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Technique
detection

Competitor Monitoring

Competitor monitoring in AI search means recording which rival brands AI engines recommend, and where they appear instead of you. This page explains the technique.

This capability was part of the paid AEO Platform product, which closed on 2026-10-02. It is not available. This page explains the technique for reference.

Quick answer
Understanding your own AI visibility is only half the picture. Competitor monitoring records which other brands AI engines recommend when users ask about your category, how those competitors are described, and where they appear instead of, or alongside, your brand. It turns a vague sense of competitive pressure into an engine-by-engine breakdown.
How it works

Competitor Monitoring in detail

Competitor monitoring begins with a defined competitive set: the specific brands you want to compare. You can also discover competitors by reading AI engine responses to your category queries and noting which brands appear alongside yours repeatedly.

On each run of the query bank, every competitor is recorded across every prompt and every engine. Each competitor mention gets the same metadata as your own: sentiment, position in the response, context type, and co-mentioned brands. This produces a symmetric dataset where your brand and every competitor are measured with the same method.

The data is usually shown as a leaderboard, a trend chart, and a gap matrix. The leaderboard ranks brands by Share of Model. The trend chart shows how each score changes over time. The gap matrix highlights prompts where a competitor appears and you do not. These are the highest-value optimisation targets.

Benefits

Why Competitor Monitoring matters

1

See which competitors AI engines favour for each prompt family in your category

2

Spot new competitors entering AI answers before they appear in organic search

3

Identify the specific prompts where competitors appear and you do not

4

Track competitor sentiment to spot reputational shifts early

5

Prioritise content creation based on competitive gap data rather than guesswork

Use cases

When to use Competitor Monitoring

A product marketing team finds that a lesser-known competitor has higher AI visibility for "enterprise" queries and adjusts messaging.
An SEO lead identifies five high-intent prompts where two competitors appear but the brand does not, then creates targeted content.
A VP of marketing uses competitive trend data to justify budget for an AI visibility programme.
An agency includes AI competitor data in monthly client reports to show the visibility gap.
FAQ

Competitor Monitoring FAQ

Related terms

Key concepts

Share of ModelBrand Recommendation RateCompetitive Displacement RateAI Visibility Platform
Related features

Explore more features

Brand Mention Tracking

detection

Brand mention tracking is the practice of recording when and how AI engines mention your brand across models and prompts. This page explains the technique.

Share of Model Scoring

detection

Share of Model is the percentage of AI answers in a category that mention your brand. This page explains how to calculate and read it.

Smart Alerts

detection

AI visibility alerts notify a team when mentions, sentiment, or citations change. This page explains how baselines and thresholds make such alerts useful.

SEO-AI Gap Analysis

resolution

SEO-AI gap analysis compares your Google rankings with your AI mention rates to find where the two channels disagree. This page explains the technique.

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