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Forecasting & Optimizing Reach in a PII Compliant Measurement Ecosystem

Forecasting & Optimizing Reach in a PII Compliant Measurement Ecosystem

Spencer Lambert – VP, Product & Partnership Success, datafuelX

Matthew Weinman – Sr. Director, Advanced Advertising Product Management, TelevisaUnivision

Reach and frequency planning requires access to unique viewership data, which has become increasingly restricted due to identity restrictions. However, challenges exist with panel-only measurement, including the undercounting of Hispanic and Spanish language coverage, stated Matthew Weinman (TelevisaUnivision). Panel data undercounts Hispanics audiences by upwards of 20%, even for broad demographics. The benefits of big data exist across audience planning, viewership measurement and outcomes. Excessive frequency can be limited while maintaining or expanding reach, as well as improving ROAS. However, there are barriers to working with big data, including PII compliance. Additionally, the size and scale of big data leads to lengthy ID forecast times and computing costs. Spencer Lambert (datafuelX) presented details of their approach to ID-level forecasting which included their reach and frequency clustering methodology. Key takeaways:
  • Advantages of clustering methodology over identity methodology for reach and frequency:
  • Efficiency and accuracy: Delivers comparable accuracy metrics
  • Lower error rates: Seven percent for cluster reach forecasts vs. 20% error rate on identity-scaled reach forecasts
  • Cross-platform reach and frequency: By scaling cluster assignments to digital IDs, this methodology can empower cross-platform management and optimization
  • Lower compute time and costs
  • PII compliant: Preserves the use of identity-level planning

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CTV Ads: Viewer Attention & Brand Metrics

CTV Ads: Viewer Attention & Brand Metrics

Rohan Castelino – CMO, IRIS.TV

Mike Treon – Programmatic Lead, PMG

Representing the Alliance for Video Level Contextual Advertising (AVCA), Rohan Castelino (IRIS.TV) and Mike Treon (PMG) examined research conducted with eye tracking and attention computing company, Tobii. The research endeavor focused on the impact of AI-enabled contextual targeting on viewer attention and brand perception in CTV. Beginning the discussion, Rohan examined challenges with CTV advertising. He noted that advances in machine learning (ML) have empowered advertisers to explore AI enabled contextual targeting, which analyzes video frame by frame, uses computer vision, natural language, understanding, sentiment analysis, etc., to create standardized contextual and brand suitability segments. Highlighting a study of participants in U.S. households, the research specifically aimed to understand if AI-enabled contextual targeting outperformed standard demo and pub-declared metadata in CTV. Additionally, they wanted to understand if brand suitability had an impact on CTV viewers’ attention and brand perception. Results from the research found that AI-enabled contextual targeting outperformed standard demo and pub-declared metadata in CTV and increased viewer engagement. In closing, Mike provided the marketers’ perspective on the use of AI-enabled contextual targeted ads and its practical applications. Key takeaways:
  • Challenges with CTV advertising: Ads can be repetitive, offensive and sometimes irrelevant, in addition to ads being placed in problematic context.
  • In addition, buyers are unsure who saw the ad or what type of content the ad appeared within. A recent study by GumGum showed that 20% of CTV ad breaks in children’s content were illegal (e.g., ads shown for alcohol and casino gambling).
  • Advertisers have begun experimentation with contextual targeting in CTV, as a path to relevance.
  • A study conducted with U.S. participants that examined the effects of watching 90 minutes of control and test advertisements, using a combination of eye tracking, microphones, interviews and surveys to gather data found that:
    • AI-enabled contextual targeting attracts and holds attention (e.g., 4x fewer ads missed, 22% more ads seen from the beginning and 15% more total ad attention).
    • AI-enabled contextual targeting drives brand metrics (e.g., 2x higher unaided recall and 4x higher aided recall).
    • AI-enabled contextual targeting increases brand interest (e.g., 42% more interested in the product, 38% gained a deeper understanding).
  • Research to understand if brand suitability had an impact on CTV viewers’ attention and brand perception found that:
    • Poor brand suitability makes CTV viewers tune out ads and reduces brand favorability (e.g., 54% were less interested in the product, 31% liked the brand less).
    • AI-enabled contextual targeted ads are as engaging as the show.

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If You Stream It, They Will Come: Marketing Through Streaming Platforms

If You Stream It, They Will Come: Marketing Through Streaming Platforms

  • MSI

Livestreaming platforms and social shopping in general have grown into marketing channels that can be very lucrative for several different categories. However, livestreaming stands apart from “normal” social media in the fact that influencers are less reliant on corporate sponsors, as they have their own customer base that they rely on. So, how can marketers be successful within these channels? This Marketing Science Institute (MSI) working paper illustrates what forces are at play with livestreaming and how to balance them for the benefit of all parties.

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How Viewers are Changing

  • Posted: February 1, 2024

A new LA Media Research Council event featured insights from 2023 research, new studies on changes in behaviors and discussions about 2024 priorities. Read more »

The 6th Annual Privacy Study

The 6th Annual Privacy Study

One of the ARF’s most popular reports for membership and the press, the 6th Annual Privacy Study has now been released. The study surveyed 1,329 American consumers in the spring of 2023 on a Qualtrics online sample and platform. The report contains perennial questions regarding device usage, trust in institutions and how well privacy terms are understood. Last and this year’s versions also investigated what changes in information the public is willing to share and under what circumstances they are willing to share it. A new aspect to this year’s study is that it contains longitudinal findings across all six years.

