Context has been a factor in ad buys for years with banking brands adjacent to financial news, new car ads placed in automotive sections and online verticals drawing viewers interested in food, gardening or fashion. Early on in the discussions about the demise of cookies, context was touted as one of the effective privacy-safe targeting alternatives. It still is, particularly since contextual targeting is now applicable to streaming.
AI-enabled contextual intelligence analyzes a video frame-by-frame to create standard and custom contextual segments and brand suitability segments for targeting and risk management. Iris.TV, which originally started as a video recommendation engine, has evolved with the creation of Iris_ids, a privacy-safe content data platform that allows advertisers to reach consumers through relevant content rather than by cookies or personal identifiers. Instead of just using keywords or browsing history, streaming platforms use content IDs to understand video assets and programming better. These IDs store data such as what’s happening in the video, logos, and even emotions.
Last August, Blue Ant Media announced its partnership with Iris.TV to add contextual audience targeting across all of its FAST channels globally to enable campaigns to be planned and executed in content relevant to a brand’s audiences.
Iris_ids give publishers more control over their data by essentially assigning unique identifiers to video assets, enabling publishers to access contextual data for more targeted ad placements in streaming platforms. This helps ads fit better with the content and makes sure they’re shown in safe places. Plus, advertisers can see how well their ads are doing and make changes if needed, making streaming ads even more effective. The Iris_ids are created for each piece of content sent by publishers with input from data companies before being uploaded into ad platforms.
Richie Hyden, co-founder and COO of Iris.TV, explains, “Publishers send us all of their video content including the video file, the metadata, transcripts, closed caption files, all of the data they have around an episode, video clip or movie. We create an ID for each video in our system so it’s a content ID not a people-based ID. We work with a lot of data companies that create segments and labels assigned to the content such as travel content or sports programming. Then it’s all onboarded into SSPs and DSPs so American Express, for example, can run an ad adjacent to travel programming because its audiences are big travelers.”
A study from AVCA, the Alliance for Video-level Contextual Advertising, was in field last August and September to explore the impact of connected TV (CTV) advertising on viewer attention and brand perception.
A nationally representative panel of 24 households that regularly watches ad-supported streaming TV was selected to watch over 1,000 ad experiences. To simulate the CTV experience, participants watched control and test content on their smart TV at home. They were allowed to have their phones and any other items they would usually have when watching TV. Half of the participants watched in pairs. Upon completion of the 90 minutes of programming, the participants were interviewed and surveyed
The research, conducted for AVCA by eye-tracking research company Tobii, found that ads targeted using AI-enabled contextual data outperform those targeted using standard demo and publisher-declared metadata. Viewers paid more attention to the ad, learned more about the product and were more interested in the products shown in AI-enabled contextually targeted ads.
Respondents frequently commented that ads were engaging even if the product wasn’t relevant and that they would remember the product and bring it up in conversation. The report revealed that viewers are sensitive to irrelevant and brand ad placements that are unsuitable, resulting in reduced attention and increased negative perception of the brands and products appearing in the ads.
Panelists also recalled twice as many brands from AI-enabled contextually targeted ads compared to publisher-declared and demographically targeted groups. When given a list of brands to select, panelists recalled four times as many brands from contextually targeted ads compared to publisher-declared and 50% more than the demographic group.
Iris.TV is a data platform built for video and CTV to structure, connect, and activate video-level data to create better viewing experiences and advertising outcomes. The Iris_id content identifier enables the building of scalable advertising solutions for contextual and brand-suitability planning, targeting, and measurement.
