Summary
Retail media marketers evaluating new measurement solutions need to focus on how the iROAS core requirements impact the accuracy of the solution. Incremental Return on Ad Spend (iROAS) demands transparency, customization, and granularity. Skai’s iROAS solution addresses these foundational needs, empowering marketers to unlock actionable insights and optimize campaigns with confidence. By focusing on these fundamentals, brands can achieve smarter strategies and drive sustainable growth.
Last updated: December 23, 2025
Retail media measurement remains a complex puzzle, with countless ad formats, channels, retailers, and fragmented data points adding to the challenge. As brands grow their year-over-year investments in retail media, the stakes have never been higher—and performance goals are becoming harder to achieve. Incrementality has emerged as the go-to approach for understanding “true” impact, but not all solutions are created equal. In this high-stakes environment, accurate measurement isn’t just helpful—it’s essential for making smarter, more effective decisions.
Throughout my career, from working within both front-end and back-end Amazon teams to leading strategic account teams within an agency, I’ve seen firsthand how the right tools and approaches can transform a marketer’s ability to move from generic reporting to actionable, business-specific insights. These experiences taught me that solving the retail media puzzle means embracing tools that go beyond surface-level metrics and address the nuances across channels.
Today, early evergreen incrementality solutions like iROAS (incremental Return on Ad Spend) are paving the way for actionable measurement. While these tools provide an important step forward, it’s critical to ask the right questions before committing to any one approach. Not all solutions offer the iROAS core requirements of transparency, context, and flexibility that marketers need to make decisions confidently and effectively.
Micro-answer: Incremental lift per dollar spent.
Unlocking the power of iROAS in a complex retail media landscape
- Retail media incrementality is harder at scale.
- iROAS needs transparency and control.
- A practical iROAS program combines trusted data access, marketer configurable experiment design, and actionable insights that translate lift into decisions. Done well, it helps teams compare retailers fairly, reduce wasted spend, and shift budgets toward tactics that create real incremental growth.
The evolution of retail media continues to set these channels apart from traditional media, offering solutions that embrace the publisher and the point of sale as the same. It blends the complexities of media and commerce in ways that challenge traditional measurement approaches. The evolution brings more data for a singular channel; however, this both enables and hinders marketers as they try to solve for incrementality. Walled gardens and fragmented attribution systems make achieving a unified view of performance difficult. On top of this, the endless variations in metrics, operational levers (pricing, promotion, rating, inventory, etc.), and the interplay between online and in-store performance add layers of complexity.
Even within organizations, teams often disagree on the baselines for incremental analysis. In fact, a recent joint study by the Path to Purchase Institute and Skai found that 70% of advertisers struggle to measure the incremental performance of their retail media, underscoring the need for more accurate and adaptable measurement approaches.
The introduction of iROAS (incremental Return on Ad Spend) marks a significant step in this evolution. It has up-leveled the foundational digital marketing metric of ROAS by measuring the potential causal impact of advertising spend in real terms. While it provides a valuable starting point, vendors often approach iROAS in different ways, leading to varying levels of transparency and customization. The result? Marketers must carefully evaluate which tools truly meet their needs.
An always on iROAS program works best when execution and reporting live in one place. Explore Skai’s omnichannel marketing platform for unified cross channel management and clearer performance visibility.
What are the Skai iROAS core requirements for a tailored transparent and actionable incrementality solution?
- Skai built iROAS around six core requirements.
- Tailored experiments plus transparent inputs drive trust.
- A strong solution supports configurable design, granular measurement choices, and meaningful outputs marketers can act on immediately. It should show how results were derived, adapt to different retailer constraints, and help teams continuously improve incrementality rather than treat it as a one off reporting exercise.
At Skai, we’ve built our iROAS solution with one goal in mind: to address the real-world challenges of retail media measurement. Incrementality should never be a buzzword; it should be a strategic suite of solutions that empower marketers to refine their approach and make smarter decisions.
We believe that the iROAS core requirements are threefold:
First, transparency is foundational to building trust in any measurement solution. Many vendors offer black-box iROAS calculations, leaving marketers unclear on how calculations are made. This can be compared to fumbling for a light switch in a dark room—it’s inefficient and frustrating. That’s why Skai prioritizes clarity. Our solution offers full visibility into data inputs, methodologies, and assumptions so marketers can confidently act on insights – understanding the inputs required to optimize the outputs.
Second, customization is essential because no two brands, campaigns, or goals are alike. Skai’s iROAS solution adapts to each business’s unique needs, whether that means aligning calculations with product categories, price points, or campaign setups. Measurement isn’t one-size-fits-all, and it’s critical that tools reflect this reality. Incrementality solutions like iROAS require context before blindly making optimization decisions. Without it, brands are left guessing which levers to pull.
Finally, keyword granularity isn’t just a ‘nice to have’ but a true need. By delivering insights at the keyword level, we help marketers get closer to customer intent and make precise optimizations. Granular insights help marketers turn data into action, especially at the keyword level. This level of detail bridges the gap between strategy and execution, enabling marketers to refine campaigns with confidence.
