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    Weekly Insights: PPC Industry News and Updates - 07/07/25

    By Christina McLeod
    5 minute read
    Weekly Insights: PPC Industry News and Updates - 07/07/25

    Google Introduces AI Max Match Type for Enhanced Search Campaigns

    Google Ads has introduced a new AI-driven match type, AI Max, which aims to simplify keyword targeting while maximising reach and performance. Currently in closed beta, AI Max is designed to automate the process of matching search queries with ads, using artificial intelligence to determine optimal targeting and bidding strategies. This development aligns with Google’s broader move towards automation in paid search campaigns.

    Advertisers opting into AI Max will no longer need to manage individual keyword match types such as broad, phrase, or exact. Instead, the new system evaluates search intent, campaign goals, and user behaviour in real time to deliver what Google claims is “maximum performance” with minimal manual input. Importantly, advertisers can still influence performance by providing keyword themes, exclusions, and conversion goals to guide the AI’s decisions.

    While the promise of increased efficiency is appealing, the update represents a significant shift in control. With traditional match types being bypassed entirely, advertisers will need to place greater trust in Google's algorithms. Additionally, this could make performance analysis more complex, as transparency around which queries triggered ads may be limited compared to current keyword-based approaches.

    From a strategic perspective, AI Max could benefit advertisers looking to scale quickly or those with limited resources to manage large keyword lists. However, it also introduces potential risks around ad relevance, wasted spend, and brand safety if not properly monitored. Advertisers are encouraged to approach the new match type with clear conversion tracking in place and robust negative keyword lists to maintain campaign quality. [1]

    Google Retires Tax Settings for U.S. Product Feeds

    Google has announced that tax settings will no longer be required within product feeds for merchants targeting the United States. This update simplifies the feed management process by eliminating the need for manual tax configuration, as Google will now automatically calculate applicable tax based on customer location and product type.

    The change, effective immediately, means advertisers no longer need to include tax information either at the account level or within individual product data in Merchant Center. Google’s systems will automatically estimate tax rates during the shopping ad auction, streamlining setup for retailers and reducing the risk of errors or feed disapprovals linked to tax discrepancies.

    This update reflects Google’s ongoing efforts to automate and simplify campaign management for advertisers, particularly in the eCommerce space. While this change currently applies only to U.S. feeds, it raises the possibility of similar automation being rolled out in other markets in the future.

    Importantly, advertisers must still ensure that pricing is accurate and complies with legal requirements, especially when targeting multiple states with varying tax regulations. Although Google is automating tax estimation for Shopping ads, the responsibility for tax compliance ultimately remains with the merchant. [2]

    Meta Introduces Enhanced Marketing Messages for Messenger

    Meta is expanding its suite of business messaging tools with the introduction of Enhanced Marketing Messages on Messenger. This new feature is designed to support customer retention by allowing businesses to send recurring, personalised messages to users who have opted in, offering an additional touchpoint for re-engagement within Meta's messaging ecosystem.

    These Enhanced Marketing Messages can be delivered to opted-in users over a 12-month period, giving businesses extended opportunities to share updates, promotions, or relevant content. Meta aims to provide more structured and efficient remarketing capabilities, helping brands nurture customer relationships beyond the initial point of contact.

    The rollout follows a broader trend of increasing personalisation and automation within digital advertising. Businesses can manage these messages through Meta’s Inbox or integrate them into existing workflows via the Messenger API, ensuring flexibility and scalability depending on the size or complexity of the operation.

    Importantly, consent remains a key component. Users must opt-in before receiving recurring messages, aligning with Meta’s ongoing commitment to privacy standards. Advertisers are encouraged to be transparent about the nature and frequency of their communications to maintain user trust and engagement. [3]

    Microsoft Advertising to Retire Target CPA and ROAS Bidding for New Campaigns

    Microsoft Advertising has announced that it will be phasing out Target CPA (cost per acquisition) and Target ROAS (return on ad spend) bidding strategies for newly created campaigns. This change comes as part of a broader move towards streamlining automated bidding options within the platform.

    Following this update, advertisers will be required to adopt Microsoft’s ‘Maximise Conversions’ or ‘Maximise Conversion Value’ strategies for new campaigns. These bidding types will allow the optional setting of targets for CPA or ROAS, providing a more flexible framework while aligning with Microsoft’s goal of simplifying campaign management and optimising performance through automation.

    It is important to note that existing campaigns already using Target CPA or Target ROAS will continue to function as normal. However, Microsoft has confirmed that these options will no longer be available for selection when setting up new campaigns from the September deadline onwards.

    Advertisers are encouraged to begin testing the recommended bidding strategies ahead of the transition to ensure campaign stability and performance. Leveraging the target-setting capabilities within the Maximise strategies can help maintain existing efficiency benchmarks while benefiting from improved automation and learning algorithms. [4]

    [1] Google

    [2] Google

    [3] Meta

    [4] Search Engine Land

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