Understanding how your AI visibility compares to competitors is essential for strategic planning and identifying growth opportunities. This guide covers benchmarking methodology and tactics.
Setting Up Competitor Benchmarking
Step 1: Identify Your Competitors
Create tiers of competitors:
Direct Competitors: Similar products/services: same target market, similar pricing, overlapping capabilities.
Indirect Competitors: Alternative solutions: different approach to the same problem, different market positioning.
Adjacent Competitors: Related space: future potential competitors, emerging solutions, adjacent market overlap.
Two mechanical facts should shape how long that list gets. A project may track up to 20 competitors, on every plan. It is a hard limit rather than a tier perk, and the 21st is refused. And your configured list is the denominator of your share of voice, so adding an adjacent player you are not really competing with permanently depresses a number you are trying to trend. Keep direct competitors in the list; track the indirect and adjacent ones as a periodic manual review instead.
A third fact decides how you write the names, and it is the one that catches people out. Competitors are a flat list of strings with no grouping: there is no parent entity, no alias field and no way to fold a rival’s sub-brands or product lines under one heading. Matching is near-exact: case, surrounding whitespace and full stops or commas are normalised away, so “Acme Inc.” and “Acme, Inc” collapse to one competitor, but “Acme” and “Acme Cloud” do not, and neither do two spellings that differ by anything else. That cuts both ways and the second direction is the expensive one:
- Enter both names and you get two rows in the leaderboard and two units in the share-of-voice denominator, which overstates how much of the conversation that one company owns.
- Enter only the parent and an answer that names “Acme Cloud” is dropped entirely, not rolled up into Acme. It counts for nobody, which quietly understates that rival and inflates your own share.
There is no configuration that avoids both. The practical rule: enter the name form the engines actually use in answers about your category (read a few answers before deciding), and if a rival is genuinely named two ways, track both and mentally add the rows together rather than expecting the product to.
Step 2: Define Benchmark Categories
Track performance across:
- Visibility score: overall AI visibility (see understanding your visibility score)
- Share of voice: your mentions against your tracked competitor set (see share of voice explained)
- Mention rate and average rank: how often you are named, and how early
- Engine performance: all of the above broken out per engine
Two categories people expect here and should plan around instead of waiting for. Cited sources are not benchmarked per competitor; the Citations page separates your own domain from external sources and does not attribute an external domain to a rival, so “how often is Competitor A cited” is a manual read of the external list. And query coverage per competitor is not reported: a benchmark scan gives you the four aggregate figures above for that subject, not a per-prompt matrix of who appeared where.
Step 3: Select Query Benchmarks
Define query sets to monitor:
Branded Queries (Most competitive): Your brand vs competitor searches.
Category Queries (Primary opportunity): “Best [product category],” “How to [core use case],” “Comparison: X vs Y.”
Problem Queries (Emerging trends): Problem-first queries, long-tail variations, emerging use cases.
Benchmarking Framework
Visibility Tier Analysis
Tier 1: Market Leaders: Visibility Score: 70+, SOV: 30%+ of mentions, dominance in category queries, strong brand sentiment.
Tier 2: Strong Competitors: Visibility Score: 40–70, SOV: 15–30% of mentions, present in most major queries.
Tier 3: Emerging Players: Visibility Score: 20–40, SOV: 5–15% of mentions, present in some category queries.
Tier 4: Niche Players: Visibility Score: <20, SOV: <5% of mentions, limited query coverage.
Competitive Analysis Matrix
Mention quality breakdown
Position is reported in four tiers: first (named first), prominent (2nd–3rd), mid (4th–7th) and fine-print (8th or later, or named with no discernible order), plus absent. Your own breakdown across those tiers is on the Rankings page, both for the latest scan and as a share-over-time chart.
Building the same breakdown for a competitor is a different job, and the distinction is worth being precise about because it costs credits. A competitor benchmark scan runs your prompt set with the competitor as the subject, and the benchmark table reports four figures per subject: visibility score, mention rate, share of voice and average rank, each from that subject’s most recent scan.
| Brand | Visibility score | Mention rate | Share of voice | Avg. rank |
|---|---|---|---|---|
| Competitor A | 71 | 62% | 45% | 2.1 |
| Your Brand | 58 | 44% | 31% | 3.4 |
| Competitor B | 49 | 38% | 24% | 3.9 |
Read down the average-rank column for the positioning story: Competitor A is not merely mentioned more often, it is mentioned earlier. That is a different problem from a coverage gap and takes a different fix. What you will not get here is a tier-by-tier percentage split per competitor; the benchmark carries the four columns above and no per-tier breakdown, so the average rank is the positioning signal to work with.
