AEO Platform for Product Marketing
When a buyer asks an AI engine to compare your product against competitors, your positioning needs to be in that answer.
AI visibility at a glance
Challenges product marketing face with AI visibility
- AI engines presenting inaccurate or outdated competitive comparisons of your product
- No visibility into how AI engines position your product versus competitors in response to comparison queries
- New feature launches not reflected in AI engine responses for weeks or months after announcement
- Competitor messaging appearing more prominently in AI responses due to better content structure
- Review site data (G2, Capterra) influencing AI comparisons in ways you cannot directly control
- Inconsistent product messaging across owned and third-party sources creating confused AI brand narratives
How AEO Platform helps product marketing
Competitive positioning tracker shows exactly how AI engines compare your product against each named competitor
Messaging consistency analysis compares your product claims across your site, review platforms, and AI engine outputs
Feature mention tracking monitors which of your product features AI engines reference—and which they miss
Launch impact measurement tracks how quickly new product announcements are incorporated into AI engine responses
Win/loss analysis at the AI level: which competitors appear alongside your brand and in what context
Source attribution identifies which third-party sources (reviews, articles, forums) are influencing AI engine perceptions of your product
Features that matter for product marketing
A typical day using AEO Platform
A Product Marketing Manager opens AEO Platform first thing Monday morning to check the competitive positioning dashboard. A new comparison query report shows that for "best [category] tool for enterprise," the brand has dropped from position 2 to position 3 in AI-generated responses—a competitor recently published a comprehensive comparison page that AI engines are now citing. The PMM flags this for the content team and drafts a response strategy.
At midday, the PMM reviews the Feature Mention Report ahead of a product launch planned for next week. The report shows that AI engines currently reference 8 of the product's 12 key features, but consistently miss the two features that are core to the new launch's positioning. The PMM works with the content team to create structured feature pages and update the llms.txt file to ensure the launch features are clearly defined for AI extraction.
In the afternoon, the PMM uses Source Attribution to investigate why a competitor is appearing more favourably in AI responses for a key use-case query. The analysis reveals that the competitor has 3x more review content on G2 for that specific use case, and AI engines are drawing heavily from G2 data. The PMM adds "increase G2 review coverage for [use case]" to the next quarter's competitive strategy and sets up a monitoring alert to track progress.
AEO for Product Marketing FAQ
Common workflows
AI Brand Monitoring
Track how AI engines mention, describe, and recommend your brand across every major model.
AI Competitive Intelligence
See where competitors appear in AI responses and identify gaps in your AI visibility.
AI Brand Sentiment Monitoring
Track how AI engines describe your brand's strengths, weaknesses, and positioning.
Industries where product marketing use AEO
Other teams using AEO Platform
For CMOs
Your brand is being described by AI engines billions of times a day—do you know what they are saying?
For Content Teams
Every piece of content you publish is training data for AI engines—make sure it earns citations, not silence.
For Demand Generation
AI engines are influencing your pipeline before prospects ever fill out a form—measure and optimise that influence.
Start with the pages and proof that AI can actually use
Run the free audit to see what blocks AI from citing your site. Use the trial when you need ongoing monitoring, attribution, prompt discovery, and team workflows after the first fixes are live.