deeper accountability. Traditional last-touch ROAS models quickly came under fire. Critics pointed out a fundamental flaw: last-touch attribution often rewards brands for advertising to consumers who were already going to buy the product anyway—such as loyalists searching explicitly for a brand name.
Enter incrementality. Industry thought leaders began arguing that true performance could only be measured by identifying "lift." Retailers began investing heavily in data science capabilities to run sophisticated test-and-control experiments, splitting audiences into control groups (who see no ads) and test groups (who see the campaign) to calculate genuine incremental revenue.
Phase 3: The Implementation Chasm (2023–Present)
By 2023 and into 2024, major retail media networks were universally positioning incrementality as the gold standard of campaign evaluation. Retailers like Target invested heavily in educating brands, building automated measurement dashboards, and evangelizing the methodology at industry conferences.
However, as Shawn McGahee’s recent revelations in New York underscored, evangelism has not translated into widespread operational adoption. Despite years of industry advocacy, the vast majority of advertisers continue to rely on legacy metrics, treating incrementality as an occasional luxury audit rather than the day-to-day foundation of budget allocation.
Supporting Context & Metrics: Decoding the Incrementality Dilemma
The stubborn persistence of legacy metrics over incrementality is not driven by ignorance; rather, it is the result of a complex web of technical, financial, and organizational hurdles. To grasp why only 8% of Roundel’s clients have made incrementality their primary metric, one must examine the mechanics of the metric itself and the friction it introduces into corporate marketing workflows.
What is Incrementality, Really?
Mathematically and operationally, incrementality is defined as:
$$textIncrementality = textTotal Sales (Test Group) – textTotal Sales (Control Group)$$
By holding back advertising from a randomized control group of consumers, data scientists can measure the baseline purchasing behavior of shoppers who resemble the target demographic. Any statistically significant divergence in sales between the test group and the control group is attributed directly to the advertising intervention.
Unlike last-touch ROAS—which often flatters campaigns by taking credit for organic demand—incrementality forces brands to confront hard truths. It asks: Did this ad campaign actually expand our market share, or did we just pay to acquire customers who were already in our conversion funnel?
The Barriers to Adoption: Why Advertisers Hesitate
1. The Fear of Suppressed Sales (The Control Group Cost)
To run an incrementality test, an advertiser must intentionally withhold ads from a portion of their target audience. For brands hyper-focused on quarterly sales targets and short-term revenue velocity, holding back marketing pressure feels counterintuitive and risky. Marketers often worry that the control group will experience a dip in sales, negatively impacting overall volume during a competitive promotional window.
2. Organizational Inertia and Attribution Habits
Corporate marketing structures are deeply entrenched in legacy attribution models. Many brands have built internal compensation structures, agency contracts, and dashboard software entirely around last-touch ROAS or multi-touch attribution (MTA). Shifting to incrementality requires a complete rewrite of how success is reported up the corporate ladder—a daunting task for marketing directors accustomed to reporting predictable, if flawed, positive ROAS figures.
3. Data Complexity and Resource Constraints
Executing reliable incrementality tests requires advanced data infrastructure, statistical expertise, and robust sample sizes. Smaller and mid-sized brands operating within retail media networks often lack the dedicated data science teams required to interpret complex lift studies, preferring simple, out-of-the-box reporting metrics provided by publisher dashboards.
4. The "Truth Hurts" Phenomenon
Perhaps the most potent, if unspoken, deterrent to incrementality adoption is the reality it exposes. When brands transition from traditional ROAS to rigorous incrementality measurement, reported performance metrics often drop significantly. Brands that previously boasted a 5x ROAS under loose attribution models may discover their true incremental ROAS is closer to 1.5x. In a corporate culture where performance metrics justify budgets, voluntarily adopting a metric that makes campaigns look less efficient requires immense political courage from marketing leadership.
Official Statements and Industry Perspectives
The discourse surrounding Roundel’s recent disclosures highlights a fascinating dichotomy between platform confidence and advertiser hesitation.
Speaking directly to the gathered advertisers in New York City, Shawn McGahee struck a tone that was simultaneously pragmatic and resolute. While acknowledging that only 8% of Roundel’s advertisers have fully integrated incrementality as their primary guiding metric, McGahee expressed unwavering confidence in Target’s measurement framework.
"We are entirely confident in our approach to measuring incrementality," McGahee emphasized during his presentation. "The methodology is sound, the data infrastructure is robust, and the insights it provides are unmatched in terms of business truth. However, we also recognize that the industry is on a journey. Shifting the foundational way a brand evaluates performance requires a fundamental evolution in mindset, tooling, and organizational risk tolerance."
Industry analysts have weighed in heavily on McGahee’s remarks, noting that Roundel’s transparency is indicative of a broader conversation happening across the entire retail media landscape.
Nicole Perrin, an industry analyst specializing in retail media, noted:
"Retail media networks have spent the last three years building sophisticated measurement engines. But building the car is only half the battle; teaching the industry how to drive it at high speeds is proving much harder. Advertisers are comfortable with the comfortable fiction of last-touch attribution. Moving to incrementality means accepting lower reported numbers in exchange for higher-quality business decisions—and that is a hard sell for any marketer trying to protect their budget."
Meanwhile, brand-side executives point out that retail media networks must do more to lower the barrier to entry. Several prominent consumer packaged goods (CPG) marketing directors have argued that RMNs need to standardize incrementality testing, make control-group management more transparent, and share the financial risk of withholding ad impressions during critical retail seasons.
Future Outlook: Bridging the Gap in Retail Media Measurement
As the retail media market matures past its hyper-growth infancy, the conversation is shifting from sheer expansion to efficiency, optimization, and financial accountability. Where does the industry go from here, and how can retailers close the vast gap between the 8% adoption rate and the theoretical ideal of 100% incrementality-driven marketing?
1. The Evolution of Hybrid Attribution Models
Rather than demanding an overnight, all-or-nothing leap from traditional ROAS to pure incrementality, forward-thinking RMNs are beginning to develop hybrid measurement frameworks. These models use incrementality benchmarks to calibrate and adjust routine, lower-funnel attribution dashboards, allowing brands to benefit from the accuracy of lift studies without the day-to-day friction of managing live control groups for every campaign.
2. Automation and AI-Driven Lift Measurement
To solve the resource and data complexity barrier, retail media networks are increasingly turning to machine learning and artificial intelligence. By automating synthetic control groups and predictive modeling, platforms like Roundel can reduce the operational burden on advertiser data science teams, making incrementality insights as easy to access as a standard click-through report.
3. Agency Education and Executive Alignment
Closing the adoption gap will also require active participation from holding company agencies and C-suite executives. As procurement departments and CFOs demand greater financial rigor from marketing investments, the pressure to prove true incrementality will mount from the top down. Agencies that successfully guide their clients through this transition will position themselves as indispensable strategic partners.
Conclusion
Shawn McGahee’s revelation that just 8% of Roundel’s advertisers rely on incrementality as their primary metric serves as a sobering reality check for the retail media industry. It highlights a critical paradox: while incrementality is universally acknowledged as the most accurate measure of advertising effectiveness, the structural, psychological, and operational inertia of corporate marketing continues to favor comfortable proxies over inconvenient truths.
Nevertheless, the trajectory is clear. As digital ad budgets face increased scrutiny and retail media networks continue to refine their measurement products, the pressure to adopt true lift-based metrics will only intensify. The brands and retailers that successfully bridge this measurement gap today will not only master the science of retail media but will secure a decisive competitive advantage in the retail landscape of tomorrow.