Session Summary

The summary below provides a structured breakdown of the key moments from the session. It follows the flow of the presentation, highlighting the strategic context, major product updates, and live demonstrations shared by Shay, as well as the audience Q&A that followed.

Marketing Hub’s Role in the HubSpot Ecosystem

Shay opens by positioning Marketing Hub within HubSpot’s broader product ecosystem. At its core, HubSpot is framed as a unified CRM layer, with Marketing Hub focused on solving two persistent customer challenges: generating leads and automating marketing. These problems, Shay explains, are not diminishing over time,  they are becoming more complex as customer expectations and channels continue to evolve.

Marketing Hub is described as the bridge between attracting visitors and nurturing leads through the funnel. Shay highlights that AI is increasingly central to unifying these efforts, enabling marketers to work more effectively with growing volumes of data. This context sets the stage for why many of the latest product updates are concentrated around audience reach, insight generation, and automation.

Transparency, Confidentiality, and Product Update Context

Before diving into demos, Shay clarifies that some of the material being shared is not yet publicly available. A simple rule is offered: if a feature exists in a customer’s portal, it is fair to discuss openly; if not, it should be treated as a confidential preview. Certain elements will be removed from the official recording for this reason.

Shay also acknowledges the challenge customers face with the sheer volume of product updates. Rather than attempting to cover everything, the session focuses on major recent releases and select upcoming investments that customers may not yet have had time to explore. This framing helps prioritise depth over breadth throughout the remainder of the session.

AI Investments Across Lead Generation and Automation

A significant portion of the session centres on how HubSpot is doubling down on AI across Marketing Hub. On the lead generation side, Shay highlights increased investment in agents, including content and social agents, alongside AI-powered lead scoring. These tools aim to help marketers identify and prioritise high-quality leads more effectively.

On the automation side, Shay introduces Journey Automation, a new marketing-centric approach built on HubSpot’s workflow system. Journey Automation is designed to give marketers a clearer, more intuitive way to map and manage full customer journeys, rather than relying on isolated workflows. Shay notes that a brief demo may be shown depending on time, reinforcing the practical, hands-on nature of the session.

What’s Coming Next: Emerging AI Capabilities

Looking ahead, Shay outlines several upcoming AI-driven features currently in development. One particularly notable example is AI email template import. This feature allows users to provide an HTML file or even a screenshot of an email, which HubSpot can then convert directly into a usable email template within the platform.

Shay frames this as a solution to a common marketer pain point, emphasising the time savings and reduction in manual effort. Additional upcoming capabilities include multi-account management, such as syncing sandboxes across portals and sharing assets between accounts, making it easier for organisations managing multiple HubSpot instances to work consistently at scale.

Live Demo: ChatGPT Deep Research Connector

The session then moves into a live demonstration of the ChatGPT Deep Research Connector. Shay explains that this tool allows users to connect ChatGPT’s deep research capabilities directly to their HubSpot account, enabling AI to analyse CRM data at scale. After authenticating ChatGPT, users can run complex prompts across their entire portal.

Using an example prompt focused on identifying high-converting cohorts and creating tailored nurture sequences, Shay shows how the tool asks clarifying questions before analysing the data. A previously completed query is shared to demonstrate the output, which includes audience insights, content performance trends, lifecycle analysis, and links for deeper exploration. Shay emphasises that insights like these would normally take days of manual analysis but can now be generated much faster.