The academic study at the heart of this presentation compared 13 hierarchy-of-effects (HoE) advertising models to determine which model matters the most, what moderators are most prominent, and what factors and sequence are most important in driving sales. Understanding the sequence of effects is most important for advertisers and marketers as they build their campaigns.
Kara Manatt (Magna) and Heather O’Shea (Snap) presented research that compared :06 second and :15 second ad lengths across three video platforms – Snap, video aggregators, and full episode players (FEPs) – to determine the optimum ad length for an effective ad strategy.
In testing the same :06 and :15 ads for the same four brands, the study factored in the characteristics of each platform – pre-roll/mid-roll, skippable and non-skippable, and device – as it tracked 7,500+ panelists’ viewing behaviors for brand awareness, brand perception, and purchase intent.
Ariane Le Port of Google explored the relationship between augmented intelligence and creative effectiveness on YouTube. She noted that in the past, measuring creative was a challenge that was “so nuanced and so complex” that people tended to shy away from measuring it. In this session, Ariane pointed to a six-year experiment on YouTube video ads to help brands understand what is most effective in mobile video. In the experiment, they conducted A/B testing and took into account a variety of areas, such as framing, pacing, audio and other areas to find patterns of creative effectiveness. These experiments led to a partnership between Google and Ipsos to create YouTube’s ABCDs (Guidelines) for creative effectiveness. YouTube and Ipsos studied 17,000 ads in an effort to identify the creative elements that have a measurable impact, using a human and machine learning (ML) approach. Leveraging machine learning (ML) enabled them to look at large and robust datasets to gain a deep understanding of what elements work best in creative. Ariane discussed their augmented intelligence methodology which included data scope and collection, human and machine creative coding, metrics and data modeling and insights and commercialization.
On June 7, 2023, attention economy experts came together in NYC to share case studies and participate in engaging discussions on the attention measurement landscape. Plus, attendees heard a recap of the issues debated at AUDIENCExSCIENCE and an update on Phase I of the ARF Attention Validation Initiative, an empirically based evaluation of the rapidly developing market for attention measurement and prediction.
Member Only AccessMaggie Zhang of NBC Universal invited all the presenters back to a wrap-up session called “Attribution Pivot,” where she asked what challenges marketers are facing and how they are meeting them. Each provided insight into important attribution challenges that they as a marketer or their client is facing. Limitations include lacking the ability to do A/B testing, privacy issues and the looming issue of cookie depreciation. It is also difficult to determine long-term lift, such as lifetime value.
Data scientists at Spotify’s self-serve advertising platform examined their use of attribution to understand the role of different media channels and their contributions to an advertiser signing up and spending on Spotify’s ad platform.
Carl Mela (Duke University) helmed a panel of the day’s presenters to further review the “vanguard work of MMM in 2022.” Granularity inspired the most debate among the panelists, with other topics including causality, cadence of modeling vs. decision-making, false trust in priors, marketing mix model (MMM)’s worst mistakes and lack of precision, and methods for long-term ROI and branding meriting discussion.
In this session, Ross Link (Marketing Attribution) and Jeff Doud (Ocean Spray Cranberries) examined a large-scale experiment conducted with Ocean Spray. They applied randomized controlled trials (RCT) to approximately 10 million households (30 – 40 million people) in which ads were consumed by their participants via a variety of devices. Jeff explained that the experiment was done to measure the impact of when certain ads were suppressed for some of their participants. Additionally, they examined an MTA (multi-touch attribution) logit model that was subsequently applied, which yielded KPIs such as ROI. Information from this MTA-RCT experiment supplied refreshed results monthly. Daily ROI results from the campaign were collected from the MTA-applied modeling. Outcomes from this experiment revolved around retargeting and recent and lagged buyers. In addition, the study also explored creative treatments and platform effectiveness.
Victoria Schiappacasse from Mercado Libre, a Latin American ecommerce technology company, described the reasoning behind and steps involved in implementing Meta’s open-source GeoLift, an incrementality application, in-house. As introduced by Meta’s Nicolas Cruces, the advantages of the free software bring value by “democratizing measurement.” Flexibility, user-friendliness and a robust support community are some of the other main advantages cited by Victoria and exemplified in two use cases.