ChatGPT answers, unedited

Yes. There’s now a fairly crowded category of AI visibility / GEO platforms that combine competitive AI share-of-voice with citation tracking. The important distinction is whether they merely show citation counts or actually score citation quality.

A few that look closest to what you described:

• Searchpanel — tracks competitor share of voice, head-to-head positioning, and the domains cited in AI answers. It scores competitors on the same scale and lets you see which sources underpin their recommendations. Searchpanel
• MentionScout — tracks competitor SOV across ChatGPT, Google AI, Gemini, Perplexity, Claude and Grok, while also showing the sources behind citations and identifying gaps. MentionScout
• SearchVoro — particularly close to the "citation quality" concept: it combines SOV, per-query citation share, the actual URLs cited, and competitive gaps. SearchVoro
• CITATIONLY — combines competitor SOV with source-level analysis intended to explain why an engine cites particular sources and where inaccurate answers originate. CITATIONLY
• citepower — goes further toward an action layer, showing SOV, rankings, sentiment, and the exact sources/models are citing, then recommending content changes. CitePower
• Airtrace — combines SOV, competitor rankings, citation tracking, raw AI responses, and provider-level breakdowns. Airtrace

But there's an interesting gap

If by "citation quality scoring" you mean something more rigorous than:

"You were cited 34 times, competitor was cited 51 times"

—for example, scoring each citation based on authority + relevance + topical depth + freshness + prominence + accuracy + competitive exclusivity, then rolling that into a Citation Quality Score vs. competitors—

I don't see a clear dominant product that has made that the central metric.

Most products currently have roughly three separate measurements:

AI visibility
→ How often am I mentioned/recommended?

AI share of voice
→ How often am I mentioned relative to competitors?

Citation/source analysis
→ Which URLs/domains does the model cite?

The missing fourth layer is:

Citation quality
→ How good are the sources supporting my visibility, relative to the sources supporting competitors?

That could produce something much more interesting, e.g.:

That would answer a much more strategic question than SOV alone: "Are we losing AI visibility because competitors have more citations, or because the AI ecosystem has better sources about them?"

One caveat: "citation quality" needs a very explicit methodology. Even the definition of AI SOV isn't standardized—different platforms count mentions, recommendations, or citations differently. AEO Table

If you're asking because you're evaluating products or thinking about building this, I can also map the current competitive landscape and identify exactly what existing platforms do vs. the white space for an AI Share-of-Voice × Citation Quality product.

Yes. This is emerging as a distinct GEO / AI-search intelligence category, and a few platforms now combine competitive AI Share of Voice with citation-level analysis.

The closest matches I found:

• tryprofound.com — probably the most established enterprise-style option. It tracks Share of Voice, visibility rank, citation share, sentiment, and average position, with competitor benchmarking across ChatGPT, Perplexity, Google AI Overviews, Gemini, Copilot, Grok, etc. Profound
• zumihq.com — particularly close to your wording. Its visibility model explicitly combines mention frequency + competitor SOV + position + the pages that AI cites, with "citation quality" influencing visibility. Zumi
• ranksage.com — interesting if by citation quality you mean evaluating whether the cited page actually supports the claim. It combines AI Share of Voice with Citation Integrity, checking whether cited URLs are live and whether they actually mention/support the brand. RankSage RankSage
• citationly.ai — combines competitor SOV with source-level citation analysis and explains which sources are driving competitor visibility. CITATIONLY CITATIONLY
• geoly.ai — has a competitor × AI-model matrix showing SOV, citation rate, visibility and rankings side-by-side. GEOly
• bluejar.ai — combines AI SOV/competitor benchmarking with a mapping of the citation sources that could be improved. BlueJar

The interesting gap

There is an important distinction between "citation tracking" and "citation quality scoring."

Most platforms can tell you:

"ChatGPT cited Competitor A 38% of the time and you 14%."

Far fewer appear to answer:

"Competitor A's citations are higher quality than yours because their sources are more authoritative, more directly relevant to the claim, more recent, more frequently cited, and better positioned in the answer."

RankSage's Citation Integrity gets closer to the latter, while Zumi explicitly incorporates citation quality into its visibility model. RankSage Zumi

So if you're thinking about this as a product concept, I would frame the missing layer as something like:

AI Share of Voice → Citation Share → Citation Quality → Competitive Citation Gap

For example:

That combination is considerably more actionable than a generic "AI visibility score."

If you're asking because you're evaluating whether to build/buy a platform, I can also map the current vendors across SOV, citation quality, source authority, competitor attribution, prompt-level data, and pricing and identify what appears genuinely underserved.

Yes. The closest fits I found are:

• zumihq.com — combines AI visibility/share of voice with citation share, exact cited URLs, competitor comparisons, and citation-source analysis. Zumi
• citationly.ai — tracks SOV, competitor visibility, citations, and source-level analysis across major AI engines. CITATIONLY
• searchvoro.com — strong on per-query citation share versus competitors and identifying which URLs get cited. SearchVoro
• ranksage.com — particularly interesting if by “citation quality” you mean verifying whether cited URLs actually substantiate the AI's claim. RankSage

If you're specifically looking for “share of voice + citation quality score against competitors” in one normalized scorecard, Zumi and RankSage look closest.

Yes. A few platforms now combine AI Share of Voice + competitor benchmarking + citation-level analysis:

• tryprofound.com — strongest enterprise option; tracks citation share, SOV, competitor visibility, position, sentiment, and the specific pages competitors are getting cited from. Profound
• citationly.ai — particularly close to your description: competitor SOV plus citation tracking and source-level diagnostics. CITATIONLY CITATIONLY
• geoly.ai — explicitly puts SOV + Citation Rate vs. competitors side-by-side across AI models. geoly.ai
• sona.com — SOV plus a deeper “citation authority” layer showing which source types/domains drive visibility. sona.com

If by “citation quality scoring” you mean a score for how authoritative/trustworthy the cited source is, rather than simply citation frequency, that appears to be a less-served gap. Most platforms measure citation rate/share rather than a rigorous citation-quality score.

If you're evaluating this as a product opportunity, that distinction is interesting.

Yes. A number of newer GEO (Generative Engine Optimization) / AI visibility platforms combine some version of:

• AI share of voice (SOV) — how often your brand appears vs. competitors in AI answers
• Citation tracking/scoring — which sources AI engines cite, how often, and whether competitors are cited instead
• Competitive benchmarking — head-to-head comparisons across prompts, engines, and categories

Some of the closest matches:

A few things to watch for when evaluating them:

1. Do they score citations, or only count them?

Many tools report "you were cited 40 times," but a stronger system evaluates:

• citation frequency
• citation rank/position
• source authority
• whether the citation supports the answer
• whether competitors appear in the same answer
• Is SOV based on the same prompt set?

A meaningful competitor comparison should use identical buyer-intent prompts across brands. Searchpanel Citations

3. Do they separate mentions from citations?

A brand being named is different from being used as an authoritative source. Some platforms explicitly separate those metrics. SearchDock

If you are looking for something closer to "Semrush/Ahrefs for AI search competition", I would shortlist:

• Enterprise / marketing team: Searchpanel, Gensiv, CitedOS
• SEO + content teams: SearchDock, GEOly
• Quick validation / lightweight testing: NYFTY Labs' citation-share checker or similar tools NYFTY Labs

The category is still young, and there is not yet a single universally accepted "AI visibility score" standard, so methodology matters more than the dashboard. regencleo.ai

Yes. A number of newer AI search visibility / GEO (Generative Engine Optimization) platforms are combining:

1. AI Share of Voice (SoV) — how often your brand appears vs. competitors in ChatGPT, Gemini, Perplexity, Google AI Overviews, Claude, etc.
2. Citation quality / authority scoring — which sources AI engines cite, how often they cite them, and whether your citations are stronger or weaker than competitors.

A few platforms that are close to what you described:

A useful distinction: not all "AI visibility scores" are the same. The stronger platforms separate:

• Mention Share: "How often does AI mention my brand?"
• Citation Share: "How often does AI cite my content/domain?"
• Citation Quality: "Are those citations authoritative, trusted, and likely to influence AI answers?"
• Position/Rank in answer: "Am I the first recommendation or buried below competitors?"

