Don't mistake hyper-personalization for effectiveness. Running hundreds of tiny, account-specific campaigns is inefficient and hard to measure. A more successful approach is to group accounts by industry or shared pain points and run fewer, larger campaigns for better data and stronger engagement.

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.

AI models for campaign creation are only as good as the data they ingest. Inaccurate or siloed data on accounts, contacts, and ad performance prevents AI from developing optimal strategies, rendering the technology ineffective for scalable, high-quality output.

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.

A CRM is more than a database; it's the engine for accountability and strategy. Without the ability to track revenue drivers, customer segments, and marketing ROI, you cannot make data-informed decisions or manage performance. This foundational gap kills your potential for strategic growth.

The CMO trend of consolidating to a single all-in-one platform often sacrifices best-in-class capabilities, especially in AI. A more agile strategy is to keep your preferred ESP and SMS tools and layer a dedicated AI decisioning engine on top, using APIs to orchestrate campaigns without a costly rip-and-replace.

The core problem for many small and mid-market businesses isn't a lack of software, but an excess of it, using 7 to 25 different apps. This creates massive data fragmentation. The crucial first step isn't buying more tools, but unifying existing data into a single customer profile to enable smarter, automated marketing.

With 15,000+ martech tools and no-code options, your competition is no longer just your direct category rivals. You're fighting every other potential software purchase—and the "build it yourself" option—for the same limited time, attention, and budget, rendering high-volume outreach ineffective.

Companies struggle to get value from AI because their data is fragmented across different systems (ERP, CRM, finance) with poor integrity. The primary challenge isn't the AI models themselves, but integrating these disparate data sets into a unified platform that agents can act upon.