Pratik Desai, Head of Applied AI at ListEngage, published a framework on June 17, 2026, advocating for a transition from traditional campaign-based marketing to an always-on model. The article states that historical reliance on batch-and-blast campaigns was a workaround for technological limitations, such as the inability to provide real-time, personalized responses at scale. Modern infrastructure, particularly Agentforce Marketing and Salesforce Data 360, enables brands to process thousands of simultaneous customer signals and trigger relevant communications across email, SMS, and WhatsApp the moment a specific customer need is identified.

Always-on marketing functions by engaging customers at the exact moment of relevance, rather than adhering to rigid marketing calendars. This model addresses specific scenarios such as delivering nudges when customer intent peaks, responding instantly to cart abandonment at 11pm, or launching re-engagement flows before a subscriber churns. By embedding intelligence across the platform, Agentforce Marketing optimizes send times at the individual level, predicts churn risk without manual queries, and recommends content variants for specific micro-segments.

The transition evolves the role of the marketing practitioner from manual executor to the architect of a self-operating system that markets continuously. Organizations that adopt this approach benefit from a compounding effect, as every interaction feeds the underlying data model to refine future personalization. The author recommends starting by identifying high-signal customer moments—such as post-purchase SMS sequences or browse-abandonment emails—to build out these automated responses, arguing that these focused actions will outperform traditional, scheduled large-scale campaigns.

Pratik Desai, Head of Applied AI at ListEngage, published a framework on June 17, 2026, advocating for a transition from traditional campaign-based marketing to an always-on model. The article states that historical reliance on batch-and-blast campaigns was a workaround for technological limitations, such as the inability to provide real-time, personalized responses at scale. Modern infrastructure, particularly Agentforce Marketing and Salesforce Data 360, enables brands to process thousands of simultaneous customer signals and trigger relevant communications across email, SMS, and WhatsApp the moment a specific customer need is identified.

Always-on marketing functions by engaging customers at the exact moment of relevance, rather than adhering to rigid marketing calendars. This model addresses specific scenarios such as delivering nudges when customer intent peaks, responding instantly to cart abandonment at 11pm, or launching re-engagement flows before a subscriber churns. By embedding intelligence across the platform, Agentforce Marketing optimizes send times at the individual level, predicts churn risk without manual queries, and recommends content variants for specific micro-segments.

The transition evolves the role of the marketing practitioner from manual executor to the architect of a self-operating system that markets continuously. Organizations that adopt this approach benefit from a compounding effect, as every interaction feeds the underlying data model to refine future personalization. The author recommends starting by identifying high-signal customer moments—such as post-purchase SMS sequences or browse-abandonment emails—to build out these automated responses, arguing that these focused actions will outperform traditional, scheduled large-scale campaigns.