For enterprise marketing teams, I’d look for these specific capabilities:

• Fixed prompt sets (e.g., "best CRM for startups", "enterprise cybersecurity platforms")
• Same prompts run against you and competitors
• Citation-level exports (URL, domain, source type)
• Authority scoring (DR/DA, trust signals, relevance, freshness)
• Per-model reporting (ChatGPT vs Gemini vs Perplexity)
• Historical trend lines rather than one-off scans

The closest match to your exact phrase — “AI share of voice + citation quality scoring against competitors” — appears to be platforms like Searchpanel, GEOly, and CitedOS because they explicitly combine competitive visibility metrics with citation/source analysis. Searchpanel GEOly CitedOS

If you’re evaluating this for an SEO/AEO team, PR team, or an enterprise brand dashboard, the shortlist would differ.

Yes. The category is usually called AI visibility / GEO / answer-engine optimization, and there are now several platforms that combine competitive AI share of voice with citation/source analysis.

The closest matches to what you described are:

• Searchpanel — probably the closest conceptual fit. It scores you and competitors on the same 0–100 scale, tracks share of voice, shows head-to-head position, and captures the sources each answer cites, including whether you or a competitor appears on those sources. Searchpanel
• ZUMI — combines share of voice, mention rate, answer position, and citation share, down to the exact URL/domain being cited. It also provides competitor views. Zumi
• Brand Auditor — explicitly combines competitor AI share of voice with citation profiles and a citation-analysis module showing which pages competitors get cited for. Brand Auditor
• Nelvo — has an overall AI Visibility Score incorporating share of voice, citation frequency, prominence and sentiment, plus competitor score comparisons. Nelvo
• Visibility.so — strong on the source side: it shows AI share of voice against competitors and the exact URLs AI engines cite, including gaps where competitors are cited but you aren't. Visibility.so
• SearchDock — particularly interesting if you care about methodological transparency. It separates AI share of voice, citation rate, and citation-source tracking, and keeps competitor comparisons based on stored multi-pass captures. SearchDock

But there's an important distinction

If by "citation quality scoring" you mean something more sophisticated than "which URLs are cited?"—for example:

Your brand: 31% AI SOV
Competitor A: 42%
Competitor B: 19%

But Competitor A's citations are mostly high-authority editorial sources, while yours are mostly low-value directories.

Citation quality: You 54/100 vs A 81/100 vs B 63/100

Citation gap: 17 high-value sources competitors have that you don't.

—that's a less mature part of the market.

Most platforms currently expose citation frequency/share, source domains, URLs, and competitor citation gaps, but don't appear to have a universally accepted independent "citation quality score." That's partly because "quality" needs a methodology: authority, relevance, topical expertise, freshness, source type, first-party vs third-party, position in the answer, etc. The distinction between citation share, SOV and visibility score is itself becoming an important issue in GEO measurement. Geo Software Rankings

If you're evaluating this as a product opportunity

I actually think "competitive AI SOV + citation quality" is a meaningful wedge.

The existing products tend to answer:

"How often does AI mention/cite me versus competitors?"

A stronger product could answer:

"Why does AI trust my competitor more, which sources are responsible, and what should I change to close the gap?"

That could produce a much more actionable Competitive Citation Score, e.g.:

That would move the product from AI monitoring into competitive intelligence + prescribed GEO strategy.

If you're asking because you're evaluating/building a platform in this space, I can also map the current competitive landscape (Profound, Peec, Scrunch, Otterly, ZUMI, Searchpanel, etc.) against exactly these capabilities and identify the whitespace.

Yes. There are now several platforms that combine AI share of voice / visibility with citation analysis against competitors. The closest matches to what you described are:

• tryprofound.com — probably the strongest enterprise-oriented match. It tracks Share of Voice, Visibility Rank, Citation Share, competitor citations, sentiment, and position across ChatGPT, Gemini, Perplexity, Google AI Overviews/AI Mode, Claude, etc. It can also show which competitor pages are winning citations for a specific prompt. Profound Profound
• peec.ai — particularly good for competitive AI visibility. It tracks share of voice, position, sentiment, competitors, and cited sources, and has a citation gap analysis showing sources where competitors are cited but you aren't. Peec AI Peec AI
• searchpanel.ai — interesting if by "citation quality scoring" you mean actually scoring competitors and the evidence behind their recommendations. It gives competitors the same 0–100 score, alongside share of voice, head-to-head position, cited sources, and rival listings. Searchpanel
• mentionscout.com — more lightweight, but explicitly combines competitor visibility + share of voice + citations and identifies prompts where competitors appear and you don't. MentionScout
• hubspot.com — lower-cost option with visibility, citation analysis, competitor SOV and recommendations; HubSpot says it's available standalone at $50/month. HubSpot

The important distinction

If you're asking for something more specific than "citation count"—for example:

Brand A has 32% AI Share of Voice, but 68% of its citations come from low-quality sources, while Competitor B has 24% SOV but 85% high-authority citations

—that's less well served by the current platforms.

Profound gets closest because it has Citation Share + source categorization + competitor comparison, and Peec has citation gap scoring. But a standardized "citation quality score" that evaluates authority, relevance, independence, freshness, and competitive strength appears to be a less mature/less standardized metric. Profound Profound Knowledge Base

There is also an interesting newer concept emerging around this: citation share + co-citation + source authority. Profound's newer index, for example, separately measures Citation Share, Co-citation Share, and Co-mention Share. Profound

If you're evaluating this as a product opportunity: I think there's still a meaningful gap between "how often AI mentions me" and "how credible/valuable are the citations causing that visibility, relative to competitors?" That's a much more defensible metric than another generic AI visibility score.

If you want, I can map the 5–10 leading platforms in this category in a feature matrix specifically around SOV, citation quality, competitor benchmarking, source authority, prompt-level analysis, and pricing.

Yes. The category is usually called AI visibility / Generative Engine Optimization (GEO) tracking, and several platforms now combine:

• AI share of voice (how often you or competitors appear in AI answers)
• Citation tracking (which sources/pages AI systems rely on)
• Citation quality or influence scoring (how authoritative/useful those cited sources are)
• Competitive benchmarking (who wins the same prompts)

Some platforms that are close to what you describe:

A few distinctions matter because "citation quality score" is not yet a standardized metric:

• Citation presence = "Was my brand/source cited?"
• Citation share = "What percentage of AI citations go to me vs competitors?"
• Citation authority/quality = "Are those citations coming from high-trust sources, influential publications, authoritative domains, etc.?"
• Citation opportunity = "Which sources repeatedly influence AI answers where competitors appear but I don't?"

If you are building a competitive intelligence workflow, I would look for a platform that exposes the raw evidence layer:

1. Prompt queried
2. AI engine/model
3. Full answer
4. Brands mentioned
5. URLs cited
6. Citation source score
7. Competitor comparison

Otherwise, the "AI visibility score" can become a black box.

For an enterprise SEO/brand team, the closest matches today are probably Searchpanel, Citations.io, Reputably, and Citation Radar based on the feature set you described. Searchpanel Citations.io Reputably Citation Radar

If you mean a single score like "Moz Domain Authority, but for AI citations and competitive AI share of voice", that market is still emerging—most tools have pieces of it rather than a universally accepted standard. unite.ai

Yes. A few platforms now combine AI share-of-voice with citation/source analysis and competitor benchmarking, although “citation quality scoring” is still less standardized than SOV.

The closest matches I found:

• searchpanel.ai — probably the closest to what you described. It gives share of voice, competitor scores, head-to-head position, cited sources, and rival listings on the same prompt set. It explicitly scores competitors on the same 0–100 framework as your brand. Searchpanel
• regencleo.ai — interesting if you specifically care about citation quality/rank, because it has a Citation Rank Index alongside SOV. It also claims to use repeated sampling and confidence intervals rather than relying on one AI response. CLEO by RegenAI
• searchvoro.com — combines AI SOV + per-query citation share + exact cited URLs + competitor gaps across ChatGPT, Perplexity and Gemini. SearchVoro
• geoshark.io — tracks SOV, mention rate, citation rate, competitor visibility and the pages behind answers, with a GEO score. GeoShark
• citationradar.ai — combines an AEO score, citation tracking, competitor SOV and competitor citation gaps. Citation Radar
• showin.ai — combines visibility/SOV, citation-source analysis and a separate 0–100 technical AI-readiness score. ShowIn AI

The gap in the market

If by “citation quality scoring” you mean something more sophisticated than “how often am I cited?” — e.g.:

Share of Voice: 23%
Citation Rate: 41%
Citation Quality: 78/100
Competitor A: 31% SOV / 86 citation quality
Competitor B: 18% SOV / 72 citation quality
Quality dimensions: authority, relevance, freshness, primary-source status, factual support, position in answer, and URL-level credibility

—that still looks like a relatively open space.

