Chen from Connatix Explores How Context Plus Cookies Enhance Consumer Understanding

**Welcome to Connatix: Revolutionizing Contextual Advertising in the Digital Era**

In this video interview with Beet.TV, Jenn Chen, chief revenue officer at Connatix, unveils the power of deep contextual advertising and its relevance in today’s advertising landscape. As digital identifiers and third-party cookies become obsolete, the industry is witnessing a resurgence of contextual targeting strategies. Chen explains how Connatix is leading the charge in this new age of contextual advertising, leveraging AI, machine learning, and publishers’ video content to enhance ad targeting.

Founded in 2014, Connatix is a video technology company that offers publishers an end-to-end tech stack for creating, playing, monetizing, and optimizing videos[^1^]. Their platform integrates an ad server and exchange specifically designed for video, alongside built-in monetization formats. By mining publishers’ video content, Connatix can generate signals that power contextual ad targeting[^1^].

Chen describes deep contextual advertising as a groundbreaking approach that delves into the fundamental components of video signals. Connatix’s AI and machine learning technologies analyze various signals, including clips, images, and meta tags. By combining these elements, Connatix creates a targetable context and provides valuable insights for advertisers[^2^].

Recognizing the significance of contextual advertising in today’s industry landscape, Connatix is committed to surpassing the limitations of traditional contextual targeting approaches. Chen emphasizes that the new era of contextual advertising removes the dependence on third-party cookies, enhancing privacy and eliminating the “creepiness” sometimes associated with previous approaches[^3^].

Connatix’s deep contextual model combines its proprietary kinetics knowledge graph with metadata, keywords, and manual input from publishers’ editorial teams. By leveraging advanced technology, Connatix generates real-time, dynamic context, offering a superior alternative to static labeling and pre-formed taxonomies[^3^].

Brand safety and transparency have been prominent concerns for advertisers. In response, Connatix ensures high-quality content by establishing partnerships with over 3,000 validated publishers, such as Accuweather, Associated Press, and Forbes. These publishers employ dedicated teams to curate and maintain the quality of their inventory, providing a solid foundation for deep contextual analysis[^4^].

Regarding the future integration of contextual targeting and behavioral targeting, Chen states that the industry is still in a state of flux. As behavioral targeting evolves, a combination of both approaches is likely to emerge. Contextual targeting enables precise placement of ads based on the user’s current interests and behavior, creating a more effective advertising strategy and a better understanding of the consumer’s mindset[^5^].

Join Jenn Chen in this insightful interview as she unveils the power of deep contextual advertising and how Connatix is revolutionizing the advertising industry in the absence of third-party cookies and digital identifiers.

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Although behavioral targeting may appear on the rocks, the established digital ad tactic may not be completely shipwrecked.

Instead, a likely outcome is that the tactical correction now underway, thanks to the deprecation of digital identifiers, will lead to a balance of approaches.

In this video interview with Beet.TV, Jenn Chen, chief revenue officer, Connatix, explains how it will work.

Player to profit

Founded in 2014, Connatix offers publishers an online video player with built-in monetization formats, an integrated ad server and exchange built for video.

It also mines publishers’ video content to create signals that can power contextual ad targeting.

That tactic aims to place ads that match content, rather than ones which precision-target individuals, not unlike how analogue ad sales used to function.

Contextual 2.0

“The new age of contextual is quite different,” Chen says.

“Deep contextual, how we’re approaching it, is starting from sort of like the molecules and atoms, the actual fundamental pieces of video signals.

“We use AI and machine learning to look at different signals, such as clips and images, all the way through to looking at meta tags and what publishers use in in tagging their videos and combining it into something that makes sense at the higher order and making it something that is targetable and being able to provide insights from that as well.”

Connatix’s context

In 2021, Connatix  took new investment from Court Square Capital Partners, with money earmarked for M&A, global expansion and product innovation.

This year, the firm has:

Opened a Chicago office.
Hired Taboola’s Mike Renfro to head a Midwest operation.
Appointed a chief people officer, VP North America amid and chief revenue officer to manage growth.

The company works with more than 3,000 publishers, including McClatchy, Reuters, CBS Local and Accuweather.

Mixing methods

Chen sees contextual targeting as helping advertisers use a blended targeting approach.

“In the cookie world as we’ve defined it before, it’s like, ‘this person must be black or white’, this label,” she says.

“But that doesn’t evolve. It doesn’t change as they consume content.

“If you combine the benefits of contextual and understanding that background of the user, you come up with a much better, richer combination of both. That’s what I think will happen in the future.”

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