By combining transparency, customization, and granularity, Skai’s iROAS solution equips marketers to not just measure impact but to use those insights as a competitive advantage.
Teams that operationalize these requirements can turn measurement into a repeatable growth loop. See how Skai’s retail media solutions support marketplace advertising at scale with the controls needed for incrementality driven optimization.
What questions should you ask when evaluating an iROAS solution?
- How transparent is your iROAS calculation process? Can you provide visibility into your measurement’s data inputs, methodologies, and assumptions?
- Does your solution allow for customization to align with our business needs? For example, can it tailor the metrics to account for unique factors like campaign setup, product categories, or specific business objectives?
- What level of granularity does your solution offer? Can it access insights at the keyword level or other detailed metrics that allow for actionable decision-making?
- How does your solution handle cross-publisher measurement and standardization? For instance, can it provide parity across networks like Amazon and Walmart, and how does it manage differences in metrics or attribution windows?
- What level of support and integration does your solution offer? How easily does it integrate with existing tools, and what support is provided for onboarding and ongoing optimization?
- How does your solution ensure scalability for evergreen incrementality measurement? Does it allow for always-on measurement, and how does it adapt to changing data availability or campaign structures over time?
How can you elevate retail media incrementality for long-term growth?
- Incrementality is now a competitive advantage.
- iROAS turns lift into better spend decisions.
- By adopting a transparent, tailored, and actionable iROAS framework, brands can overcome retail media complexity and measure true performance across retailers. The result is more confident optimization, less wasted budget, and a repeatable system that proves what is actually driving incremental revenue and growth.
The retail media landscape is evolving, and so should the way we measure success. Metrics like iROAS are a strong starting point, but they’re only as effective as the context and customization behind them. The future of retail media measurement lies in incrementality solutions that go beyond surface-level insights to deliver actionable, always-on guidance.
For marketers, this means shifting from one-off tests to scalable strategies that refine how they spend, not just where they spend. With Skai’s tailored approach to iROAS, I believe we’re equipping brands to turn measurement into a competitive advantage.
Incrementality isn’t just about proving the value of your campaigns; it’s about driving smarter, long-term growth. And that’s a goal worth pursuing.
Related Reading
- ROAS jumps 113% YoY as Lewis Media Partners Scales Walmart Connect for Sauer Brands ROAS more than doubled year over year while scaling spend, showing how disciplined optimization and measurement can unlock profitable growth in retail media portfolios.
- PepsiCo unlocks over 80% new-to-brand ROAS with Skai capabilities for Amazon DSP A test and learn approach improved new to brand efficiency, illustrating how structured experimentation and clearer incrementality signals can guide expansion decisions.
- Manuka Doctor’s Amazon DSP achieves a +53% ROAS increase using Skai’s Advanced Automated Actions Automation scaled upper funnel activity while improving ROAS, reinforcing the value of repeatable rules and transparent performance feedback loops.
Frequently Asked Questions
What is retail media iROAS?
Incremental lift per dollar spent.
Retail media iROAS estimates how much additional revenue a campaign generated beyond what would have happened anyway, then compares that lift to spend. It relies on a credible baseline (such as a control group or pre/post design) so you optimize toward true growth rather than attributed conversions.
How do I set up an always on iROAS measurement program?
Start with a consistent test calendar, define the decision you will make from results (budget shifts, bidding rules, audience expansion), and standardize baselines per retailer. Keep inputs stable, document assumptions, and refresh tests with enough volume to remain statistically credible as seasonality, pricing, and assortment change.
Why isn’t my iROAS result stable across retailers?
Common issues include inconsistent baselines, different attribution windows, limited data access in walled gardens, and mismatched granularity (keyword versus product). Align definitions first, then hold methodology constant while changing only one variable at a time so differences reflect real performance rather than measurement drift.
Retail media iROAS vs ROAS: Which is better?
ROAS is useful for directional efficiency within a single system, especially when attribution is consistent. iROAS is better when you need causal lift and budget confidence, such as comparing retailers, validating upper funnel tactics, or defending incremental growth to finance. Many teams use ROAS for pacing and iROAS for strategy.
What’s new with retail media incrementality measurement in 2025?
More brands are increasing retail media investment while calling out measurement as a barrier, pushing demand for clearer standards and transparency. In parallel, industry groups have expanded guidance for consistent definitions and offline formats, which helps teams compare outcomes more reliably and operationalize always on incrementality programs.
Glossary
iROAS: A measurement approach that expresses incremental lift (sales or profit above a baseline) relative to ad spend, so teams can optimize toward true growth rather than attributed outcomes.
Incrementality: The causal difference between what happened with advertising and what would have happened without it, typically estimated using experiments or credible quasi experimental baselines.
Control group: A comparable set of shoppers, regions, or time periods that does not receive the treatment, used to create the baseline needed to calculate incremental lift and iROAS.
Granularity: The level at which results are measured (such as keyword, product, or audience). Granularity affects actionability and stability, because finer detail can guide optimizations but often requires more volume for confidence.