AI/ML

The ARF Member AI Workshop

The ARF Member AI workshop introduced members to the potentialities of various AI platforms and tools to boost their work productivity. The workshop covered how LLMs such as Copilot, ChatGPT, Gemini and Claude can be employed in three main areas: presentations and reports, advertising research and meetings. Issues such as privacy and security of using AI, as well as the current limitations and challenges of the technology were also discussed. The hands-on, interactive workshop was an opportunity for all those interested in best practices and guidelines for using AI to learn how to interweave such programs into their daily work processes.

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Predicting Attention to Advertising Through Machine Learning

Privacy regulations have served as the impetus for a renewed interest in contextual targeting. To be effective, an ad must be related to its context but different enough to stand out. This working paper from the Marketing Science Institute (MSI) at the ARF presents a comprehensive model leveraging eye-tracking data and XGBoost algorithms to forecast the effectiveness of ad placements in real time.

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Generative AI Can Make Ad Creative Better Than Humans Alone

Have we reached the John Henry moment in ad creative where the machine can outperform a human in creating visuals for ads? Not quite. Generative AI does have a place in creative, however. This Marketing Science Institute (MSI) working paper found that GenAI when trained on ads which were rated the most effective by consumers can create ad visuals and text that outperform the originals in KPIs related to the purchase funnel and brand associations. Yet, the human element has not been cut out just yet. In fact, it might be pivotal to the process. The human AI combo saved time and effort and created pleasing visuals while maintaining a brand’s distinctive positioning.

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Research to Improve AI

Yes, AI is a great tool for marketers. But how can we avoid the “AI Conundrum” – taking advantage of its strengths while avoiding its errors and risks?    

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AI at a CPG Company

Colgate-Palmolive reveals how AI helps them achieve key objectives and improve processes. They  provided insights into the use of AI in marketing at AUDIENCExSCIENCE as well as MSI’s Summit 2024.

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Driving Greater Campaign Reach and Relevancy Across Formats

Sharmilan RayerGM, Amazon Publisher Cloud


Sharmilan Rayer of Amazon Publisher Cloud discussed an approach to empowering addressability as legacy identifiers (cookies and mobile IDs) fade. This approach, called durable addressability, includes the sharing of first-party signals across publishers, advertisers and third parties. Its three pillars are first-party signal investment, secure signal collaboration and machine learning (ML) powered modeling. The Amazon Marketing Cloud is their new advertiser clean room which takes this approach. It allows advertisers to combine their first-party signals with Amazon’s publisher ones and any third-party’s in a privacy compliant way. Key takeaways:
  • Durable addressability starts with each member investing in first-party data from a resource, funding and technology perspective.
  • Sixty percent of advertisers report planning to leverage first-party data for ad placements, and 47% of publishers say their first-party data is the answer to cookie deprecation.
  • The first-party data advertisers would bring to this strategy includes customer engagement, conversions and proprietary audiences.
  • Amazon has access to publisher first-party data across CTV, web, mobile and audio. Having access to this first-party data allows for determining which ad opportunities are best for a particular campaign.
  • As cookies deprecate, clean rooms will begin playing a more important role, according to Amazon.
  • Modeling by machine learning has increased reach 20-30% on unaddressable supply, Amazon claims.
  • A new product called Performance Plus combines Amazon Ads signals, advertiser conversion signals and machine learning to generate predictive segments. It has been observed boosting conversions 30-80%.

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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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