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Introducing the Agentic Customer Platform

William Gu
William Gu
Marketing AI Team @ MKTGAGENT.AI

Unlocking Business Potential with the Agentic Customer Platform

In today’s fast-evolving business landscape, artificial intelligence (AI) promises a lot but often falls short in delivering clear, actionable outcomes that truly benefit companies. This is the challenge the new Agentic Customer Platform is designed to overcome. By providing a richer, more contextual understanding of customer data, this innovative platform aims to bridge the gap between AI’s potential and real-world business results.

What Is the Agentic Customer Platform?

The Agentic Customer Platform is developed by HubSpot to address a frequently heard complaint among business leaders: AI tools generate impressive outputs, but these often don’t translate into meaningful business outcomes. Unlike many existing AI solutions, this platform emphasizes the critical importance of context—something that is often missing.

At its core, the platform integrates multiple layers of information: detailed customer data, relevant business context, and the dynamics of internal teams. This comprehensive approach allows businesses to harness both human expertise and AI efficiency in a coordinated manner.

The Platform’s Innovative Architecture

The architecture of the Agentic Customer Platform is structured around three main layers:

  • Context Layer: Consolidates full customer profiles and gathers insights from all previous interactions. This ensures that every AI recommendation or action is informed by a holistic view rather than isolated data points.

  • Action Layer: Equipped with advanced hubs and AI agents designed to carry out tasks intelligently and automate workflows, this layer transforms insights into tangible actions.

  • Coordination Layer: Facilitates seamless collaboration between human teams and AI tools, ensuring that each complements the other and fostering productive synergy.

Why Context Matters in AI

AI systems traditionally rely heavily on raw data but often miss what surrounds that data—the context. Context includes the nuances of customer preferences, past interactions, team objectives, and broader business goals. The Agentic Customer Platform’s focus on context means smarter, more relevant AI-driven recommendations, leading to improved customer experiences and stronger business results.

Key Insights

  • How does the Agentic Customer Platform improve AI outcomes? It integrates customer context, business factors, and team dynamics to create a unified environment where AI and humans work smarter together.

  • What makes this platform different from other AI tools? Its layered structure that explicitly addresses the gap between raw outputs and real-world outcomes by embedding complete customer and business context.

  • Who will benefit most from this platform? Business leaders and teams seeking to leverage AI to drive measurable results and enhance customer interactions meaningfully.

  • What is the broader impact on business operations? It encourages more informed decision-making, greater collaboration between people and machines, and more personalized customer engagement.

Conclusion

The Agentic Customer Platform represents a significant step forward in how businesses can leverage AI—not just for automation or data processing but as a truly intelligent partner in decision-making and customer engagement. By uniting comprehensive customer data with business context and team collaboration, it empowers organizations to achieve better, measurable outcomes and foster deeper, more tailored customer relationships moving forward.

Source: https://blog.hubspot.com/marketing/introducing-the-agentic-customer-platform

LinkedIn: AI-powered search cut traffic by up to 60%

William Gu
William Gu
Marketing AI Team @ MKTGAGENT.AI

LinkedIn Adapts to AI-Powered Search Changes: Traffic Drops and New Marketing Strategies

In the evolving landscape of digital marketing and search engine technology, LinkedIn has encountered a significant challenge that is reshaping how businesses attract and engage audiences. Recently reported data reveals that LinkedIn’s non-brand B2B awareness traffic has dropped by up to 60% due to changes brought by Google’s AI-powered search features. This steep decline has prompted LinkedIn to rethink its marketing approach and prioritize new strategies adapted to AI-driven search ecosystems.

The Impact of AI-Powered Search on LinkedIn Traffic

Google’s introduction of the Search Generative Experience (SGE), which has evolved into AI Overviews, is transforming how users access information. These AI-generated summaries provide direct answers to queries, reducing the need for click-throughs to external websites. For LinkedIn, this means fewer organic visits from non-brand search terms despite their stable search rankings. The diminished click-through rate (CTR) reflects a broader challenge where traditional ‘search, click, website’ methods no longer guarantee visibility or traffic.

Shifting Marketing Focus: From Clicks to Consideration

In response, LinkedIn is shifting its marketing paradigm from counting on search clicks to focusing on brand presence and customer perception. This new model is summarized as ‘be seen, be mentioned, be considered, be chosen.’ The emphasis is now on creating fresh, authoritative content that stands out in an AI-dominated search landscape. LinkedIn aims to be more than a search result; it wants to be part of the narrative that AI shares with users.

Strategic Initiatives and Challenges Ahead

To respond effectively, LinkedIn is optimizing its owned content for generative AI visibility and has launched an AI Search Taskforce. This team is dedicated to combating misinformation and enhancing LinkedIn’s authority and relevance in search results influenced by AI. However, with limited data available on the effectiveness of these measures, the company faces uncertainty in measuring how well these new approaches will perform.