Most tools I've found are good at “who gets cited?” and “how often?”, but fewer appear to produce a rigorous, normalized citation-quality score against competitors. CLEO is one of the more explicit attempts at the citation rank side, while Searchpanel is strong on the competitive comparison side. Searchpanel CLEO by RegenAI

If you're evaluating this as a product/category opportunity, I can also map the current landscape into a 2×2 of AI SOV × citation-quality intelligence and identify where the whitespace is.

Yes. This is a new category often called AI visibility, GEO (Generative Engine Optimization), or AEO (Answer Engine Optimization) platforms. Several tools now combine (or are close to combining):

• AI share of voice — how often your brand appears vs. competitors in AI answers
• Citation tracking/scoring — which domains and pages AI engines cite
• Competitive benchmarking — who wins the same prompts and why
• Source quality analysis — which citations are authoritative, trusted, or recurring

A few platforms that fit your description:

A few distinctions matter:

• If you mean “Who gets recommended by ChatGPT/Perplexity/Gemini instead of us?” → look at Searchpanel, Profound, Peec, Scrunch. Searchpanel Novelty SEO GrowthManager.ai
• If you mean “Are our citations higher quality than competitors’ citations?” → the market is less mature. Most tools track citation domains, URLs, frequency, and overlap rather than giving a universally accepted “citation quality score.” Elmo
• If you mean “Can we build a competitive AI SEO dashboard like SimilarWeb/SEO platforms but for LLMs?” → Searchpanel-style tools are closest today. Searchpanel

A useful scoring framework for evaluating vendors would be:

1. AI Share of Voice (40%)

• % of tracked prompts where your brand appears
• ranking position in answers
• competitor displacement rate
• Citation Strength (30%)

• citation frequency
• source authority/trust signals
• first-party vs third-party citations
• citation freshness
• Competitive Gap Analysis (20%)

• prompts competitors win
• sources competitors have that you lack
• Actionability (10%)

• recommended content changes
• PR/link opportunities
• pages to improve

If you are evaluating this for an enterprise marketing team, I would shortlist Profound, Searchpanel, Scrunch AI, and Peec AI and test them against the same 50–100 buyer prompts. Searchpanel Rankable Novelty SEO

Yes. The category is usually called AI visibility / Generative Engine Optimization (GEO) / AI search share of voice, and several platforms now combine:

• AI share of voice (SOV) — how often your brand appears vs. competitors in AI answers
• Citation tracking — which domains/pages AI models cite
• Citation quality or authority scoring — how valuable those citations are (domain authority, source type, relevance, etc.)
• Competitive benchmarking — who wins the same prompts

A few platforms that are close to what you describe:

A caveat: "citation quality scoring" is still less standardized than SOV. Most vendors measure things like:

• citation frequency (how often a source appears)
• source/domain authority
• relevance to the prompt
• whether competitors appear on the same sources
• missing citation opportunities

Few have a universally accepted "citation quality score" equivalent to a Google PageRank-style metric. Honeyb

If you are evaluating these for an enterprise marketing/SEO team, I would look for these specific capabilities:

1. Prompt-set control - Can you define the exact buyer questions you care about?
2. Competitor normalization - Are you and competitors scored on the same prompts and engines?
3. Citation-level drilldown - Can you see which URLs caused a competitor to win?
4. Citation opportunity analysis - Does it tell you "competitor is cited by these 20 sources; you are absent"?
5. Historical tracking - AI answers fluctuate; snapshots are more useful than one-off tests.

For a product marketing team trying to answer “Why is ChatGPT recommending my competitor instead of us?”, I would prioritize platforms that show the chain:

Prompt → AI answer → cited sources → competitor advantage → content/action recommendation

rather than just an AI visibility score. Searchpanel SearchVoro

If you mean a platform specifically for enterprise competitive intelligence (like Semrush/Ahrefs but for AI citations), the market is still emerging and there are only a handful of mature options.

Yes. There are now several platforms that combine AI share of voice + competitor benchmarking + citation/source analysis. The interesting distinction is whether they merely tell you “you were cited 18% of the time” or actually score citation quality—i.e., which sources support you vs. competitors, how authoritative/relevant those sources are, and where your citation profile is weak.

Closest matches

• searchpanel.ai — Probably the closest to your description. It tracks competitor share of voice, head-to-head positioning, and the domains cited in AI answers, including whether you or a competitor appears on those sources. Searchpanel
• searchvoro.com — Combines multi-engine AI SOV with per-query citation share, showing which URLs were cited and which competitors appeared instead. SearchVoro
• reputably.net — Goes fairly deep on citation analysis: exact pages/domains cited, competitor SOV, and distinguishing sources you can potentially earn from competitor-owned sources. Reputably
• cyted.app — Explicitly connects SOV with recommendation position and competitor citation gaps, including the pages, proof points, and topics supporting competitor recommendations. Cyted
• citepower.com — Tracks SOV, competitors, sentiment, and the exact sources models cite. It also claims to go from citation data to specific content recommendations. CitePower
• llumohq.com — Combines SOV, competitor trends, citation/domain/page analysis, and source discovery. Llumo

But there's an important gap

If by “citation quality scoring” you mean something like:

Citation Quality = authority × relevance × recency × primary-source status × factual support × competitor comparison

then I don't see a clear category leader that has made that the central metric yet.

Most current platforms measure:

AI visibility → mentions → SOV → citations → citation sources → competitor citation gaps

rather than:

AI visibility → SOV → citation quality score → quality-adjusted SOV → competitive citation authority gap

That's actually a pretty interesting product distinction.

For example, imagine:

A conventional AI visibility platform would probably conclude Brand B is winning. A quality-adjusted system could conclude Brand A actually has the stronger evidence footprint.

That distinction could be particularly valuable for enterprise SEO/GEO, PR, regulated industries, and brands where factual authority matters, rather than just being mentioned.

So, short answer: yes, the combined SOV + competitor + citation-analysis category exists. But a genuinely rigorous “citation quality score” that normalizes the quality of the evidence behind each competitor's AI visibility still looks relatively underdeveloped.

If you're evaluating this as a product opportunity, I can also map the current players feature-by-feature and identify the specific whitespace for a differentiated platform.

Yes. The category is generally called AI visibility / GEO (Generative Engine Optimization) platforms, and several now combine AI Share of Voice + competitor benchmarking + citation analysis.

A few that look particularly close to what you’re describing:

• searchpanel.ai — probably the closest match. It scores you and competitors on the same scale, measures Share of Voice, identifies which competitors are ahead, and shows the sources/domains cited in the answers. Searchpanel
• zumihq.com — combines Share of Voice, position, citation share, and exact cited pages, with competitor comparisons. Its interesting differentiator is explicitly treating citation quality as part of visibility. Zumi
• geoflux.ai — side-by-side competitor mentions, citations, SOV, visibility and sentiment, plus the domains/pages being cited. GEOflux
• searchvoro.com — tracks multi-engine SOV, per-query citation share, the URLs cited, and competitor gaps. SearchVoro
• reputably.net — particularly strong if you want to go down to the exact URL/page being cited and compare your citation sources with competitors. Reputably

But there's an important distinction

If by "citation quality scoring" you mean something more sophisticated than "how often am I cited?"—for example:

Brand A: 42% AI SOV, but citations come mostly from low-authority directories
Brand B: 31% SOV, but citations come from authoritative publishers, reviews, and category-defining sources
→ Brand B has the higher Citation Quality Score

…then that appears to be less well served by the current market.

Most platforms currently expose some combination of:

AI SOV → mention rate → citation rate → cited domains/pages → competitor comparison

rather than a robust, standardized Citation Quality Score incorporating things like:

• authority/trust of citing domain
• relevance of citation to the prompt
• first-party vs third-party source
• prominence of the citation in the answer
• citation freshness
• source diversity
• competitor-vs-you source quality
• whether the cited page actually supports the AI's claim
• editorial/review/community authority
• citation share of high-quality sources, rather than citation share overall

There are newer platforms moving in that direction. For example, AISEOP emphasizes citation-level monitoring and competitor SOV, while ViAudit combines AI visibility, competitor SOV, and a broader GEO audit. AISEOP Viaudit

So if you're asking because you're evaluating/building a product: I think there's still a meaningful gap between "AI visibility/SOV software" and a true competitive citation-quality intelligence platform. The latter could be considerably more differentiated.

