News Round-up: Revising Advertising Standards, AI Chatbots Cause Revenue Concerns, & More
In early March, The Current reported that business-to-business (B2B) ad spend is expected to increase in 2023, up 9.3% from 2022 and 58% from 2020. This increase has led B2B marketers to seek out new tools to harness better understanding from data-driven insights.
In mid-March, MarTech Series discussed the ad industry effort to revise digital advertising Standard Terms and Conditions. A joint effort between 4A’s, IAB, and ANA, all three agencies stressed that while industry standards still remain the same as a decade ago, there have also been changes and evolutions that require revisiting the framework. According to ANA CEO Bob Liodice, “The scale and complexity of today’s digital media transactions requires an updated foundation of contractual terms and conditions that underpin this large marketplace.”
AdExchanger looked at the role of data clean rooms, seeking to better define their purpose. They stated that the vast majority of advertisers were concerned about audience trust being affected by online privacy changes, with the worry that “consumers will stop buying from them if they feel their data privacy is not respected.” As a result, advertisers want to build relationships with publishers, as they have behavioral insight into first-party data. AdExchanger believes that publisher cohorts will “model advertiser data across publisher first-party data,” assisting advertisers in reaching their audiences.
The New York Times recently spoke to several publishers who expressed concerns that AI chatbots will cause a decline in traffic on their websites. Because chatbots relay full answers to user queries, users may have little reason to visit the website, which would cause a reduction in publisher revenue. Various news sites chimed in, with News Corp’s chief executive, Robert Thomson, stating that he believes that “tech companies should pay to use publishers’ content to produce results from A.I. chatbots” as those search results are generated by pulling information from various websites.
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