Stellantis, the multinational automotive group, has published details of a global attention measurement program it ran with Integral Ad Science and Publicis Media, covering more than 13 billion impressions across 19 countries and yielding a 165% increase in engagement on high-attention inventory - along with a 33% improvement in ad recall for key audiences.

A program built on scale

The case study, published by IAS on June 4, 2026, describes what both companies characterize as one of the richest and most diverse attention datasets assembled in the advertising industry to date. The initiative was not a single campaign test. According to IAS, the program launched in 2024, ran for more than six months globally, and extended to as long as 18 months in key markets such as France.

The scale involved is worth pausing on. Over 13 billion impressions were measured across more than 20 Stellantis brands and services - a group that includes Peugeot, Alfa Romeo, Jeep, and others. Stellantis itself was formed in 2021 through the merger of Fiat Chrysler Automobiles and the PSA Group, making Peugeot, founded in 1810 and builder of its first steam-powered vehicle in 1889, one of the oldest brands in the portfolio. That context matters: a group managing more than 14 distinct automotive marques faces an inherently complex media planning challenge, and standardizing measurement across all of them was central to what this program attempted.

The three parties - Stellantis, Publicis Media, and IAS - deployed IAS Quality Attention across Stellantis's open web programmatic campaigns as the primary measurement layer. Rather than using attention as a single-point campaign KPI, they developed a broader strategic roadmap that combined continuous measurement across eligible media environments with deep global and local market analysis, dedicated qualitative and quantitative research, and cross-analysis with established media quality metrics including viewability, fraud detection, and brand suitability.

What Quality Attention actually measures

Understanding the results requires understanding what the measurement product actually does. IAS launched Quality Attention in partnership with Lumen Research in early 2024 as what it described as the first product in the industry to unify media quality metrics with eye-tracking data and machine learning. Lumen's technology provides the eye-tracking layer, which IAS then combines with signals around visibility, situational context, and user interaction behavior.

The visibility dimension captures viewability, video quartile completion, and time-in-view. The situational dimension covers ad density, ad share of screen, and device and format type. The interaction dimension tracks user scroll behavior, pauses, resumes, skips, starts, and volume changes. According to IAS, these three dimensions feed a machine learning model trained on billions of impressions and millions of conversion events, generating a composite score - with above-average attention defined as a score of 65 or higher on a scale to 100, and below-average attention defined as scores between 1 and 64.

IAS expanded Quality Attention to mobile in-app environments in July 2024, extending the measurement beyond open web display and into one of the fastest-growing ad environments globally.

The Stellantis program relied on Lumen data specifically for predictive modeling within the Quality Attention framework. It also activated Total Visibility, IAS's supply path optimization product, to link attention data with financial efficiency metrics - allowing Stellantis and Publicis Media to understand not just where attention was being captured, but at what cost.

Different markets, different attention drivers

One of the more practically useful findings in the case study is the degree to which attention drivers varied by geography. The analysis did not produce a single universal optimization playbook. Instead, it found that the signals driving attention performance differed meaningfully across markets and media environments.

In the United States, visibility emerged as the primary driver. Across European markets, less cluttered media environments and stronger share-of-screen dynamics had a greater influence on performance. These distinctions shaped how Publicis Media refined its optimization frameworks: the methodology was applied market by market, rather than applied uniformly at a global level.

That market-level granularity has a direct operational consequence. According to IAS, it enabled Stellantis to evolve media allocation strategies with greater precision. Lower-attention environments were used more deliberately for lower-funnel objectives where repetition and cost efficiency matter most. Higher-attention environments were reserved for premium storytelling, immersive creative formats, and key product messaging where brand-building exposure carries more weight.

The program also introduced what IAS describes as an ongoing optimization model - treating attention not as a static measurement taken at the end of a campaign, but as a continuous signal used to improve performance in-flight over time.

The numbers from the Dynata study

The performance metrics reported in the case study split into two categories: engagement and conversion data from the programmatic campaigns themselves, and brand lift outcomes measured through an independent study conducted with Dynata.

On the campaign side, according to IAS, high-attention inventory produced a 165% increase in engagement. Click-through rates on high-attention formats increased 165%. Conversion rates improved 29%. The cost per thousand metric improved 16%, reflecting what IAS characterizes as better overall cost efficiency through quality-spend optimization.

The Dynata brand lift study focused specifically on the French market and targeted males aged 18 to 44 - Stellantis's main target demographic for the campaigns analyzed. The study compared outcomes between those exposed to above-average attention placements (scores of 65 and above) against those exposed to below-average attention placements (scores between 1 and 64). The sample comprised 61 control respondents and 32 above-average attention respondents.

Among that demographic, aided awareness was 12% higher among those exposed to high-attention placements, measured at 90% confidence. Ad recall improved by 33%, also at 90% confidence. Brand favorability increased 18%, measured at 80% confidence. According to IAS, the Dynata study validated the connection between attention quality and brand KPIs specifically within the target demographic, offering evidence that the attention signal correlates with measurable shifts in consumer perception.

Alix Tanniou, Media Manager at Peugeot France, is the named spokesperson in the published materials. "Without measurement, you're navigating blindly," she said. "Our media investments need to become increasingly effective and profitable, so understanding their real impact is crucial for us. That's what we aimed to achieve with IAS solutions, which go beyond traditional measurement. Advertising attention is a key challenge and reflects a broader industry shift toward identifying new, effective signals. To sustainably adopt this KPI, we needed proof. Working with Publicis Media and IAS was essential. With Quality Attention, we achieved very positive full-funnel results, validated through two large-scale studies - a brand lift study and a performance impact study - demonstrating the effectiveness of this new KPI."