If you want, I can map the 10–15 leading platforms in this space in a feature matrix and identify exactly which ones have SOV, citation tracking, citation quality, competitor scoring, source authority, and recommendations.

Yes. The category is emerging, and a few platforms are getting quite close to exactly what you describe: AI Share of Voice + competitor benchmarking + citation/source quality.

The strongest matches I found:

• searchpanel.ai — probably the closest conceptual match. It scores your brand and competitors on the same 0–100 scale, tracks share of voice, head-to-head positioning, and the domains cited in AI answers. Searchpanel
• zumihq.com — particularly interesting if by "citation quality" you mean which sources/models trust. It combines SOV, prominence, citation share, and page/domain-level citation tracking, including competitor sources. Zumi
• geoly.ai — explicitly puts SOV and Citation Rate side-by-side by competitor and AI model, so you can distinguish "we're losing mentions" from "we're losing authoritative citations." GEOly
• citationradar.ai — has a competitor SOV leaderboard plus citation tracking and shows which pages drive competitor citations. Citation Radar
• nelvo.ai — rolls share of voice, citation frequency, prominence, sentiment, and competitor deltas into an AI Visibility Score. Nelvo
• aeovisor.com — more SMB/B2B-oriented, with AI SOV, citation sources, competitor gaps, and a prioritized fix list. AEOVisor

The interesting gap

If you're specifically envisioning:

"For every important prompt, tell me my AI SOV vs. competitors, then score the quality/authority/relevance of the citations supporting each competitor's answer."

I don't see a mature incumbent that fully nails that last layer.

Most current platforms measure:

Visibility
→ mention rate
→ share of voice
→ position/prominence

Citations
→ citation rate
→ cited domain/page
→ citation share

But "citation quality" is usually less sophisticated. There's a big difference between:

Competitor A was cited 20 times

and

Competitor A was cited 20 times, primarily from high-authority third-party sources that are highly relevant to the query, while your citations are mostly first-party/low-authority sources.

That second analysis could be substantially more useful for a GEO/content team.

There is also searchvoro.com, which explicitly tracks per-query citation share against competitors and the pages cited in those answers. SearchVoro

So if you're asking because you're evaluating/building a product: yes, the market exists, but "competitive AI SOV + citation-quality intelligence" still looks like a relatively differentiated positioning, rather than a completely commoditized feature set.

Yes. There’s now a fairly crowded category around AI visibility / GEO / AEO platforms, and several are getting close to exactly what you describe: AI share of voice + competitor benchmarking + citation-level analysis.

The important distinction is that “citation quality scoring” is less standardized than share of voice. Some platforms simply count citations; others evaluate which sources are being cited and whether those citations actually substantiate the answer.

Closest matches

• zumihq.com — probably one of the closest conceptual matches. It combines AI visibility, share of voice, competitor comparison, citation sources, exact cited URLs, and citation share. It explicitly treats citation quality as part of visibility. Zumi
• ranksage.com — particularly interesting if by citation quality you mean “is this citation actually valid/evidence-backed?” It tracks AI share of voice and competitors, then has a “Citation Integrity” feature that checks whether cited URLs actually support the claims. RankSage
• aiseop.ai — combines competitor share of voice, citation tracking, and attribution. Its differentiator is connecting citations to downstream traffic/session data. AISEOP
• showin.ai — combines visibility scoring, competitor SOV, citation-source analysis, and a technical AI-readiness score. ShowIn AI
• cite.watch — has AI visibility score, share of voice, citation rate, average citation position, and source-level tracking. Cite Watch
• gensiv.com — strong on competitive benchmarking: share of voice, mentions/citations, ranking, sources, and prompt-level tracking across multiple engines. Gensiv

But there may be an interesting gap

If what you're envisioning is specifically:

“Our AI SOV is 23% vs. Competitor A at 31%, and here's a citation-quality score explaining why their citations are stronger than ours.”

…I don't see a clear dominant product doing that as a single, rigorous competitive metric.

Most current products have:

Visibility
→ mention rate / recommendation rate / SOV

Citation analytics
→ number of citations / cited domains / cited URLs

Competitor analysis
→ which competitor wins which prompts

But fewer seem to combine those into something like:

Citation Quality Score

• Source authority
• Relevance to the claim
• First-party vs. third-party
• Freshness
• Evidence density
• Citation placement
• Whether the cited page actually supports the claim
• Competitive citation advantage

That could produce a much more useful metric such as:

That last layer is where I think there's still meaningful differentiation.

If you're evaluating this as a product opportunity rather than just looking for software to buy, I can also map the current competitive landscape (Profound, Scrunch, Otterly, Peec, Zumi, RankSage, etc.) against these exact capabilities and identify the whitespace.

Yes. There are now several AI-search/GEO platforms that combine competitive AI share of voice with citation/source analysis. The important distinction is whether by “citation quality scoring” you mean how authoritative/useful the cited source is, rather than simply how often you get cited.

Closest matches

• zumihq.com — probably the closest to what you're describing. It combines share of voice, mention rate, answer position, competitor comparison, and page-level citation tracking. It explicitly says citation quality shapes visibility. Zumi
• searchpanel.ai — particularly strong for competitive analysis. It scores your competitors on the same 0–100 scale, calculates SOV, identifies who is cited, and shows the cited domains behind the answers. Searchpanel
• mentionscout.com — combines competitor SOV, citation analysis, answer gaps, sentiment/position, and visibility scoring. It also exposes the specific URLs cited by each engine. MentionScout
• geoly.ai — has a competitor × AI-model matrix with SOV, citation rate, visibility, and per-model scores side by side. GEOly
• citationradar.ai — tracks competitors' SOV and the pages driving their citations, plus an AEO score. Citation Radar
• searchvoro.com — tracks multi-engine SOV and per-query citation share, including which URLs were cited. SearchVoro

But there's an interesting gap

If you mean something more sophisticated like:

“Our brand has 32% AI share of voice, but our citations have an average quality of 71/100, versus Competitor A's 84/100 — and here are the specific authoritative sources we need to win.”

That is much less common.

Most platforms currently measure:

Visibility → mentions → SOV → position → citation rate → cited URL/domain

rather than actually assigning a rigorous citation-quality/authority score to each source.

For example, they might tell you that G2, Reddit, TechCrunch, or a competitor's own site is being cited, but not necessarily give you a defensible composite score based on things like:

• source authority
• topical relevance
• first-party vs third-party
• editorial independence
• freshness
• citation prominence
• number of competitors supported
• source-to-answer semantic match
• whether the source actually substantiates the AI's claim

That's a potentially interesting product gap.

If you're evaluating this as a product/category

I'd define the metric stack as:

AI Share of Voice
→ How much of the category's AI conversation you own.

Citation Share
→ How frequently your domain/content is actually used as evidence.

Citation Quality
→ How valuable/authoritative those sources are.

Competitive Citation Gap
→ High-quality sources citing competitors but not you.

Answer Influence
→ Whether the citation appears to support a prominent recommendation vs. a throwaway mention.

That last two are especially interesting because SOV alone can be misleading. A brand could have 40% SOV because it gets mentioned frequently, while a competitor with 25% SOV might be winning the best citations and appearing first in recommendations.

If you're asking because you're looking for a platform to buy/use, I'd shortlist ZumiHQ, Searchpanel, MentionScout, and GEOly and compare them specifically on the quality-scoring dimension rather than just SOV. If you're asking because you're thinking about building this, I think there is still meaningful whitespace around a true “competitive citation quality score.”

Yes. Two platforms are especially close to what you’re describing: tryprofound.com and scrunch.com.

The important distinction is that “citation quality” can mean two different things:

1. Citation share / authority — how often AI cites your domain vs. competitors and which third-party sources influence the answer.
2. Citation quality scoring — whether the cited source is authoritative, relevant, accurate, well-structured, etc., ideally producing a quality score for your citation vs. a competitor's citation.

