Don't unleash a generic AI agent on your entire database. To get high response rates, segment contacts into specific sub-personas based on role, behavior, or status (e.g., churn risk). Then, train dedicated sub-agents or campaigns for each persona, allowing for true personalization at scale in batches of around 1,000 contacts.

To succeed, marketers must stop passively accepting the data they're given. Instead, they must proactively partner with IT and privacy teams to advocate for the specific data collection and governance required to power their growth and personalization initiatives.

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.

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.

Companies can use AI to generate unique, 'ephemeral software' experiences for marketing campaigns. Instead of a generic Spotify Wrapped-style review, businesses can now affordably create a custom, interactive 'unwrapped' summary for each user based on their specific product usage data, costing just cents in tokens.

Instead of manually sifting through overwhelming survey responses, input the raw data into an AI model. You can prompt it to identify distinct customer segments and generate detailed avatars—complete with pain points and desires—for each of your specific offers.

Expensive user research often sits unused in documents. By ingesting this static data, you can create interactive AI chatbot personas. This allows product and marketing teams to "talk to" their customers in real-time to test ad copy, features, and messaging, making research continuously actionable.

Modern marketing relevance requires moving beyond traditional demographic segments. The focus should be on real-time signals of customer intent, like clicks and searches. This reframes the customer from a static identity to a dynamic one, enabling more timely and relevant engagement.

Avoid the 'settings screen' trap where endless customization options cater to a vocal minority but create complexity for everyone. Instead, focus on personalization: using behavioral data to intelligently surface the right features to the right users, improving their experience without adding cognitive load for the majority.