Gap Analysis: Where to Attack
1. Coverage Gaps
Identify queries where competitors appear but you don’t. Focus on creating targeted content and building authority in these areas; a structured content gap analysis turns these coverage gaps into a prioritized roadmap.
2. Quality Gaps
Identify queries where you appear but in lower quality positions. Improve content quality and depth. Build more authority and backlinks.
3. Sentiment Gaps
Track differences in how different brands are discussed. Monitor sentiment differences and address negative perceptions.
4. Velocity Gaps
Track growth rates vs competitors. Identify fast-growing competitors. Determine what’s driving their growth and adapt your strategy accordingly. When a rival consistently outranks you, a deeper competitor analysis helps you reverse-engineer why, and our guide on why your competitor is in AI and you’re not covers the most common causes.
Engine-Specific Benchmarking
ChatGPT Benchmarking
- Track mention frequency
- Monitor brand sentiment
- Identify ChatGPT-specific coverage gaps
- Focus on recent, authoritative content
Claude Benchmarking
- Focus on authority signals
- Track academic and expert citations
- Monitor depth of mention
- Identify topic specialization gaps
Perplexity Benchmarking
Perplexity is the engine where citation is most explicit: its Search API returns ranked web results as structured data, and the answer surface reflects that same source list, so a benchmark here is closer to a source audit than a sentiment read.
- Track citation rates (most cited)
- Monitor linked mentions
- Identify content gaps
- Focus on sourced, verifiable information
Gemini Benchmarking
- Consider Google integration
- Track Knowledge Graph visibility
- Monitor official information presence
- Link SEO and GEO strategies
Common Benchmarking Mistakes
- Tracking Wrong Competitors: Monitor direct, not tangential, competitors
- Infrequent Monitoring: Track weekly or monthly, not quarterly
- Limited Query Set: Use comprehensive query sets, not just branded queries
- Ignoring Engine Differences: Monitor each engine separately
- Not Adjusting for Trends: Seasonal and market factors affect benchmarking
Benchmarking Action Plan
Week 1: Establish Baselines: Identify primary competitors, and name them explicitly so they are tracked on every scan alongside your own brand rather than noticed by accident; a project holds up to 20 of them, on every plan. Select the query set you will track (up to 15 active prompts per project on Business, 100 on Agency, 3 on Free), weighting it toward the comparison and “best X” prompts where displacement actually happens. Calculate visibility scores and SOV. Document current positioning.
Week 2–4: Deep Analysis: Analyze competitor content strategies. Identify what makes top competitors successful. Map query coverage gaps.
Month 2–3: Strategy Development: Identify priority improvement areas. Create targeted content plans. Develop authority-building initiatives.
Month 4+: Execution and Iteration: Execute content strategy. Monitor competitive movements. Adjust tactics based on results. Defend against competitive threats.
Competitive benchmarking provides crucial context for your AEO strategy. Use it to identify opportunities and defend your position.
Frequently Asked Questions
How many competitors should I benchmark against?
Start with 3–5 direct competitors so the comparison stays actionable, then layer in indirect and adjacent players as your strategy matures. Tracking too many at once dilutes focus; the goal is a tight set whose movements you can actually respond to.
How often should I run competitor benchmarking?
Track weekly or monthly rather than quarterly; AI answers shift with model updates and fresh content, so a quarterly cadence misses meaningful movement. Reserve deeper, full-matrix analyses for monthly or per-launch reviews and use lighter weekly checks to catch sudden swings.
Which metric matters most when comparing against competitors?
It depends on your stage: visibility score and share of voice show overall standing, while mention quality (first-mention vs. listed) reveals positioning gaps that raw frequency hides. Pair a quantity metric with a quality metric so you don’t mistake frequent-but-buried mentions for strong performance.
How do I benchmark when competitors rank differently across engines?
Benchmark each engine separately, because the same brand can be a first mention on Perplexity and a listed mention on ChatGPT for an identical query. Engine-specific scorecards prevent a strong showing on one engine from masking weakness on another.