AISEOCourse.academy Module 3

Module 03 · Lesson 4 of 4

Tracking Competitor Visibility

About 11 minutesPrerequisite: Lesson 3.3
After this lesson you cancompute mention share for you and named competitors on your query set, maintain a monthly leaderboard, and convert leaderboard movement into content and coverage priorities.

Your visibility number means nothing in isolation. Mentioned in 30 percent of answers sounds strong until you learn the leader sits at 70. Competitor tracking puts your numbers in context, and context is the only thing that makes them decision-grade.

Mention share, defined

DefinitionMention share is the percentage of your query set on which a brand is mentioned or cited in the generated answer. Compute it per run: brand mentions divided by queries that produced any AI answer. Track mentions and citations as separate shares.

Two brands matter to the denominator: queries where no AI surface appeared do not count for or against anyone. If 30 queries produced AI answers on 24, and you appeared on 6, your mention share is 25 percent. Same arithmetic for each competitor, same run, same denominator.

The leaderboard

BrandRun 3Run 4Direction
Competitor A58%54%Slipping
Competitor B29%38%Climbing
You8%13%Climbing slowly

Illustrative numbers, real reading. Competitor B gained nine points in one week: worth one investigation pass (lesson 3.3's questions) to find what changed, because sometimes it is one new comparison page, and that is a move you can answer. Your own five-point gain after a content update is evidence the update worked, the kind you cannot buy from a dashboard.

From leaderboard to priorities

Each month, the leaderboard hands you exactly three conversations to have. Where you rose: what did you do, and can you repeat it? Where you fell: which queries flipped, and was it content, coverage, or noise repeating in the new direction? Where a competitor surged: what did they publish or earn, and does it expose a gap you should close first? Those three answers become next month's shortlist, and the cycle continues. This loop, run honestly, is the actual practice of AI SEO: measurement informing content, content informing the next measurement.

Worked example: one flipped query (illustrative)
  1. The log shows you cited for "how to choose an seo tool" in runs 1-3, absent in run 4.
  2. Competitor B appears in run 4 with a new comparison page, dated last week.
  3. Open both pages side by side. Theirs loads faster, answers in the first hundred words, adds a pricing table yours lacks.
  4. Decision: this slot is ownable. Brief the upgrade now, schedule it, and watch runs 5-6 for the flip back.
Workbench 3.4
  1. Name the two competitors who appear most in your log. Add a column per brand if you have not already.
  2. Compute mention share and citation share for all three brands on your latest run.
  3. Build the leaderboard table and write one sentence per brand: direction and suspected cause.
  4. Pick the single query where your absence costs most, and mark it as the first Module 4 brief.
Self-check
Why use only queries that produced AI answers as the denominator?
Queries with no AI surface cannot contain anyone's mention. Including them deflates every share and makes movement look smaller or bigger than it is, depending on how surfaces shift.
A competitor jumped eight share points in a week. What do you do?
Investigate before reacting: run the 3.3 interrogation on their newly cited pages. Find the specific change, then decide whether the slot is ownable with better content or belongs to coverage.
Is a one-week decline a problem?
Not by itself; variability guarantees weekly wobble. Worry when a decline repeats across three or more runs, and always investigate what changed before changing anything yourself.
Key principleVisibility is relative: your number only means something next to your competitors' numbers on the same query set.

Sources used in this lesson
Google Search Central: AI features and your website

Previous 3.3 Citation Source Analysis