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The CMO believes AI for generic content creation is overrated. Instead, their most effective use of AI is creating highly tailored drip and outbound campaigns based on a user's specific in-product activity and results. This contextual outreach helps prevent churn and increase monetization.

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The true power of AI in marketing is not generating more content, but improving its quality and effectiveness. Marketers should focus on using AI—trained on their own historical performance data—to create content that better persuades consumers and builds the brand, rather than simply adding to the noise.

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.

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.

Beyond just generating creative, the future of AI in CRM is using "agentic AI" to build better strategies. This involves agents that help define audience segments, determine the next best product or action, and accelerate the implementation of complex campaigns, enhancing human strategy rather than replacing it.

The primary role of AI in marketing isn't to replace creative work but to automate the complex process of understanding customer behavior. AI systems continuously analyze data to answer critical questions about conversion, value, and budget waste, freeing up humans for strategic tasks.

Instead of batching users into lists for A/B tests, AI can analyze each individual's complete behavioral history in real-time. It then deploys a uniquely bespoke message at the optimal moment for that single user, a level of personalization that makes static segmentation primitive by comparison.

Instead of guessing at marketing copy, build an AI model of your ideal customer. By feeding it internal data like call transcripts and external data like forum posts, this "digital twin" can review and rewrite your marketing materials using the customer's exact language.

Instead of using AI for mass content creation, which leads to overload, leverage it to adapt a core value proposition into highly relevant messaging for each persona within a buying group (CEO, CTO, CFO), addressing their specific pain points.

AI makes it easy to generate grammatically correct but generic outreach. This flood of 'mediocre' communication, rather than 'terrible' spam, makes it harder for genuine, well-researched messages to stand out. Success now requires a level of personalization that generic AI can't fake.

Don't wait for the perfect AI marketing platform. Repurpose existing AI sales tools for marketing automation. Their sequence and re-engagement capabilities can be hacked to run hyper-personalized drip campaigns, bridging the current technology gap.