Once you define your current customer, use AI as a strategic partner to forecast their evolution. Prompt ChatGPT to build out the next phases of their journey—three years from now or after they achieve a specific milestone. This helps you proactively design an ascension model of products that grows with them.

Leverage AI to conduct comprehensive research on a prospect's company, industry, and the specific individuals you're meeting. This allows you to bypass basic discovery questions and dive into more relevant, informed conversations, making the sales call more efficient and valuable for the customer.

Go beyond simple prompts. Gather raw data—comments from your social media, competitor book reviews, and podcast feedback—and feed it all into ChatGPT. Then, ask it to synthesize this data into a detailed avatar guide, identify market gaps, and suggest opportunities for your offer.

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.

In AI, low prototyping costs and customer uncertainty make the traditional research-first PM model obsolete. The new approach is to build a prototype quickly, show it to customers to discover possibilities, and then iterate based on their reactions, effectively building the solution before the problem is fully defined.

Instead of relying on static persona decks, marketers can feed raw data like sales call transcripts and support tickets into AI tools to generate live, interactive customer profiles. These apps can be instantly updated with new information, ensuring the entire organization is aligned on a current view of the customer.

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 general analysis, feed your AI a defined customer persona (e.g., "Growth Gabby") and ask it to evaluate a competitor's website copy from that specific perspective. This uncovers messaging weaknesses that directly relate to your target audience's concerns, like complexity or pricing.