OOH Measurement’s Game Has Changed

Christina RadiganSVP, Research & Insights, Outfront

Christina Radigan of Outfront explored the advantages of out-of-home advertising (OOH) and discussed advancements in its measurement techniques. Christina noted that with the loss of cookies and third-party data, contextual ad placement will see a renewed sense of importance, and in OOH, location is a proxy for context, driving content. She further indicated the benefits of OOH citing a recent study by Omnicom, using marketing mix modeling (MMM), which found that increased OOH spend drives revenue return on ad spend (RROAS). This research also highlighted that OOH is underfunded, representing only 4% to 5% of the total media marketplace. Following up on this, Christina pointed to attribution metrics, measuring the impact of OOH ad exposure on brand metrics and consumer behaviors, to demonstrate OOH's effectiveness at the campaign level. Expanding on their work in attribution, she noted changes stemming from the pandemic: Format proliferation and greater digitization, privacy-compliant mobile measurement ramping up (opt-in survey panel and SDK) and performance marketing and measurement becoming table stakes for budget allocations. New measurement opportunities from OOH intercepts included brand lift studies, footfall, website visitation, app download and app activity and tune in. Finally, she examined brand studies conducted for Nissan and Professional Bull Riders (PBR), showcasing the effectiveness of OOH advertising in driving recall, ticket sales and revenue. Key takeaways:
  • MMMs return to the forefront, as models become more campaign sensitive and are privacy compliant (powered by ML and AI).
  • A study from Omnicom, using MMM, found that optimizing OOH spend in automotive increased brand consideration (11%) and brand awareness (19%). In CPG food, optimizing OOH spend increased purchase intent (24%) and optimizing OOH spend in retail grocery increased awareness (9%).
  • OOH now represents a plethora of formats (e.g., roadside ads, rail and bus ads, digital and print) and has the ability to surround the consumer across their journey, providing the ability to measure up and down the funnel, in addition to fueling behavioral research.
  • Key factors for successful measurement in OOH: feasibility (e.g., scale and scope of the campaign, reach and frequency), the right KPIs (e.g., campaign goal) and creative best practices (Is the creative made for OOH?).
  • OOH advertising is yielding tangible outcomes by boosting consumer attention (+49%). Additionally, there has been a notable surge in advertiser engagement (+200%).
  • Ad recall rates in OOH continue to increase (e.g., 30% in 2020 vs. 44% in 2023).

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2023 Attribution & Analytics Accelerator

The Attribution & Analytics Accelerator returned for its eighth year as the only event focused exclusively on attribution, marketing mix models, in-market testing and the science of marketing performance measurement. The boldest and brightest minds took the stage to share their latest innovations and case studies. Modelers, marketers, researchers and data scientists gathered in NYC to quicken the pace of innovation, fortify the science and galvanize the industry toward best practices and improved solutions. Content is available to event attendees and ARF members.

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Advertising Effectiveness: Performance Measurement in the New World of Privacy and Tools

  • Insights Studio

On July 26, measurement practitioners discussed how to adapt to this new era of privacy with tools for measuring ad performance effectiveness. Panelists explored new considerations for existing methods, such as marketing mix modeling (MMMs) and multi-touch attribution (MTAs), and discussed the pros and cons of various privacy enhancing technologies (PETs), including multi-party computation, clean rooms, and more.

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Transforming Media Planning & Activation at Walgreens through Unified Marketing Measurement

Walgreens’ three-year change management evolution, in partnership with Ipsos MM, embedded unified marketing measurement (UMM) into tactical and strategic decisions at the retailer. This approach to change management included simulated impact testing, validated results and provided proof points. Douglas Brooks of Ipsos MMA provided a current overview of UMM at Walgreens, which consists of monthly marketing mix models, weekly attribution models and continuous validation through testing. Jenny Peelle of Walgreens stated that this approach impacts decision making, including what businesses to support, reach and frequency management and an understanding of attribution for individual KPIs as well as for enterprise business growth objectives. The resulting shift to UMM increased revenue at both the business unit level and for the entire enterprise.

Holistic Cross-Media Measurement

Brendan Kroll – VP Performance Measurement, Nielsen

Anne Ori – Measurement Lead, CG&E, Google

Daniel Sacks – Incrementality Lead, US Agency, Google

Brendan Kroll of Nielsen and Anne Ori and Daniel Sacks, both of Google, explained that their study’s objective was to identify potential improvements to marketing mix models by utilizing enhanced prior beliefs (priors) based on sales lift studies and exploring the resulting changes in campaign-level sales lift once those priors were incorporated. Incrementality experiments are widely accepted as the gold standard for causal measurement. Calibrating individual channels via experimentation ensures optimization of model outcomes. However, the results of incrementality experiments are often not part of marketing mix model (MMM) design. Nielsen utilized NCS sales lift studies as the source of the experimental data for this analysis. NCS determined the causal effects of advertising on incremental sales while controlling for targeting and other co-variates. The study design involved 10 brands with existing MMMs and available NCS results for corresponding periods, model re-estimation using NCS lift priors, refinement of the priors and scaling. This study showed that applying this methodology to a YouTube campaign resulted in significant sales lift, as well as revenue and ROAS increases, including a 2.6x median increase in the effectiveness in the adjusted model. The adjusted model showed greater marketing contribution overall; therefore, marketers are at risk of undervaluing their overall marketing if experimental results are not included.

Key Takeaways

  • Brands can effectively leverage experiment-based priors to strengthen marketing mix models.
  • For nascent channels, the inclusion of experimentation results proved fundamental, especially if those campaigns showed strong initial results, since MMMs cannot rely solely on historical anchoring to measure true impact.
  • When experiments reveal high performing channels or campaigns, the use of testing can aid more accurate MMM measurements as investment scales.
  • Even for channels with long histories and relative stability, experimentation can serve as a way to validate models and may give models a chance to remain flexible in case of strategic shifts and/or changes in consumer behavior.

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Quote of the Week

“The clock is ticking. In September 2024, the currency we’ve all used for decades is going to disappear. That means no more year-over-year comps. Sorry, no more media mix models based on outdated TV metrics that are simple, siloed counting and was yesterday’s consumers.” Read more »

Attribution & Analytics Accelerator 2022

The boldest and brightest minds joined us November 14 - 17 for Attribution & Analytics Accelerator 2022—the only event focused exclusively on attribution, marketing mix models, in-market testing and the science of marketing performance measurement. Experts led discussions to answer some of the industry’s most pressing questions and shared new innovations that can bring growth to your organization.

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