PMs Play a Hidden Role in Product Discovery

Let’s be real, most product managers don’t think of themselves as discoverability experts. You set the roadmap, unite cross-functional teams, and lead product launches. But when it comes to actually getting your product noticed, content and search have usually belonged to someone else.

That’s changing fast. Users and buyers are now heading to large language models (LLMs) like ChatGPT, Gemini, and Claude to research products and weigh their options. Instead of crawling and ranking web pages, these AI engines generate answers in real time, drawing on wide-ranging sources and recognizable patterns. So, product visibility isn’t just about ranking on Google anymore, it’s about showing up when an AI model talks about your product category or brand.

And here’s the thing: product managers have a surprising amount of influence, even if they never touch a blog post or mess with SEO settings. By shaping your messaging, spotting inconsistencies, and working hand-in-hand with marketing, you have the power to influence what AI chatbots recommend. Treat it as product discovery for the AI era, where being proactive makes all the difference.

Audit How AI Mentions Your Brand or Product

Where should you begin? Start by finding out exactly how your product appears in major LLMs. With Google, you’re used to a fixed search result; with AI, every answer can be different. Focus on these angles:

  • Branded queries: What do you get when you ask ChatGPT or other LLMs about your actual product or company name? Does it nail your unique value, or fall flat?
  • Unbranded queries: Try broad searches for your product category or the specific problem you solve. Are you mentioned as an option, or are you missing from the conversation?

If this is your first time, spend a few minutes running quick prompts like:

  • “What are the top [your category] products for [use case]?”
  • “Can you tell me about [your product name]?”
  • “Which companies solve [a common customer problem]?”

You’ll probably notice the answers don’t always line up with the true market leaders, or may totally miss your core messaging. Sometimes your product isn’t mentioned at all. Sometimes it’s described using outdated info or inaccurate details. It’s a clear sign that LLM product visibility is constantly shifting, driven by the content and signals AI models pick up.

Spot Positioning Gaps and Inconsistencies

After auditing, step back and review what the AI is saying. Product managers are used to spotting trends in feedback or user data; think of this as a similar exercise, but focused on your category’s representation in LLMs. 

Here’s what to keep an eye out for:

  • Are you even in the conversation? If core LLM queries pass you over, your visibility probably lags behind competitors.
  • Is your messaging accurate? Sometimes LLMs highlight features you’ve dropped or push old positioning you retired ages ago. Check that your selling points come through, and that they’re both current and consistent.
  • How do you compare to competitors? Pay attention to which players come up ahead of you, and the language used to pitch them. Look for key traits LLMs seem to latch onto.
  • What’s being overlooked? You might realize that specific features, integrations, or even use cases aren’t mentioned alongside your brand, even though you offer them. That’s an easy opportunity to shore up your presence.

This kind of pattern-finding helps you prioritize what to fix. Maybe your cloud security product isn’t showing up for “zero trust” queries, even though it’s a headline feature. Or maybe ChatGPT is pushing a competitor’s unique language because their team made sure it’s everywhere that matters. Take this as proof: AI can only echo what’s published and consistent across public channels.

Partner With Marketing to Boost LLM Visibility

No need to become an SEO guru, but working closely with marketing makes a huge difference. Here’s how product managers and marketers can level up LLM product recommendations together:

  • Align on messaging: Ensure the positioning you’ve crafted as a PM is reflected everywhere, from your website and blog to press releases and help docs. AI trains on everything it can see.
  • Share your audit takeaways: Bring clear, specific LLM examples to your marketing meetings. Showing what AI “thinks” about your product instantly puts these priorities on everyone’s radar.
  • Suggest new content priorities: Pinpoint missing feature pages, FAQs, or resources that could fill in gaps where you’re not mentioned or misunderstood.
  • Champion third-party updates: LLMs often reference sites like Wikipedia, G2, or analyst reports. Make sure those listings are up to date. Sometimes a quick fix there does more than another round of homepage tweaks.
  • Keep tabs on the competition: Even if marketing owns the messaging, it pays to track where and how LLMs are positioning your rivals. Use those insights to adjust your strategy and stay ahead.

Small, steady updates across trusted sources can quickly shift how AI sees your product. Consistency wins here. PMs who spot what’s missing and push for updates can keep their products in the recommendation set, before missed mentions cost you valuable organic visibility.

Track Changes and Keep Optimizing

AI models change fast. The way ChatGPT answers your favorite prompt today might be different next month, depending on updates and new data. Tracking your LLM visibility isn’t a box you check once, it’s an ongoing effort.

Product teams who review their LLM presence regularly are the ones who keep their edge. Here’s what an ongoing workflow looks like:

  • Set a routine cadence: Monthly or quarterly check-ins on key queries will help catch shifts early.
  • Measure what moves the needle: If new content or updates spark better LLM visibility, take note, and do more of it.
  • Jump on any errors: Outdated info, broken links, or hallucinated details can pop up anytime. Flag them early and update them so they don’t spread.
  • Spot new search trends: As LLMs evolve, new product categories or buying questions may crop up. Stay flexible and ready to reposition.

Keeping this feedback loop running means you won’t be caught off guard. This is the next era of answer engine optimization (AEO), and PMs who get it will lead the way, driving organic visibility, no matter how AI search changes.

Murmur Makes LLM Product Discovery Simple

Managing LLM visibility can sound like a lot, but it doesn’t have to be. Murmur does the heavy lifting for you, so you can focus on building great products instead of running endless audits. 

  • It tracks how your brand appears in both branded and unbranded queries across ChatGPT, Gemini, Claude, and more.
  • It shows you exactly where you’re winning, getting ignored, or being misrepresented.
  • It delivers clear scores, trendlines, and actionable suggestions, without any technical setup required.
  • It sends alerts if your positioning or the competitive set shifts in LLMs.

Just type in your brand and let Murmur handle the rest. You’ll stay visible and top-of-mind in AI chats, without sweating the details or chasing endless updates.

Want to see how your product looks to AI chat engines? Visit Murmur to get a full view of your LLM rankings.