AI's most significant impact is not just campaign optimization but its ability to break down data silos. By combining loyalty, e-commerce, and in-store interaction data, retailers can create a holistic customer view, enabling truly adaptive and intelligent marketing across all channels.

Fragmented data and disconnected systems in traditional marketing clouds prevent AI from forming a complete, persistent memory of customer interactions. This leads to missed opportunities and flawed personalization, as the AI operates with incomplete information, exposing foundational cracks in legacy architecture.

To effectively serve SMBs, B2B marketers must evolve their approach from collaboration ('do it with them') to automation ('do it for them'). SMB owners are not marketers and lack the time and staff to manage complex tools. The most valuable service is one that simplifies complexity and leverages technology to execute marketing tasks on their behalf, empowering them to achieve more with minimal direct involvement.

Marketing leaders pressured to adopt AI are discovering the primary obstacle isn't the technology, but their own internal data infrastructure. Siloed, inconsistently structured data across teams prevents them from effectively leveraging AI for consumer insights and business growth.

Instead of viewing them as separate efforts, businesses should link customer retention and acquisition. By unifying data to better re-engage existing customers via owned channels like email and SMS, brands increase lifetime value. This, in turn, reduces the long-term pressure and cost associated with acquiring entirely new customers.

While the industry chases complex AI, research shows less than half of marketers (42%) use basic preference data for personalization. This highlights a massive, untapped opportunity to improve customer experience with existing data before investing in advanced technology.

Brands miss opportunities by testing product, packaging, and advertising in silos. Connecting these data sources creates a powerful feedback loop. For example, a consumer insight about desirable packaging can be directly incorporated into an ad campaign, but only if the data is unified.

According to Salesforce's AI chief, the primary challenge for large companies deploying AI is harmonizing data across siloed departments, like sales and marketing. AI cannot operate effectively without connected, unified data, making data integration the crucial first step before any advanced AI implementation.