Salesforce Introduces Agentic Marketing with AI Agents

The marketing landscape is rapidly evolving, requiring marketers to engage not only human audiences but also AI models. Customer journeys are no longer linear, necessitating a strategic approach to influence AI-driven answers that consumers increasingly rely on.

Eric Zens noted that marketers now need to market to both human and AI audiences, requiring a change in tactics.

Salesforce has acquired Contentful to integrate rich content with existing customer context, a move expected to enhance AI capabilities in personalized marketing. This acquisition aims to fill a critical gap by providing a robust content foundation for both human and AI-driven experiences.

Eric Zens expressed excitement about Contentful joining Salesforce and the marketing cloud, highlighting its role in connecting rich context with equally rich content.

The shift from traditional search to AI-driven answer engines presents a challenge for brands to understand and influence the 'black box' of AI perception.

Kimberly Gong emphasized that answer engines now serve as the new front door, as more searches originate from AEO, with 70% of consumers using search as their initial interaction point.

Salesforce unveiled Palmada, a new innovation designed to help marketers understand, measure, and improve their Answer Engine Optimization. Palmada tracks key metrics such as brand visibility, citation rates, and sentiment in AI-generated answers.

The tool assists in identifying why AI might misinterpret brand content and simulates the impact of content changes on AI results, providing actionable insights for optimization. Kimberly Gong expressed delight in introducing Palmada as their latest innovation to aid in AEO.

The process involves leveraging tools like Claude with MCP connectors to automate updates from Palmada's recommendations directly to Contentful.

This automation streamlines the content adjustment process, allowing marketers to efficiently respond to insights from AI perception data.

Formula 1 underwent a significant transformation over the last eight years, shifting from a strictly B2B business to a fan-centric B2C powerhouse. This strategic pivot led to substantial growth in its global fan base, from 525 million in 2018 to 830 million currently.

Matt Kemp highlighted that while Formula 1 is 75 years old, its B2C focus began only eight years ago, marking a period where they actively started engaging with their fans. The content strategy expanded to unconventional channels like 'Drive to Survive' and 'Emily in Paris' to reach new audiences.

The demographic profile of Formula 1 fans has dramatically shifted, necessitating adaptive marketing strategies to cater to a broader audience. Historically, the fan base was predominantly male and over 45 years old.

Currently, 43% of the fan base identifies as female, and 42% are under the age of 34, reflecting a significant move towards younger and more diverse demographics. Matt Kemp detailed that the fan base was nearly all male over 45 eight years ago, while now 43% are female and 42% are under 34.

Salesforce aims to help marketers transition from rigid, predefined workflows and manual bottlenecks to goal-oriented agentic processes. This shift emphasizes measuring marketing success by pipeline revenue growth rather than the number of messages sent or variants created.

Campaign agents are designed to autonomously prioritize timing, messaging, and channels for individual customers, with the ability to decide against sending a message if it doesn't align with campaign goals. Natalie Matthysse underscored that marketing is measured by pipeline revenue growth, not by the volume of messages or variants, stressing a focus on strategic outcomes.

This significant improvement addresses previous bottlenecks where going live with a campaign took over two weeks.

The pilot demonstrates the potential for efficiency gains, especially for brands managing large subscriber bases like Under Armour's 50 million, which often face complex creative approval needs. Natalie Matthysse reported that in the pilot, Under Armour reduced the time to build an email from hours to just minutes.

This allows AI to determine who could potentially receive a campaign, rather than who is explicitly included.

This approach enables the agent to prioritize campaigns for individuals based on their evolving needs and behaviors, leading to more relevant and timely engagements. John explained that with a campaign agent, a segment moves beyond a regular list to define eligibility criteria, focusing on who could receive a campaign rather than who will exactly receive it.

This eliminates the need for manual, step-by-step journey building, allowing marketers to focus on strategy.

The agent automatically identifies and prioritizes content that is performing well, while reducing the visibility of underperforming content. John highlighted that the agent continually tests and learns to meet goals, making optimizations like showing more effective content.

A significant challenge for marketers is responding to new leads promptly, with 93% reporting an inability to respond within five minutes. This delay represents a missed market opportunity to act on real-time customer intent.

Bridging this gap is crucial for converting interest into engagement effectively. Matt Schultz pointed out that 93% of marketers feel they cannot respond to a new lead within 5 minutes, questioning the implications if they could.

These agents are also enhancing the efficiency of Sales Development Representatives (SDRs).

Matt Schultz affirmed that they are observing a 2x conversion rate compared to previous performance with Piper, leading to increased team efficiency.

Traditional marketing often suffers from high latency between customer intent and responsive action, leading to missed opportunities. Salesforce's AI agent, 'Piper,' directly addresses this by engaging prospects in real-time on websites, turning immediate intent into instant action.

The system autonomously manages CRM tasks, such as scheduling meetings, ensuring that potential leads are acted upon promptly and efficiently. Matt described how Piper meets the CMO of Quadar, acting on their intent immediately, preventing them from being 'ghosted' unlike traditional methods.

This agent also autonomously creates CRM opportunities, streamlining administrative tasks.

By reducing the administrative burden on sales teams, 'Hunter' enables representatives to focus more on personalized customer engagement, thereby improving overall efficiency. Matt explained that Hunter interprets and understands information to prepare customized briefs for sellers, aligning with the personalization Piper provides for their accounts.

Identifying repetitive tasks serves as a signal for innovation, prompting the adoption of AI to automate grunt work in marketing. This shift allows marketers to reallocate their focus from mundane activities to more strategic and creative initiatives.

Personalization is highlighted as a core requirement for modern customers, driving the need for AI-driven strategies that enhance tailored experiences. Aaron Duncan emphasized that any repetition, or task performed more than once, signals an opportunity for AI innovation, allowing for a shift in focus toward strategy and creativity by offloading routine work like aligning brand standards and acting as an FAQ resource.