Short reads for short attention spans

Meta and OpenAI launch "Agent Campaigns" to bypass external websites

Conversational commerce has reached a major milestone as tech giants move to replace traditional website landing pages with automated, interactive agents directly inside chat threads.

Spotted within the ChatGPT Ads Manager, OpenAI is experimenting with a new performance ad format: Agent Campaigns. Clicking an "Agent" ad does not redirect the user to an external brand website; instead, it immediately opens a dedicated, brand-specific ChatGPT conversation. Powered by the advertiser's uploaded business data, the AI agent can answer prospect queries, qualify leads, and assist with purchases directly within the chat window.

Concurrently, Meta has officially launched Meta Business Agents for commercial WhatsApp accounts. Unveiled at its London Conversations showcase, the automated agent handles end-to-end customer interactions natively inside chat threads. Prospects can ask detailed product questions, receive personalised recommendations, and execute full e-commerce checkouts or appointment bookings without ever leaving WhatsApp.

Why it matters

• The Elimination of Landing Page Friction: Media buyers no longer need to worry about slow page load times or mobile site layout issues. The entire conversion journey—from initial discovery to final checkout—happens inside a familiar, conversational interface.
• First-Party Data Capture: By managing the interaction directly through AI agents, brands capture richer, qualitative zero-party data (exact customer questions and product preferences) during the initial discovery phase.
• A New Creative Focus: Optimisation moves away from designing static landing pages toward training business knowledge bases and conversation flows to ensure AI agents accurately qualify prospects and close sales.

Further reading at Search Engine Land:

Business Agents are here. Marketers should pay attention

Publisher–AI licensing risks creating a two-tier media market

As AI platforms become increasingly dependent on high-quality publisher content, licensing agreements are emerging as an important new revenue stream. But access to that revenue is far from evenly distributed.

Large publishers and news organisations have been able to negotiate individual agreements with AI companies including OpenAI, Meta, Apple, Mistral and Perplexity. Smaller publishers have considerably less bargaining power, prompting growing interest in collective licensing models that aggregate publisher rights and negotiate with AI platforms at scale.

The result could be a two-tier publishing ecosystem: major media brands receive both licensing revenue and greater prominence within AI products, while smaller publishers provide valuable source material without receiving comparable commercial returns.

Why it matters

• AI creates a new publisher revenue stream: Content licensing could partially offset declining search referral traffic, but the opportunity may disproportionately benefit the largest media owners.
• Authority could compound: Publishers with licensing relationships may gain both revenue and stronger representation within AI-generated answers, reinforcing established media brands.
• Collective licensing becomes important: Smaller publishers may increasingly need to negotiate collectively rather than individually with the major AI platforms.
• Media value is changing: A publisher’s commercial value may increasingly include not just its human audience, but how valuable and authoritative its content is to AI systems.

Further reading at Press Gazette:

AI licensing coalition SPUR in huge expansion

AI-search visibility is rapidly becoming its own martech category

A new generation of marketing technology is emerging specifically to answer a question traditional SEO platforms were not designed for: “What does AI say about my brand?”

Rather than simply tracking Google rankings, these platforms monitor whether brands, products and competitors appear in responses generated by ChatGPT, Gemini, Claude, Perplexity, Copilot and Google AI experiences.

The emerging metrics look increasingly like a hybrid of SEO and media measurement: AI share of voice, citation frequency, brand mentions, recommendation rates, sentiment and the sources influencing AI responses.

That creates a potentially significant new category alongside established SEO platforms such as Semrush and Ahrefs.

Why it matters

• Rankings alone are becoming insufficient: A brand could rank strongly in traditional search while being largely absent from the AI-generated answers consumers increasingly use for research.
• AI share of voice becomes measurable: Marketers can begin benchmarking how frequently their brand is recommended against competitors across different AI platforms.
• PR, SEO and content converge: Earned media, authoritative third-party mentions, product information and owned content can all influence what an AI system ultimately says about a brand.
• A new optimisation discipline emerges: GEO/AEO is moving from an abstract marketing concept towards something teams can monitor, benchmark and potentially optimise systematically.

Further reading at the Search Engine Journal:

How to measure your brand’s visibility in Gemini

The interesting connecting thread between all three is that the website is gradually losing its privileged position at the centre of digital marketing.

Publishers are negotiating to have their information consumed inside AI platforms. Brands are measuring whether they appear inside AI answers. And advertisers are beginning to convert customers inside AI conversations.

If that trajectory continues, the marketing funnel increasingly becomes source → AI discovery → AI conversation → transaction, with the website potentially becoming supporting infrastructure rather than the default customer interface.