I recently watched a fascinating episode of Marketing Against the Grain featuring Rachel Leist, HubSpot’s product marketing leader. The discussion centered around how AI is revolutionizing product marketing, and I was struck by the practical applications they shared that can help businesses transform their product positioning almost overnight.
Product marketing has always been about effectively communicating what your product does, why it matters, and how it helps customers. But doing this consistently across all channels has traditionally been challenging and time-consuming. With AI tools, this process is becoming dramatically more efficient and personalized.
Three Game-Changing AI Tools for Product Marketing
What caught my attention were the three specific AI applications that Rachel’s team at HubSpot is using daily:
- AI-Powered Positioning Refinement – Using Claude projects to test and refine product positioning against ideal customer profiles
- Competitive Intelligence in NotebookLM – Creating interactive battle cards that sales teams can query in real-time
- AI-Conducted Customer Interviews – Scaling customer research through automated yet conversational interviews
What makes these applications so powerful is how they leverage both internal and external data. By feeding customer transcripts, market research, and product documentation into these AI systems, marketers can create tools that truly understand their customers and products.
Positioning That Actually Resonates
The Claude project demonstration was particularly impressive. Rachel showed how her team takes existing positioning documents and runs them through an AI system that contains extensive data about their target personas. The AI then provides specific feedback on what resonates with customers and what doesn’t.
This approach solves one of the biggest challenges in product marketing – ensuring consistency across all touchpoints while maintaining authentic customer language. As someone who has worked with many businesses on their messaging, I know how easily positioning can become diluted or distorted as it moves through different departments.
“We’ve actually saved a ton of rounds of feedback and reviews because of this.” – Rachel Leist
The key to making this work is regularly updating the AI with fresh customer data. Rachel mentioned her team makes a habit of refreshing their Claude projects quarterly to ensure they reflect evolving customer expectations.
Competitive Intelligence That Sales Teams Actually Use
The NotebookLM competitive intelligence tool was perhaps the most immediately applicable idea from the episode. By organizing competitive battle cards in NotebookLM, HubSpot has created an interactive system where sales reps can ask specific questions about competitors and get immediate, contextual answers.
What’s remarkable is that this free tool is replacing expensive software solutions that cost tens of thousands of dollars annually. The sales team adoption has skyrocketed because it’s more accessible and provides information in multiple formats – text responses, audio overviews, and even podcast-style breakdowns of competitor announcements.
For businesses looking to implement something similar, Rachel recommended including:
- Top talking points against competitors
- Feature-by-feature comparisons
- Customer proof and success stories
- Specific outcomes when customers switch from competitors
- Market research and customer insights
This approach makes competitive intelligence dynamic rather than static, allowing sales teams to get exactly what they need when they need it.
Scaling Customer Research Through AI Interviews
The third tool that impressed me was Outset, which conducts AI-powered customer interviews at scale. This solves a fundamental challenge in product marketing – getting enough customer feedback to truly understand their needs and pain points.
Traditional customer interviews are incredibly valuable but limited by scheduling challenges and researcher availability. With AI interviews, Rachel’s team can conduct hundreds of interviews in the time it would take to manually complete just ten.
The system not only conducts the interviews but also analyzes the results, identifying key themes and pulling out the most valuable quotes. This creates a virtuous cycle where more customer data improves the AI systems, which in turn helps create better positioning.
The Future: Hyper-Personalized Product Marketing
The most forward-thinking concept discussed was using AI to create micro-audience targeting. Kieran demonstrated how they could take negative reviews of competitors, identify specific pain points, and automatically generate highly tailored product pages addressing those exact issues.
This points to a future where product marketing becomes increasingly personalized – not just to broad personas but to specific companies and even individuals within those companies. The ability to dynamically generate marketing content that speaks directly to a prospect’s exact situation will transform conversion rates.
As website visitors become harder to attract, making each interaction count through extreme personalization will be crucial. AI makes this level of tailoring possible at scale.
My Advice for Implementing These Tools
If you’re looking to apply these AI approaches to your own product marketing, start by gathering and organizing your customer data. Record sales and customer success calls, collect market research, and document your existing positioning. This creates the foundation that AI tools need to generate valuable outputs.
Begin with a single use case – perhaps competitive battle cards or positioning refinement – and expand from there as you see results. The beauty of these tools is that they become more valuable over time as you feed them more data.
Product marketing is more important than ever as AI accelerates feature commoditization. Your story and how you articulate value will increasingly differentiate your product. These AI tools don’t replace product marketers – they amplify their impact and allow them to focus on strategy rather than execution.
As Rachel put it so well: “Find your unlock.” Experiment with these tools until you discover the application that transforms your workflow. Once you experience that breakthrough, you’ll wonder how you ever worked without AI assistance.
