A marketing team at NAC created a custom AI engine that queries LLMs, scrapes their citations, and analyzes the results against its own content. This proactive workflow identifies content gaps relative to competitors and surfaces new topics, directly driving organic reach and inbound demand.

Every customer call is a potential blog post. An AI workflow systematically redacts all sensitive and identifying information from call transcripts, then rewrites the core use-case discussion into an SEO-optimized article. This creates a scalable content machine fueled by real customer problems, generating thousands of posts.

Keyword tools are useless for identifying the ultra-long-tail queries (often 60+ words) that drive Answer Engine Optimization. The best source for this content is your own first-party data. Analyze support tickets, sales call transcripts, and Reddit threads to discover the highly specific questions your customers are actually asking.

AI search is the new overpowered marketing channel, with traffic converting up to 17x higher than Google. To get featured, invest heavily in comprehensive "alternatives to [competitor]" and "[your product] vs [competitor]" pages, as these are the bottom-funnel queries AI models cite most often.

AI can't replicate insights gained from direct customer interaction. Methods like joining sales calls, reading product reviews, and one-on-one interviews provide "first-party data" essential for creating resonant content and differentiating your brand from competitors relying on public data.

To create resonant content, move beyond guessing customer problems. Analyze transcripts of past sales calls with an AI tool to identify recurring pain points, common questions, and the exact language your audience uses to describe their challenges.

Instead of guessing keywords, an LLM analyzes customer call transcripts to identify the exact terms customers use to describe their needs. These keywords are then automatically added to Google Ads campaigns, creating a closed-loop system that ensures marketing spend is aligned with the authentic voice of the customer.

Instead of asking AI to generate generic blog posts, use it for strategic ideation. Prompt ChatGPT with a detailed description of your ideal client and their transformation, then ask it to list their top 25 problems or questions. This provides a roadmap for creating highly relevant, problem-solving content.

When organizing your content library, add a specific category for the customer 'pain point' each asset addresses. This allows you to analyze performance based on the problems you're solving for your audience, revealing deeper insights than merely tracking topic popularity.