Why this matters for the programmatic market

The marketing community has been debating the limits of viewability as a primary media quality metric for several years. The argument, as PPC Land has covered in detail, is that an impression being technically viewable - meeting the MRC's standard of 50% of pixels visible for at least one continuous second for display - does not itself indicate that a real person paid attention to it. Attention measurement has gained traction throughout 2024 and 2025 as a more sophisticated layer, but industry participants have disagreed about how reliably attention scores translate into business outcomes.

The Stellantis program attempts to answer that question with data at meaningful scale. Thirteen billion measured impressions across 19 countries over up to 18 months is substantially larger than most published attention case studies. The inclusion of an independent third-party brand lift study via Dynata, rather than relying solely on in-campaign performance data, adds a layer of external validation that attention proponents have argued is necessary to build advertiser confidence in the metric.

The finding that attention drivers differ by market also has practical implications. A media planner optimizing campaigns across Europe cannot simply apply a single attention framework uniformly. The US-vs.-Europe distinction identified in this program - visibility driving attention in the US, share of screen and clutter reduction doing so in Europe - suggests that attention optimization requires localized calibration. That raises the operational bar, but it also suggests that campaigns which do invest in that calibration may gain a competitive edge in media efficiency.

Attention measurement has also started moving beyond measurement into active optimization. IAS launched an attention optimization tool in December 2024 that demonstrated up to 130% conversion rate lifts when comparing high- versus low-attention impressions. The company partnered with Mastercard in March 2026 to connect media quality signals directly to purchase data, moving attention from a reporting metric into an active pre-bid targeting layer. IAS also introduced Total TV in April 2026, bringing show-level transparency to connected television buying - an extension of the same logic that attention data should inform where money goes, not just report on where it went.

The broader industry context for attention measurement is still developing. The Media Rating Council and the IAB finalized comprehensive attention measurement guidelines in November 2025 following a public comment period. Standardization across providers remains unresolved - different vendors use different methodologies, making cross-vendor comparisons difficult. For the Stellantis program, using a single provider across 19 countries and more than 20 brands gave it methodological consistency that multi-vendor programs would lack.

IAS was acquired by Novacap for $1.9 billion in an all-cash deal in September 2025, transitioning the company to private ownership. Its platform analyzes up to 280 billion interactions daily across ad fraud detection, brand safety, contextual targeting, viewability, and attention measurement. In November 2025, IAS received MRC accreditation for third-party Amazon DSP measurement, marking the first independent verification of those specific metrics within Amazon's ecosystem.

The Stellantis case study also helps establish internal benchmarks - a prerequisite for any advertiser that wants to use attention as a recurring planning input rather than a one-time experiment. By building market-level and campaign-type benchmarks, Stellantis and Publicis Media now have a reference frame for evaluating future campaigns against their own historical performance. That institutional knowledge is harder to build than running a single test, and it is what separates a genuine shift in measurement practice from a pilot that never scales.

The automotive context

Automotive advertising occupies a specific position in digital media strategy. Car purchases are among the highest-consideration consumer decisions, involving long research cycles, multiple touchpoints, and significant variance between the moment of brand awareness and the moment of purchase. That makes full-funnel measurement both more important and more difficult than in categories where the purchase cycle is short.

The Stellantis program specifically examined how attention quality affected both brand and performance metrics - not treating them as separate measurement exercises but analyzing them together. The finding that high-attention inventory improved conversion rates by 29% while also lifting ad recall by 33% and brand favorability by 18% suggests the relationship between upper-funnel brand health and lower-funnel conversion performance is real and measurable, at least within the parameters of this study.

Peugeot France's involvement as the primary reporting brand within the case study is notable given France's position as one of the longer-running test markets - up to 18 months of continuous measurement compared to the six-month minimum in other markets. The longer measurement window gives the French market data more statistical reliability and more time for optimization effects to compound.

Timeline

Summary

Who: Stellantis, the multinational automotive group encompassing more than 14 brands including Peugeot, Alfa Romeo, and Jeep - working with Integral Ad Science (IAS) and media agency Publicis Media. Research validation was provided by survey company Dynata.

What: A global attention measurement and optimization program that deployed IAS Quality Attention across Stellantis's open web programmatic campaigns. The program covered more than 20 brands and services in 19 countries, measuring over 13 billion impressions. Key results included a 165% increase in engagement on high-attention inventory, a 33% lift in ad recall for the primary target demographic (males 18-44), an 18% improvement in brand favorability, and a 29% increase in conversion rates.

When: The program launched in 2024 and ran for more than six months globally, with deployments in key markets such as France running for up to 18 months. The full case study was published by IAS on June 4, 2026.

Where: The program operated across 19 countries, with France serving as the longest-running and most closely studied market. Measurement covered both desktop and mobile environments on the open web. The Dynata brand lift study examined the French market specifically.

Why: Stellantis and Publicis Media sought to demonstrate whether attention measurement could serve as a reliable signal for optimizing both media efficiency and business outcomes - moving beyond viewability as the primary media quality metric. The initiative aimed to establish internal attention benchmarks by market and campaign type, creating the foundation for a scalable global attention framework across the full Stellantis brand portfolio.