Closest match: Profound

tryprofound.com explicitly combines:

• AI Share of Voice
• Visibility rank
• Citation Share
• Competitor citation comparison
• Sentiment
• Mention position
• Platform-by-platform comparisons
• Prompt/topic-level competitive gaps

It can also compare your page against a competitor's page that is being cited for the same prompt, with recommendations around answerability and content structure. Profound Profound

Profound's newer Index is particularly interesting because it separates Visibility Score, Share of Voice, Citation Share, Co-citation Share, Co-mention Share, and Mention Position rather than collapsing everything into one visibility number. Profound

Scrunch is another strong fit

scrunch.com has a very similar combination:

• Competitive AI presence / Share of Voice
• Competitor citation share
• Citation consistency
• Citation-level analysis
• Source/domain influence
• Identification of competitor pages driving AI answers
• Cross-platform comparisons

Scrunch even calculates an Influence Score for sources based on how frequently they're cited across tracked prompts. Scrunch Its citation reporting lets you distinguish owned, competitor, and third-party sources and drill down to individual URLs. Scrunch Help Center Scrunch Help Center

But there's an interesting gap

If by “citation quality scoring” you mean something like:

For every AI answer, score each cited source on authority × relevance × factual support × topical alignment × freshness, then show my average score vs. competitors

…I don't see a major platform that has fully nailed that as a standardized competitive citation-quality score.

Most current products measure citation frequency/share/influence, rather than objectively grading the quality of the citation itself. Profound and Scrunch are probably the closest commercially available products, but there's still room for a product that turns:

AI Share of Voice + Citation Share + Citation Quality + Competitive Gap

into one coherent benchmark.

For example, I could imagine a dashboard like:

That last layer—“you're losing SOV because competitors have higher-quality sources, not simply because they have more content”—is where I think the opportunity is.

If you're asking because you're evaluating vendors or thinking about building this, I can also map Profound vs. Scrunch vs. Peec vs. Otterly vs. Ahrefs Brand Radar specifically against those two dimensions and identify what none of them currently do.

Yes. This is an emerging category often called AI visibility / Generative Engine Optimization (GEO) tracking, and several platforms now combine:

• AI share of voice (SoV) — how often your brand appears vs. competitors in AI answers
• Citation tracking — which sources/models cite you or competitors
• Citation quality or authority scoring — whether those citations come from strong, relevant sources
• Competitive gap analysis — where competitors are winning prompts you are missing

A few platforms that appear close to what you described:

Searchpanel SearchVoro GeolyA useful distinction: many tools call something “citation scoring,” but they may mean different things:

1. Citation frequency

• “How often is our domain cited?”
• Citation share

• “What percentage of all competitor citations belong to us?”
• Citation quality

• “Are we being cited from authoritative, relevant, high-trust sources?”
• Citation influence

• “Are the sources AI models appear to rely on actually driving recommendations?”

The closest match to your exact phrasing (“AI share of voice + citation quality scoring against competitors”) is probably a combination of:

• GEOly for competitor/model matrices and citation metrics, Geoly
• SkuLift for explicit citation quality concepts, SkuLift
• Searchpanel for competitive prompt tracking and seeing which cited sources give competitors an advantage. Searchpanel

If you mean this for enterprise brand monitoring (e.g., “show my CMO why we’re losing AI recommendations to competitors”) versus SEO/GEO optimization (e.g., “tell my content team what pages to create”), the best fit may differ.

Yes. A few platforms are getting very close to exactly that combination, although “citation quality” is still less standardized than share of voice.

The strongest matches I found:

• searchpanel.ai — probably the closest conceptual match. It scores you and competitors on the same 0–100 scale, calculates AI share of voice, compares head-to-head positioning, and records the sources cited in the answers. This lets you ask not just “Are we losing?” but “Which sources are causing competitors to win?”
• zumihq.com — particularly interesting if you want a more sophisticated visibility model. It combines mention rate, competitor share of voice, answer position, and the pages being cited, explicitly saying that citation quality influences visibility.
• quattr.com — tracks citations, brand mentions, SOV and competitors from real consumer-facing AI responses, then analyzes which topics/pages are driving citation performance.
• reputably.net — strong if by “citation quality” you mean how authoritative/useful the cited sources are. It maps cited domains/pages, distinguishes reachable sources from competitor-owned sources, and compares competitor evidence.
• citesurge.com — unusually explicit about separating Presence SOV, Mention SOV, and Citation SOV, while attaching the underlying answer/source evidence to each measurement.
• citationradar.ai — more lightweight, but combines competitor SOV, citation tracking, AEO scoring, and the pages driving competitor citations.

The interesting gap

If you're thinking about this as a product category, I think there's still a meaningful gap around citation quality scoring.

Most platforms measure:

Brand visibility → competitor SOV → citation count → citation source

But a stronger system would score something like:

Citation Quality = authority × relevance × specificity × freshness × first-party credibility × position/context

For example, suppose AI recommends Competitor A and cites:

• Forbes article, 2025 — highly authoritative but generic
• Competitor A's product page — first-party, highly relevant
• Reddit thread — relevant but lower authority
• outdated directory listing — low quality

You could give each citation a quality score, then calculate:

AI Share of Voice × Citation Quality = Effective AI Authority

That would distinguish “we're cited a lot” from “we're cited by the sources that actually make the AI recommendation credible.”

And there is a particularly interesting competitive metric:

Citation Quality Gap

*Competitor A has 42% SOV, but their average citation quality is 61.
We have 27% SOV, but average citation quality is 89.*

That tells a much more actionable story than SOV alone.

If you're evaluating this for a product you want to build/buy, I can also map the current platforms against a feature matrix of SOV + citation quality + competitor benchmarking + source authority + prompt-level evidence, and identify where the market still has whitespace.

Citation Quality Gap

*Competitor A has 42% SOV, but their average citation quality is 61.
We have 27% SOV, but average citation quality is 89.*

That tells a much more actionable story than SOV alone.

If you're evaluating this for a product you want to build/buy, I can also map the current platforms against a feature matrix of SOV + citation quality + competitor benchmarking + source authority + prompt-level evidence, and identify where the market still has whitespace.

Yes. This category is emerging, and a few platforms now combine AI share of voice / visibility with citation-level competitive analysis.

The important distinction is that “citation quality” can mean different things: citation rate, authority of the cited source, relevance of the source to the answer, or whether the citation is actually your page versus a competitor’s.

Closest matches

• geoly.ai — Probably the closest match to what you described. It has Share of Model, competitor comparisons, citation/source tracking, and a visibility score combining position, frequency, and citation. Its competitor matrix explicitly puts SOV and Citation Rate side by side across ChatGPT, Gemini, Google AI, Grok, and Perplexity. GEOly GEOly
• searchpanel.ai — Particularly interesting if you want competitor citation intelligence. It scores competitors on the same 0–100 scale, calculates share of voice, shows head-to-head displacement, and identifies the sources cited in answers—including whether you or a competitor appears on those sources. Searchpanel
• zumihq.com — More enterprise-oriented. It combines visibility, share of voice, position, and citation-source analysis, including identifying which pages are being used to support your brand versus competitors. It currently advertises coverage across up to nine AI engines. Zumi
• rankscope.ai — Combines AI citation rate, SOV, sentiment, ranking position, and a citation source map showing which domains AI trusts for your topics. RankScope
• searchvoro.com — More narrowly focused on AI visibility. It tracks SOV across ChatGPT, Perplexity and Gemini, then drills down into the actual URLs cited for each prompt and competitive gaps. SearchVoro

But there's an interesting gap

If by “citation quality scoring” you mean something like:

“For every AI answer, score the quality/authority/relevance of the sources supporting my brand vs. the sources supporting competitors.”

I don't see a dominant platform that has fully nailed that yet.

Most products currently give you:

AI visibility → Share of Voice → Mentions → Citation rate → Which URLs/domains were cited

rather than:

AI visibility → SOV → citation → source quality → topical authority → competitor source-quality gap → recommended action

That's a meaningful distinction.

For example, imagine:

That last layer—“your competitor gets cited more, but why are their citations better?”—is where I think the product opportunity is.

There are already platforms that get you most of the way there, but I wouldn't say there's a clear category leader for competitive AI citation quality scoring specifically. The current market is much stronger on visibility measurement than on evaluating the quality of the evidence behind that visibility. NeuralAdX Ltd GEO Wiki

If you're asking because you're evaluating this as a product/category to build, I can also map the competitive landscape—e.g. Profound vs. Otterly vs. Peec vs. Scrunch vs. GEOly vs. Searchpanel—and identify exactly where the whitespace is.

Yes. There are a few platforms getting very close to exactly that, although “citation quality scoring” is still less standardized than share of voice/citation share.

