TLDR Marketing 2026-04-23

AEO is the new SEO, and most sites aren't built for it. WordPress.com is.

• Server-rendered pages AI crawlers can actually read
• Auto-generated sitemaps, no setup needed
• Clean URLs and semantic markup out of the box
• Plugins, newsletters, SEO, and analytics built in
• Managed hosting, security, and expert support

Whether you're building with AI or trying to get found by AI, WordPress.com is ready to support you.

EU regulators plan to force Google to share search data to boost competition and improve rival ad and search performance. The policy allows access to queries, rankings, clicks, and anonymized user signals for at least five years, which can help competitors and AI platforms better target intent and refine results. Pricing must be cost-based and non-discriminatory, though large platforms with over 45 million users or $75B market cap may pay a margin. Google keeps its search index, which preserves a key advantage in relevance and ad monetization. The move signals tighter control under the Digital Markets Act and could reshape how marketers access search insights and compete for visibility.

Audiences are not tired of ads, they're tired of meaningless content. AI is making this worse by flooding channels with low-value output. The issue isn't ad fatigue, it's weak creative repeated too often. Most ads lack emotion, so more exposure drives indifference. Marketers respond with more content, which worsens the problem.

This workflow takes a keyword, pain point, funnel stage, and brand inputs, then generates a SERP-informed and ICP-focused brief. It maps search intent and builds a clear structure with narrative direction and section guidance. The output is tailored for human or AI-assisted workflows, and delivered automatically. This ensures content is grounded in data and audience needs, not guesswork.

Directly addressing competitors can attract attention and position a brand as the authority while making the real audience feel like insiders. A calm and generous tone lowers resistance, then facts correct competitor claims and frame the message as helpful information instead of an attack. Reframing comparisons is critical, since shifting from selective metrics to total cost or real usage can expose hidden disadvantages. Clear data, such as side-by-side pricing, makes claims more credible and easier to accept. Admitting a competitor's real advantage builds trust and strengthens every other argument.

Use the most powerful AI image models within a visual flow that lets you draw & annotate directly on images, compare results side by side, and keep projects clearly separated. Curious? Watch tutorials to see how it works, or download now to get started for free

This tool turns your LinkedIn network into an AI-searchable graph that Claude can reason over. It syncs and enriches your connections with full career histories, skills, and job changes, then lets you query it in natural language through an MCP integration. You can run complex searches or paste a job description and receive ranked matches with explanations. It also supports sharing access via API keys so others can query a network. It is still in early testing, so access is required and rollout is limited.

Reducing churn is often more impactful than generating new leads. This webinar will break down how top teams use multi-channel strategies across email, SMS, push, and in-app messaging, triggered by real customer behavior. Speakers from Customer.io, Notion, and Monarch will share examples, including how to choose the right channels and use AI without losing personalization. The session will take place on May 1 at 9 AM PDT.

AI is shifting marketing strategy from manual testing to automated systems that run continuous ad experimentation and optimization. Growth Engineers build agents that scrape competitor ads, generate up to 50 creative variations, launch campaigns, and pause losing ads daily, which increases speed and output. Marketing teams centralize data in shared systems similar to engineering repos, which improves context access and decision-making. Agents feed research and performance data into a unified system that answers questions instantly and removes manual searching. The focus moves from executing campaigns to designing systems and training agents that improve results over time.

A study examining eBay's redesign of its Top-Rated Seller badge found that shifting certification criteria from buyer feedback to administrative metrics changed how sellers allocate effort and how buyers interpret trust signals. Sellers responded strategically, improving performance on the specific dimensions tied to badge eligibility and clustering just above certification cutoffs. Buyer trust in the badge held strongest in categories where the new administrative measures correlated closely with consumer-reported satisfaction, driving higher purchase rates and six-month return visits in those segments.

Agents are becoming the primary “users,” so marketing and product strategy must shift from persuading humans to serving machine evaluation. Products win if they deliver fast, reliable, structured outputs that agents can use, since agents ignore UI, onboarding, and brand and replace tools that underperform. Distribution also flips, so growth depends on being discoverable, well-documented, and easy for agents to integrate rather than driving traffic through ads and funnels. Opening products through protocols like MCP becomes necessary to stay in workflows, but it weakens moats based on friction and forces companies to compete on unique data, integrations, or outputs that cannot be replicated. This shift reduces the value of traditional tactics like landing pages and SEO and increases the importance of performance and accessibility to automated buyers.

Stop mapping journeys and instead make your content answer the exact questions buyers need to justify the purchase internally.

Frequent social media use is linked to weaker language development in kids under 16, especially in word recognition and pronunciation.

Bond has ditched algorithmic feeds in favor of AI-driven real-world recommendations, and plans to let users monetize their personal data by licensing it to AI training pipelines rather than relying on advertising.