Key Insights

  • What caused the traffic decline on LinkedIn? Google’s AI-powered search features, specifically the SGE and AI Overviews, are reducing click-through traffic by providing direct answers.
  • How is LinkedIn adapting its marketing strategy? By moving from a traditional search-click approach to focusing on brand visibility and authoritative content.
  • What role does content play in this new era? Fresh, reliable, and optimized content is critical to being featured in AI-generated summaries.
  • What are LinkedIn’s next steps? Enhancing owned content and combating misinformation through a dedicated AI Search Taskforce.

Conclusion

LinkedIn’s experience underscores a broader shift in digital marketing caused by AI in search engines. As AI continues to reduce organic search traffic by offering instant answers, businesses must adapt by prioritizing brand presence and content quality over traditional SEO tactics. This evolution presents both challenges and opportunities for marketers to rethink how they engage audiences and measure success in an AI-influenced digital world.

Source: https://searchengineland.com/linkedin-ai-powered-search-cut-traffic-468187

Microsoft launches Publisher Content Marketplace for AI licensing

William Gu
William Gu
Marketing AI Team @ MKTGAGENT.AI

Microsoft Launches Publisher Content Marketplace: A New Era for AI Content Licensing

Microsoft Advertising has unveiled the Publisher Content Marketplace (PCM), a pioneering platform designed to streamline the licensing of premium content for AI applications. This development marks a significant leap in how publishers and AI developers collaborate, helping to ensure quality and accountability in the content fueling artificial intelligence systems.

Simplifying Content Licensing for AI

Traditionally, securing licenses for content can be a complex and fragmented process, often slowed by the need for numerous individual contracts. PCM addresses this challenge by providing a centralized marketplace where publishers can offer their premium content under flexible and clear licensing terms. This model enables AI developers to easily license content tailored to their specific needs without lengthy negotiations.

The platform benefits publishers by allowing them to set their own licensing terms and receive fair compensation based on content usage. It also preserves publishers’ ownership rights and editorial independence, ensuring that trusted sources maintain control over their intellectual property.

Enhancing AI Credibility and Performance

As AI technologies increasingly rely on quality information to inform decisions, the PCM framework supports the integrity and transparency of these systems. By enabling direct value exchange between content creators and AI products, Microsoft’s marketplace promotes a more ethical use of information and helps prevent misinformation.

Already, the marketplace boasts partnerships with prominent publishers, setting a precedent for quality and reliability. This initiative not only enhances the credibility of AI-driven decisions across various fields but also empowers publishers to benefit economically from the growing AI ecosystem.

Key Insights

  • What is the Publisher Content Marketplace? A centralized platform by Microsoft Advertising for licensing premium content to AI developers, simplifying the process and ensuring fair compensation.
  • How does PCM benefit publishers and AI developers? Publishers retain ownership and set licensing terms, while AI developers gain easier access to valuable content tailored for specific applications.
  • Why is this important for AI? High-quality, licensed content is crucial for trustworthy AI decision-making, reducing reliance on unverified information.
  • What industries could benefit? Virtually any sector using AI—media, education, healthcare, and more—can leverage PCM to improve AI outcomes.
  • What’s next for PCM? Expansion of publisher partnerships and broader adoption in AI content sourcing.

Conclusion

Microsoft’s Publisher Content Marketplace represents a groundbreaking step toward a more transparent and equitable content ecosystem in the AI era. By bridging the gap between content creators and AI technologies, PCM fosters trust, quality, and fair compensation, promising to elevate AI innovation while supporting the publishers who fuel it.

Source: https://searchengineland.com/microsoft-launches-publisher-content-marketplace-for-ai-licensing-468191

Universal Commerce Protocol Is Here — And Ecommerce Won’t Look the Same

William Gu
William Gu
Marketing AI Team @ MKTGAGENT.AI

How Google’s Universal Commerce Protocol is Transforming Ecommerce Forever

The landscape of ecommerce is on the brink of a major transformation, driven by Google’s introduction of the Universal Commerce Protocol (UCP). This innovative technology redefines how online purchases are made by allowing AI agents to handle everything—from discovering products to completing transactions—without the need for traditional storefronts or the familiar metrics that have long defined online retail.

What is the Universal Commerce Protocol?

UCP is a standardized framework developed by Google that enables artificial intelligence to interact directly with merchants. This means an AI can manage your entire purchasing process seamlessly. Instead of navigating through pages or filling out forms over and over, an AI agent can take care of it all, including entering address and payment information usually required from shoppers.

The Shift from Traditional Ecommerce to AI-Driven Shopping

Traditional online shopping involves clicking through storefronts, comparing products, and manually entering payment details. UCP replaces these steps with conversational AI interactions. Consumers can simply tell their AI what they want, and it negotiates and transacts on their behalf, creating a smoother, faster shopping experience.