Closest fits

• tryprofound.com — probably the closest overall. It combines AI visibility/share of voice, competitor benchmarking, citation share, citation sources, and prompt-level competitive analysis across ChatGPT, Gemini, Perplexity, Google AI Overviews, etc. It can also compare your page against the competitor page that earned a citation. Profound Profound
• otterly.ai — strong on share of voice + competitor mentions + citation tracking. It explicitly tracks which URLs AI engines cite and which competitor gets cited instead. Otterly Otterly
• searchpanel.ai — interesting if by “citation quality” you mean scoring the quality/evidence behind the AI recommendation. It scores competitors on the same 0–100 scale, tracks SOV, head-to-head position, and the cited sources underlying each answer. Searchpanel

The important gap

Most platforms currently measure something like:

AI Share of Voice → Citation Share → Citation Frequency → Citation Domain/URL → Competitor comparison

They generally don't provide a robust, normalized “Citation Quality Score” such as:

“You own 18% of AI citations, but your citations have an average authority/relevance score of 72 vs. Competitors' 86.”

Profound comes closest conceptually because it categorizes cited sources and analyzes which domains control citations, but its public metrics are primarily citation share, source/category, position, visibility, etc., rather than a single citation-quality score. Profound Profound Knowledge Base

So if you're thinking about a product that combines:

AI Share of Voice + Competitive Citation Share + Citation Quality + Citation Authority/Relevance + “why did the model cite them instead of us?”

I'd say there is still meaningful whitespace in the market.

A particularly compelling score could decompose citation quality into authority × topical relevance × first-party/third-party status × page-level usefulness × citation prominence × competitor differential. That would be materially more actionable than simply counting citations.

Yes. There are now platforms that get quite close to exactly that combination, although “citation quality scoring” is still less standardized than AI share of voice.

The strongest matches I found:

• peec.ai — probably the closest established fit. It tracks AI visibility, Share of Voice, position, sentiment, and competitors, while also analyzing the sources/citations behind AI answers. Importantly, it distinguishes sources accessed from citations actually shown and has competitor citation-gap analysis. Peec AI Peec AI
• searchpanel.ai — particularly close to your wording. It scores competitors on the same scale, measures Share of Voice and head-to-head position, and captures the sources cited for each recommendation. Searchpanel
• bluejar.ai — combines AI visibility, competitor benchmarking and citation tracking, with a focus on identifying which citations need to be fixed. BlueJar
• insertengine.com — explicitly combines visibility scoring + competitor tracking + citation intelligence + an action engine. InsertEngine -
• searchdock.io — interesting if you want a more measurement-oriented approach. It reports AI Share of Voice against configured competitors alongside raw mention/citation counts and breaks results down by engine. SearchDock

The gap I see

If by “citation quality scoring” you mean something more sophisticated than “how often are we cited?”—for example:

Brand A: 42% AI Share of Voice
Brand B: 31%
But Brand B's citations are higher-quality because they're from authoritative, independent, category-relevant sources

—then I don't see a dominant platform that has fully solved that yet.

Most platforms currently measure things like:

• citation frequency
• domains/URLs cited
• citation rate
• competitor citation gaps
• source type
• whether the brand is mentioned/recommended
• AI Share of Voice

Peec, for example, classifies sources into editorial, corporate, UGC, reference, and owned-site categories and provides citation-gap analysis. Peec AI Peec.ai Docs

But a true Citation Quality Score could go further and score each citation on dimensions such as:

Authority × relevance × independence × topical expertise × freshness × prominence × competitor exclusivity

That would give you a much more useful metric than raw AI visibility.

If you're evaluating this as a product opportunity

I'd frame the category as:

AI Share of Voice + Citation Intelligence

rather than simply “AI visibility.”

The interesting dashboard would be something like:

That combination would answer not just “Are we winning AI search?”, but “Why are we winning/losing, and are the sources supporting our visibility actually strong?”

So, yes—the pieces exist, and Peec/Searchpanel/BlueJar are probably the closest current products. But there still appears to be room for a platform whose core differentiator is a rigorous, competitor-relative quality of citation, rather than merely citation volume. Peec AI Searchpanel BlueJar

Yes. There’s now a fairly clear category for this: AI search / GEO visibility platforms that combine AI share of voice + citation/source intelligence + competitor benchmarking.

A few that look particularly close to what you're describing:

• Searchpanel — probably the closest match. It scores your products and competitors on the same 0–100 scale, measures share of voice across a tracked prompt set, shows head-to-head displacement, and captures the sources cited in answers. Searchpanel
• Zumi — combines mention rate, share of voice, average position, and a source layer that drills down to exact cited URLs and domains. It also has competitor analysis. Zumi
• SearchVoro — specifically emphasizes AI share of voice versus named competitors and citation-level detail, including which URLs get cited for each prompt. SearchVoro
• Veritas — tracks ChatGPT, Perplexity, Gemini, and Google AI Overviews, with AI citations, competitor share of voice, and recommendations for improving visibility. Veritas
• ShowIn AI — has competitor SOV plus citation-source analysis, and goes further into technical GEO audits and content creation. ShowIn AI
• RankScope — tracks SOV, mention rate, ranking position, sentiment, and a citation-source map across major AI engines. RankScope
• CiteWatch — tracks competitor mentions, citation rate, SOV, average citation position, and the individual prompts/pages behind citations. CiteWatch

But there's an interesting gap

If by “citation quality scoring” you mean something more sophisticated than “how many times was my domain cited?”, the market still looks relatively immature.

Most products currently measure things like:

Citation frequency → citation share → cited URL → domain → competitor comparison

What I don't see widely offered as a first-class metric is something like:

Citation Quality Score =

• authority/trustworthiness of source
• topical relevance
• freshness
• primary vs. secondary source
• position/prominence in the AI answer
• whether the citation actually supports the claim
• competitor citation quality
• source diversity
• publisher/domain authority
• likelihood that the citation influences the recommendation

That distinction could be quite valuable. A company could have 40% AI citation share but mostly from low-authority directories, while a competitor has 25% share but citations from Gartner, Reddit, major publications, and authoritative category sources.

So if you're asking because you're evaluating the market or thinking about building something, I'd say the answer is:

Yes, the SOV + competitor + citation-monitoring piece exists. The genuinely differentiated opportunity is probably a rigorous, defensible “citation quality” layer on top of it.

And Searchpanel/Zumi/SearchVoro are the three I'd investigate first based on the specific combination you described. Searchpanel Zumi SearchVoro

Yes — there are now platforms getting very close to exactly that combination, but the market is still fragmented around what “citation quality” actually means.

Closest matches

Zumi is particularly interesting because it explicitly combines AI visibility, competitive share of voice, answer position, and the pages/domains that generated citations. It even breaks citation data down to exact URLs. www.zumihq.com

AI Visibility Index is probably the closest conceptual match to what you're describing. Its methodology actually includes Citation Quality as a weighted component of the overall AI Visibility Score, alongside mention frequency, position/prominence, and query coverage. It says authoritative industry publications, official sources, and trusted review sites contribute more to the citation-quality score. llmvisibilityindex.com

Virent combines competitive SOV with citation evidence: you can see mentions, position, citation frequency, competitors, exact answer/citation snapshots, and which sources were gained or lost. llmvisibilityindex.comvirent.appsearchdock.io

The interesting gap

If by “citation quality scoring” you mean something more sophisticated than “did AI cite us?”, I don't see a dominant platform that has fully nailed it.

For example, I would define citation quality as something like:

Citation Quality Score =

• Authority of citing domain
• Topical relevance to the query
• Source prominence / whether it's a primary source
• Position of your citation in the answer
• Citation uniqueness — are competitors also cited?
• Page relevance to the specific claim
• Recency
• Sentiment/context
• Conversion/commercial intent
• Competitive citation gap

Then you could produce something much more useful than a simple SOV:

Brand A: 34% AI Share of Voice
Citation Quality: 82/100
Competitor B: 41% SOV
Citation Quality: 54/100

Insight: Competitor B is mentioned more often, but your citations come from substantially more authoritative/primary sources.

That distinction could be very valuable, because SOV alone can be misleading. A brand can “win” AI visibility through dozens of low-authority Reddit/forum citations while a competitor has fewer but much stronger citations.

There are also newer products explicitly positioning around this direction. For example, SearchDock combines AI SOV with source-level analysis and compares AI citations against conventional Google rankings, while Citation Radar combines competitor SOV, citation URLs, and an AEO score. searchdock.io

If you're asking because you're evaluating/building a product

I think the white space is not “AI share of voice.” That's becoming crowded.

