effectiveness & ROI

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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AI Driven Video Formats Drive Results for Brands

Tori KangYouTube Specialist, Google

Danielle PerrellaHead of Measurement, Google

Tori Kang and Danielle Perrella from Google talked about AI from a media and video perspective with a summary of the overall landscape and an examination of how AI delivers on its promise in the ways it is working within Google’s YouTube. Tracing video’s effectiveness through the consumer funnel, Tori noted how the accelerating consumer complexity in viewing habits requires marketers to be more agile in navigating audience fragmentation, and AI’s capabilities are able to do the heavy lifting by saving time, optimizing efficiency and improving performance. Danielle illustrated how Google’s AI mechanism, Video Reach Campaigns, measured up against manually optimized campaigns and traditional YouTube formats in comparing ROAS and incremental sales. Key takeaways:
  • In improving reach and efficiency compared to manually optimized YouTube video campaigns, a Bubly case study showed using AI delivered 33% more reach at a 64% lower CPM.
  • Implementing AI earned an average ROAS 3.7x (+271%) higher than, and drove more than double the incremental sales (+111%) of, manually optimized YouTube video campaigns.
  • Identifying areas for optimization by finding inefficiencies, defining how AI can answer critical business questions and evaluating how AI can improve key metrics are the key questions for considering how AI should be integrated into a media plan.
 

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A Clean Room Incrementality Experiment – An Indeed Case Study

Joe ZuckerSenior Manager, Marketing Analytics, Indeed

Clean room experiments are challenging in an online marketplace, such as Indeed’s job site for employers and employees, due to potential online experimentation biases, including activity bias, ad server bias and base rate bias, according to Joe Zucker (Indeed). Control groups can be created in multiple ways with different degrees of technical setup or in some cases, external modeling. The five variations of control groups are ghost ads, publisher house ads, PSA ads, propensity score matching and intent to treat. A comparison indicated that each option has both pros and cons, including cost, the need for additional data or publisher support. Joe reminded the audience that there is “no free lunch.” Ghost ads would be preferred by Indeed to create the control group; however, this option has high technical set-up requirements, few publisher partners have this capability and there is low control over the analysis. There are also challenges related to interpreting experimental results, which include low match/conversion rates and the need to analyze experiments with different control group construction. Indeed was able to measure aggregate incrementality for their campaign metrics and prove the value of their advertising as a result of these clean room experiments. Key takeaways:
  • Despite the challenges of clean room experiments, these experiments are critical to the measurement of the incremental impact of advertising on KPIs.
  • Clean room experiments can ensure high quality continuous reporting with actionable analytics and insights while achieving user data privacy compliance.
  • Experimentation enabled Indeed to focus on new customers in a cookie-free, privacy-forward manner with the ability to verify advertiser data.

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Retail Media Networks, Generative AI Top JAR’s Industry-Informed Research Priorities

  • JOURNAL OF ADVERTISING RESEARCH

Retail media networks, generative AI across creative, market research and trust, ad effectiveness and attention: These are among the topics highlighted on the Journal of Advertising Research’s list of 2024 research priorities. The list is a result of one-on-one interviews with advertising professionals by Editor-in-Chief Colin Campbell, who asked: "What are your biggest needs and challenges?"

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Health, Charity and Green Messaging Highlighted in JAR Prosocial-Themed Issue

  • JOURNAL OF ADVERTISING RESEARCH

A JAR 2022 call for papers on prosocial advertising generated a deluge of submissions aimed at helping advertisers use more effective means of communicating in ways that benefit society. The result is the newly published March issue focused on messaging strategies that help consumers make informed decisions on health, the environment and charity.

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Too Much Attention?

One expert argues that attention alone does not bring ad success and that we should not forget the other important levels of the “ARF Model.”

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Cross-Platform Measurement Options from an Agency Perspective

Audience measurement is changing at an unprecedented rate. Concurrently, identifiers such as cookies are fading, and traditional models and incumbent suppliers are being questioned. In reaction to all these happenings, new measurement initiatives and a new Joint Industry Committee (JIC) have risen to establish a path toward a new video measurement framework. In 2023, the Online-Offline Metrics Working Group, within the ARF Cross-Platform Measurement Council, conducted anonymous, in-depth-interviews (IDIs) with eight key decision-makers from major agency holding companies. The IDIs focused on three major issues involving the metric situation confronting the advertising industry. This report summarizes the learnings from those interviews.

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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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