Changing Metrics: From Clicks to Intent Fulfillment

With AI agents conducting transactions, old metrics such as clicks and conversions become less relevant. Instead, success will be measured by how well the AI understands and fulfills consumer intent and ensures reliable transactions. This shift requires businesses to rethink how they evaluate performance and consumer engagement.

Implications for Ecommerce Giants and Retailers

The rise of agent-driven shopping could upset current ecommerce power structures. Major players like Amazon may face challenges as the UCP evolves. Retailers and brands need to adapt their strategies and technology frameworks to stay competitive in this new environment where AI effectively becomes the buyer.

Key Insights

  • What problem does UCP solve? UCP eliminates repetitive consumer input and streamlines the shopping process through AI, making purchases quicker and less cumbersome.
  • How does UCP affect ecommerce metrics? It shifts the focus from traditional metrics (clicks, conversions) to intent fulfillment and transaction reliability, changing how success is measured.
  • Who benefits most from UCP? Consumers benefit from convenience, while businesses must innovate to align with agent-driven commerce models.
  • What challenges lie ahead? Companies must redesign their ecommerce strategies and infrastructures to accommodate AI agents acting as buyers.

Conclusion

Google’s Universal Commerce Protocol heralds a new era in ecommerce by integrating AI in core purchasing operations. This technology streamlines transactions, eliminates friction, and calls for a reassessment of business models and performance metrics. As AI agents become the norm in shopping, the ecommerce ecosystem will undergo profound changes, pushing retailers and marketplaces to innovate or risk falling behind.

Source: https://www.cmswire.com/digital-experience/universal-commerce-protocol-is-here-and-ecommerce-wont-look-the-same/?utm_source=cmswire.com&utm_medium=web&utm_campaign=cm&utm_content=all-articles-rss

Using AI For SEO Can Fail Without Real Data (& How Ahrefs Fixes It) via @sejournal, @ahrefs

William Gu
William Gu
Marketing AI Team @ MKTGAGENT.AI

Unlocking SEO Success: How Ahrefs Boosts AI with Real-Time Data Integration

In the rapidly evolving SEO landscape, leveraging artificial intelligence (AI) promises to transform how marketers strategize and execute their campaigns. However, using AI tools in isolation, without access to accurate and live SEO data, often yields flawed insights and inefficient workflows. Recent developments led by Ahrefs, highlighted in a featured article by Search Engine Journal, reveal a groundbreaking solution: the Model Context Protocol (MCP).

The Challenge with AI-only SEO Approaches

AI in SEO typically relies on pattern recognition and machine learning models, drawing conclusions from vast datasets. While powerful, AI alone can generate inaccuracies if it operates without real-time context or authentic data feeds. Conversely, traditional SEO dashboards provide accurate data but can be slow, cumbersome, and difficult to integrate quickly into decision-making processes.

Ahrefs identified this gap and sought to create a seamless connection between the two worlds—AI’s analytical prowess and the precision of live, up-to-date SEO data.

Ahrefs’ Model Context Protocol: Bridging the Gap

Ahrefs’ innovative MCP allows AI assistants to integrate directly with authentic, live SEO data. This real-time access enables AI tools to produce more reliable, actionable SEO insights faster than traditional methods could allow. By connecting automated AI prompts with continuous data updates, users can explore competitive analysis, refine content strategies, and grow organic traffic more effectively.

The article presents 15 practical use cases for MCP, ranging from quick insights like keyword opportunities to complex tasks such as advanced SEO research workflows.

Practical SEO Use Cases Powered by MCP

  • Competitive Analysis: AI can swiftly provide detailed reports on competitor backlinks and rankings.
  • Content Planning: Real-time keyword trends help tailor content creation to what audiences actively seek.
  • Traffic Growth Strategies: Automated, data-informed tactics identify optimization points for better organic reach.

Key Insights

  • Why integrate AI with real-time SEO data? Combining AI with live data drastically improves accuracy and relevance, eliminating guesswork.
  • What problems does MCP solve? It resolves the inefficiencies of static dashboards and AI isolation by enabling dynamic, prompt-driven SEO analysis.
  • How can users benefit from this approach? Enhanced speed and precision in SEO tasks free marketers to focus on strategic decisions rather than manual data collection.

Conclusion

Ahrefs’ Model Context Protocol represents a significant advancement in SEO technology by merging the strengths of AI and real-time data. This integration empowers marketers with tools that are not only intelligent but also timely and data-validated, fostering smarter strategies and higher organic traffic growth. As AI continues to mature in marketing, innovations like MCP will likely become standard practice, ensuring more effective and competitive SEO efforts moving forward.

Source: https://www.searchenginejournal.com/ai-for-seo-fails-without-data-ahrefs-spa/566077/