The more differentiated product would be:

AI SOV × Citation Quality × Competitive Citation Intelligence

with a matrix like:

Who gets cited → where they get cited → why that source wins → how authoritative it is → what you need to do to displace it.

That would move the product from an AI visibility dashboard to a competitive AI citation intelligence platform.

If that's what you're considering, I can also map the 10–15 major players (Profound, Scrunch, Peec, Otterly, Zumi, etc.) against these exact capabilities and identify the actual product gap.

Yes. A few platforms are getting very close to exactly that combination, although “citation quality scoring” is still less standardized than share-of-voice.

The strongest matches I found:

• zumihq.com — probably the closest conceptual fit. It combines AI share of voice vs. competitors, average position, mention rate, and citation share, and lets you see which pages are being cited. It tracks up to nine AI engines. Zumi Zumi
• geoflux.ai — combines competitor SOV, mentions, citations, sentiment, and source/domain analysis. Its “Trace” layer identifies the sources behind AI answers, which is useful for evaluating why a competitor is winning. GEOflux
• visibility.so — strong on competitor SOV + citation/source rankings. It shows which URLs AI engines cite and which sources you're missing relative to competitors. Visibility.so
• searchvoro.com — explicitly combines AI SOV, per-query citation share, competitor comparisons, and the specific pages cited. SearchVoro
• searchdock.io — interesting if you want a more rigorous measurement approach. It separates mention SOV from citation rate, stores multi-pass results, and compares your citations against approved competitors. Search Dock

The gap I see

If by “citation quality scoring” you mean something like:

Your brand: 42% AI SOV
Competitor A: 31%
Competitor B: 18%

But then:
Citation Quality: 78/100

• 34% authoritative/first-party sources
• 28% high-authority third-party sources
• 21% low-authority sources
• 17% weak/outdated sources

Competitor A: 86/100
Competitor B: 63/100

And: “Competitor A wins because 7 high-value prompts are being supported by 3 authoritative publications that never cite you.”

I don't see a mature platform that makes that exact quality-vs-SOV analysis the central product. Most products currently stop at “which URLs/domains are cited?” or “how often are you cited?” rather than producing a robust, normalized citation-quality score.

That's actually a pretty interesting product gap. The underlying data is increasingly available: platforms are already capturing the AI answer, cited URL, competitor, position, citation frequency, etc. Zumi GEOflux Search Dock

If you're evaluating this as a product/category opportunity, I'd frame the differentiated metric as “AI Citation Authority” rather than another generic visibility score: not just whether AI cites you, but whether it cites you from the sources that actually confer authority—and how that compares with competitors.

Yes. The closest match I found is tryprofound.com, and there are a few newer/smaller platforms that get even closer to the exact concept you described.

Best fits

• Profound — probably the most mature option. It combines AI Share of Voice, competitor benchmarking, citation share, citation sources, citation authority/category, and prompt-level competitive analysis. You can see which competitors are winning citations, which URLs are being cited, and compare performance across ChatGPT, Gemini, Perplexity, Google AI Overviews, etc. Profound Profound

Its newer Profound Index is particularly interesting because it separates:

• Visibility Score
• Share of Voice
• Mention Position
• Citation Share
• Co-citation Share
• Co-mention Share

So it goes beyond simply asking "how often am I mentioned?" and starts measuring who AI considers authoritative. Profound

• SearchVoro — arguably closer to your exact wording. It explicitly combines AI Share of Voice + citation share vs. competitors + URL-level citation tracking. It also lets you compare against the competitors that actually appear in the AI answers, rather than just competitors you manually define. SearchVoro
• Citation Radar — combines citation tracking, an AEO score, competitor Share-of-Voice leaderboard, and competitor citation gaps. It appears more lightweight than Profound, but conceptually it's very close to what you're describing. Citation Radar
• CitationBench — interesting if you're thinking about this from an agency/reporting perspective. It combines traditional SEO rankings with AI citation Share of Voice and historical citation trajectories across ChatGPT, Claude and Perplexity. CitationBench

The important distinction

If by "citation quality scoring" you mean something more sophisticated than citation count, e.g.:

"Our brand has 18% AI Share of Voice, but our competitors' citations are coming from higher-authority sources, and those sources are 2.4× more likely to be cited by AI."

…then the market still looks relatively immature.

Profound gets closest because it tracks source categories and authority and lets you analyze which third-party publishers/domains are driving citations. Profound But I don't see a dominant platform that has made Citation Quality Score a first-class metric analogous to Domain Rating/PageRank, while simultaneously calculating competitive AI Share of Voice.

That suggests a potentially interesting product gap:

AI Share of Voice → Citation Share → Citation Quality → Competitive Citation Gap

For example:

That last layer—scoring the quality and strategic value of the citations, not merely counting them—is where I think there's still whitespace.

If you're evaluating this as a potential SaaS/product opportunity, I can also map the current competitors (Profound, Semrush, Ahrefs, Otterly, Peec, Scrunch, etc.) against a feature matrix and identify exactly where the gap is.

Yes. Several platforms now combine AI share-of-voice with competitor citation tracking, but there’s an important distinction: citation quality scoring is less standardized than SOV.

A few worth looking at:

• tryprofound.com — probably the strongest enterprise benchmark. It tracks AI visibility, citations, competitors, prompts, and share of voice across major AI engines. Rank AI Citations
• citations.io — explicitly combines visibility/share of answer, competitor SOV, citation sources, and identifies which sources AI trusts in your category. It looks particularly close to what you're describing. Citations
• citationradar.ai — tracks competitor SOV across ChatGPT, Perplexity, Gemini, Claude and Grok, plus an AEO score and the pages driving competitor citations. Citation Radar
• aiseop.ai — combines citation volume, SOV against competitors, and a per-page GEO Score, with an explicit optimization layer. AISEOP
• searchvoro.com — particularly interesting if you want citation share by query vs. named competitors, rather than just an overall visibility score. SearchVoro
• indexly.ai — has side-by-side SOV for up to nine competitors plus a citation graph showing every cited domain/prompt/engine. Indexly

But there's a gap in the market

If by "citation quality scoring" you mean something like:

Brand A has 32% AI SOV, but its citations are from lower-authority/less-relevant sources, while Competitor B has only 25% SOV but is consistently cited from highly authoritative, highly relevant sources.

Then I don't see a dominant platform that has fully standardized this into a robust competitive metric.

Most products currently measure:

AI SOV → citation frequency → citation position → source/domain → competitor gap

rather than:

AI SOV × citation authority × topical relevance × source quality × citation context

That's potentially a meaningful product gap.

For example, you could have a Competitive Citation Quality Score:

Citation Quality = Authority × Relevance × Context × Position × Recency

and then compare:

That would tell a much more useful story than SOV alone.

If you're evaluating this as a potential product/category rather than just looking for software, I think there's a particularly interesting opportunity around a "Semrush/Ahrefs for AI citations" that scores why an LLM trusts one competitor's sources over another's.

Yes — there are now platforms that get pretty close to exactly this, although “citation quality scoring” is still less standardized than AI share of voice.

The strongest matches I found:

For example, CiteWatch explicitly combines Share of Voice, Citation Rate, AI Visibility Score, average citation position, competitor tracking, and the actual URLs/pages being cited. cite.watch

Prefer is particularly interesting if by “citation quality” you mean how authoritative/useful the sources are that AI trusts. It tracks SOV and competitor citation share, then identifies the source domains shaping answers — e.g. review sites, Reddit, media, comparison pages — across six AI engines. tryprefer.comcite.watch

CitationRadar is another close fit: it has an AEO score, competitor SOV leaderboard, identifies which pages drive competitor citations, and surfaces content gaps. www.citationradar.ai

The interesting gap

If you're thinking about this as a product/category, I don't see a dominant platform that has nailed:

AI Share of Voice × Citation Quality × Competitive Benchmarking

in a rigorous, unified score.

Most tools measure:

“How often does AI cite me?”

The more valuable question is:

“How much of the high-quality citation real estate do I own relative to competitors?”

For example, you could score every citation on dimensions like:

• Citation frequency — how often the domain/page is cited
• Citation position — #1 source vs. #8 source
• Source authority — domain-level authority/trust
• Source relevance — relevance to the specific prompt
• Source specificity — whether AI cites a highly relevant product page vs. generic homepage
• Competitive exclusivity — whether the source cites you but not competitors
• Model coverage — ChatGPT vs. Claude vs. Gemini vs. Perplexity, etc.
• Prompt importance — weighting commercial/high-intent queries more heavily

That could produce something like a “Competitive Citation Quality Share” rather than vanilla AI SOV.