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Making the Right Impression

Making the Right Impression

  • INSIGHTS STUDIOS

Key Takeaways

Paul Donato – Chief Research Officer, ARF Pete Doe – Chief Research Officer, Nielsen Pete Doe brought some clarity to how Nielsen currently approaches linear TV measurement and how it will evolve throughout 2024 in this detailed presentation, describing Nielsen’s integration of big data with panel data in its national TV measurement, participation in auditing and accreditation, exploration in defining impressions and conversations with the industry about time requirements and duration weighting. Other topics discussed in the Q&A that followed covered definitions of calibration and campaign reach measurement, panel adjustments for STB/ACR data, personalization and the differentiation between 30-second ads, 15-second ads and 60-second ads in terms of equivalization and measured impressions. These are selected excerpts from the session’s presentation and Q&A:
  • While big datasets are necessary to capture the fragmentation in the market, panel measurement—with its details on the persons viewing and devices being used—is essential to create a holistic view of audiences. Nielsen’s philosophy does not prioritize one over the other; instead, each informs the other.
  • After listening to industry publishers, agencies and clients, Pete assured the audience that Nielsen will still be offering C3 and C7 metrics in addition to new offerings of individual commercial metrics as of September 24th, 2024. He outlined a three-step process in Nielsen’s overall approach to its big data solution, starting with providing one year of impact national STB (set-top box) data that will then be audited by the MRC and submitted for accreditation. Pete noted that some clients were open to using non-accredited data in the interim, with buyers and sellers agreeing to available data that enables transactions.
  • Nielsen’s currency roadmap for 2024 begins with the currently available data streams that include both panel-only C3 and big data. They are planning to extend their national big data to include Comcast’s STB data calculated from sub-minute crediting in January and fully release their new currency combination of panel and big data, produced to C3 and C7 standards, in September, subject to auditing and accreditation processes. Pete also provided details on Nielsen’s approach to local TV measurement by introducing a calibration methodology, along with top line national demo findings in age groups and increases in Hispanic and Black audiences from Q1 2023.
  • Pete addressed the importance of having a consistent definition of an impression and how Nielsen worked to achieve more granularity in measurement with the sub-minute level of data. Referencing the MRC’s cross-media measurement standard and the continued debate around time requirements (at least two consecutive seconds) and duration weighting, he said Nielsen found no complete consensus from different sides of the industry, although there seems to be more support for two continuous seconds without duration weighting. Nielsen’s exploration in defining impressions assumed that equivalization as a kind of duration weighting will be assessed as deals are made.
  • Nielsen compared the impact of 1s, 2s and 5s using their sub-minute panel plus big data measurement against panel data and the average commercial minute, and, when adding duration weighting, found significant differences in impressions across varying age groups, households and day parts.
  • In terms of deals, one of the benefits of moving from the average commercial minute in a program to individual commercial metrics is the ability to look at the position in the commercial pod. In an example from a daytime broadcast show, Pete illustrated how first-in-pod ads typically deliver a higher audience than the rest of the ads in the pod, finding 99 percent of ads in the first pod indexed higher with 18 percent higher impressions than the average across 160 placements.
  • Nielsen’s national measurement’s “big data” encompass 30-35 million homes including Comcast, DirecTV and DISH return-part-data (RPD) from STBs. Smart TV ACR data from Roku and Vizio adds to the 30-35 million total with some overlap. In local markets, Nielsen does not currently use smart TV data as local stations are not all measured or supplied in its numbers so they focus instead on RPD augmented with Charter data. Because of its deals with DirecTV and DISH, Nielsen has a presence in every market.
  • Nielsen has streaming meters in about 50% of the homes in its national panel currently and is focusing on building those numbers. It also has local CTV measurement capability.
  Nielsen’s key takeaways:
  • Panel+big data means higher audiences, better stability, fewer zero ratings.
  • Overall patterns of viewing are pretty consistent between panel and panel+big data.
  • Two-second qualifier increases available impressions, while duration weighting deflates them.
  • Individual commercial minute data enables pod position considerations in deals.
 

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Navigating the Evolving Media Landscape

Navigating the Evolving Media Landscape

  • OTT 2023

The media landscape continues to evolve, arguably at a faster rate than ever. Leading media and measurement experts presented research-based insights on how viewers use different forms of TV/video on various platforms. Attendees joined us at the Warner Bros. Discovery Studios in California and via livestream to understand the latest data and discussions of the data’s implications.

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Viewers Like Choices

  • Posted: October 20, 2023

A new survey confirms viewers’ preference for choices – including whether a streaming service carries ads or not.        Read more »

Too Many TV Choices?

  • Posted: September 20, 2023

“Choice Paralysis” is a well-established concept that describes consumers’ confusion and hesitancy in making choices when there are too many options. Is this an issue for viewers of streaming services?  

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