Media Monday
Summer Blockbuster & Fall TV Preview by Hollywood Joe
By Joe Antonini, Media Supervisor
Just like your Katie Holmes, Danny Devitos, and Jeremy Strongs, I myself made the transition from Television to Broadway.
Working for a TV client previously, we had many resources and made many presentations that mapped out the entirety of programming across the out-of-control landscape of broadcast, cable, streaming, DTC theatrical, in-theater theatrical, and so on.? While a lot to keep track of, the simple purpose was making decisions about zigging (aligning ourselves with similar or competitive content) or zagging (avoiding the clutter - this is more the client’s decision than ours).
As Streamers’ advertising offerings proliferate* (including programmatically), I have been getting asked by Account teams: Why Peacock over Max?? What’s going to be on in our flight?? It’s almost as if, had we not started encompassing Traditional TV buying capabilities at Situation, they would have encompassed us anyway!? The question is a great one (in addition to considering targeting capabilities and ad products for these newborn partners), though sometimes difficult to answer as Streamers - still participating in the old zig-zag game I left - keep a lot of programming announcements close to the belt.? That may change as we become more and more central to their revenue strategies.
Another zig we performed recently was with our Disney client.? They were able to provide us CRM data on Little Mermaid fans.? It was, obviously, a pretty large “pool”.? And we were able to send some 4,500 of them to the Lion King and Aladdin sites through TTD and Meta in the midst of their flurry of excitement for the new smash hit.
*As Streamers realize the financial ruin they are in and invite Advertisers back into the foray to save them
领英推荐
The Trade Desk Announces New AI Infrastructure, Kokai
By Jacqueline Watson, Media Buying Specialist, Paid Social
This past Tuesday, The Trade Desk announced advancements in their programmatic AI with the launch of Kokai (which means “open waters” in Japanese), a new approach for managing AI-based ad campaigns.
Kokai (based upon TTD’s pioneering AI work with Koa, launched in 2018) will distribute deep learning algorithms across all aspects of the programmatic media buying process within the platform, serving as a Trader’s co-pilot. While Koa assists advertisers with campaign set up and optimization based on KPI’s, Kokai provides a new comprehensive suite of advanced tools that leverage AI across various aspects of media buying on TTD’s platform. These new tools include predictive clearing, ad impression scoring based on relevance, bid management, targeting ads, measuring sales, and KPI scoring. Kokai will also feature new innovations in measurement and reporting tools that help analyze results from growing channels like CTV with the launch of “The TV Quality Index” (measuring the quality of ad experience across streaming platforms/content) and “The Quality Reach Index” (facilitates customer base expansion by targeting relevant customer profiles). During Kokai’s unveiling, TTD’s CEO Jeff Green also touched upon the future development of API’s (application programming interfaces), that would help incorporate AI into programmatic ad creation.??
Interested in learning more? Watch a recap of Kokai’s New York City launch event here.
Google Ads Trademark Policy Update
By Angie Holden, Paid Search Manager
Google Ads has announced an update to their Trademarks policy this week that's good news for advertisers. Starting July 24, 2023 Google Ads will only accept and process trademark complaints against specific advertisers rather than all advertisers in the trademark owner's industry. Over-flagging and long wait times for ad policy violation disputes have caused major problems for advertisers over the years. This policy update will reduce the number of industry-wide restrictions and make resolutions faster and easier. Although the policy is going into effect mid-July, advertisers can expect a gradual rollout over the next 12-18 months. You can read more about it, here.