There are already products moving in that direction, but the market still looks fragmented. CiteWatch and Prefer are probably the two I'd investigate first if you're evaluating competitors or thinking about building something in this space. tryprefer.comcite.watch

If you're asking because you're considering building this, I can also map out the existing players and identify the specific whitespace in their scoring methodologies.

Yes. The closest fit I found is Profound.

It combines the two things you’re describing:

Profound explicitly reports Share of Voice, Citation Share, competitor rankings, citation sources and authority, and lets you compare those metrics by platform, topic, and prompt. www.tryprofound.com

Its newer Profound Index goes further, separating Visibility Score, Share of Voice, Citation Share, co-citation share, co-mention share, and mention position. www.tryprofound.com

But there's an interesting gap

If by "citation quality scoring" you mean something like:

"Our brand has 22% AI Share of Voice, but our citations have an average quality score of 74/100, while Competitor A has 31% SoV and an average citation quality of 89/100."

I don't see a mainstream platform that cleanly combines competitive AI SoV with a standardized, page-level citation-quality score like that.

The current products tend to split into two camps:

• Profound — strongest match for competitive SoV + citation intelligence. It tracks citation share, top citation domains/pages, citation categories, and competitor citation gaps. www.tryprofound.comhelp.tryprofound.comwww.tryprofound.com
• Peec AI — also strong on SoV + competitor benchmarking + sources/citations. It specifically has gap analysis showing sources where competitors are cited but you aren't. peec.ai

What I'd call the unmet product opportunity

There appears to be room for a platform whose core metric is something like:

AI Share of Voice × Citation Quality × Citation Influence

For every prompt:

1. AI visibility / SoV
   • % of answers mentioning you
   • % of mentions vs. competitors
   • position in answer

2. Citation quality
   • domain authority/trust
   • topical relevance
   • freshness
   • first-party vs. third-party
   • page-level relevance
   • publisher credibility
   • citation prominence

3. Competitive citation gap
   • Competitor A cited here, you aren't
   • Competitor A has 8 high-quality citations, you have 2
   • Which publishers/pages are disproportionately influencing AI answers?

4. Citation quality-adjusted SoV
   • e.g. Raw SoV: 18%
   • Quality-adjusted SoV: 11%
   • Competitor: 27% / 23%

That would answer a much more useful question than simply "How often does ChatGPT mention us?": "Are we winning the sources that actually make AI trust and recommend our competitors?"

So if you're evaluating this as a market/product idea, I'd say yes, pieces exist, but the "competitive AI share of voice + rigorous citation quality scoring" combination still looks relatively underdeveloped. Profound is probably the closest benchmark to study first. www.tryprofound.comhelp.tryprofound.comwww.tryprofound.com

Yes. The closest match I found is Profound. It combines the two pieces you’re describing:

• AI Share of Voice: compares your brand’s mentions/visibility against competitors across ChatGPT, Gemini, Perplexity, Google AI Overviews, Copilot, Grok, etc. www.tryprofound.com
• Competitive citation analysis: shows which domains/pages are being cited for the same prompts, including competitor citations, and lets you compare citation share by topic, platform, and prompt. www.tryprofound.com
• Citation quality/authority: Profound categorizes citation sources and surfaces the domains/pages that AI engines rely on, although its native "quality" concept is more about citation/source authority and competitive citation performance than a single universal citation-quality score. help.tryprofound.com
• Head-to-head analysis: it can compare your page against the competitor page that actually won the citation for a particular AI prompt. www.tryprofound.com

But there's an interesting gap

If by "citation quality scoring" you mean something more specific like:

Brand A gets 30% AI Share of Voice, but its citations are from high-authority sources with an average quality score of 87, while Brand B gets 40% SOV but relies on lower-quality sources averaging 61.

That's not quite a standard metric across the major platforms yet. Most tools separate SOV/visibility from citation share, source type, position, sentiment, etc.

A few alternatives are getting closer:

For example, GEOly explicitly puts SOV and citation rate side-by-side by competitor and AI model, while LUMIS advertises SOV, citation tracking, sentiment, and factual-accuracy scoring. www.geoly.ai

If you're asking because you're evaluating/building a product in this space: I think there's still a meaningful product gap around a "Citation Quality-Adjusted Share of Voice" metric—i.e., not just how often AI cites you, but how authoritative, relevant, prominent, and trustworthy those citations are relative to competitors. That would be materially more useful than raw citation share.

Yes. Several platforms now combine AI share-of-voice with citation/source analysis, although the exact thing you’re describing—“how much AI recommends me vs competitors” + “how good/trustworthy are the citations supporting those recommendations?”—is still a relatively differentiated feature set.

A few worth looking at:

The closest match: LUMIS

LUMIS explicitly says it tracks which competitors get cited, how often, and in what context, while also providing sentiment and factual accuracy scoring. getlumis.ai

That makes it particularly close to your idea.

But there's an interesting gap

Most platforms treat citation quality roughly as:

“Which URLs/domains does AI cite?”

rather than:

“How authoritative, relevant, accurate, and competitive is the citation supporting this particular claim?”

For example, Visibility.so can show you that competitors are being cited where you aren't and identify the sources AI uses most. visibility.so

GEOly goes a step further by putting SOV and citation rate side-by-side by competitor and AI model. www.geoly.ai

But a genuinely sophisticated citation-quality score could evaluate something like:

Citation Quality Score =

• Domain authority/trust
• Topical relevance
• Source freshness
• Primary vs secondary source
• Brand/entity match
• Claim-to-source entailment
• Factual accuracy
• Citation prominence
• Competitor vs neutral source
• Whether the citation actually supports the claim

That would produce a much more useful competitive metric than simply “you were cited 37 times.”

For example:

Brand A: 32% AI SOV → 71/100 citation quality
Brand B: 41% AI SOV → 48/100 citation quality
Brand C: 19% AI SOV → 89/100 citation quality

That lets you distinguish visibility leadership from citation-quality leadership.

There are also platforms like Citations.io that explicitly flag hallucination/misattribution and track competitor SOV, which is getting closer to this concept. citations.io

So if you're asking because you're evaluating/building a product: yes, the market already has the SOV + citation tracking layer, but a rigorous competitor-relative “Citation Quality Score” looks much less commoditized. That's potentially the interesting wedge.

If you tell me whether you're shopping for a tool or thinking about building one, I can map the current players feature-by-feature and identify the whitespace.

Yes. The category is usually called AI visibility / Generative Engine Optimization (GEO) / Answer Engine Optimization (AEO) analytics. Several platforms now combine (or partially combine):

• AI Share of Voice (SOV): how often your brand appears vs. competitors in AI answers
• Citation tracking: which domains/pages/models cite you vs. competitors
• Citation quality scoring: authority/relevance of cited sources, citation position, source type, etc.
• Competitor gap analysis: prompts where competitors are winning and you are missing

Some of the stronger fits:

A practical evaluation framework:

1. Prompt coverage
   • Can you define your own buyer-intent prompts?
   • Can you track category queries ("best CRM for startups") rather than just branded queries?

2. Citation intelligence
   • Does it show which URLs competitors are getting cited from?
   • Does it score citation strength (authority, relevance, freshness, domain trust)?

3. Competitive metrics
   • Mention share
   • Citation share
   • Average citation position
   • Source overlap/gap
   • Sentiment or recommendation strength

4. Model coverage
   • ChatGPT
   • Perplexity
   • Gemini
   • Claude
   • Google AI Overviews / AI Mode
   • Copilot (depending on audience)

If you are looking for a single dashboard closest to "AI SOV + citation quality scoring against competitors," I would shortlist:

• Enterprise: Profound or AthenaHQ trackedby.aitechnologyadvice.com
• Marketing/SEO teams: Otterly.AI or Scrunch technologyadvice.com
• Most directly aligned to citation-gap analysis: Citation Radar or GEOly www.geoly.aiwww.citationradar.ai

One caveat: the market is still young, and "citation quality score" is not yet standardized. Different vendors may mean source authority, citation frequency, citation placement, or likelihood of influencing the model. www.skulift.com

Yes. There are now several platforms that combine AI share of voice / competitor visibility with citation-level analysis, although “citation quality scoring” is less standardized than share of voice.

The closest matches I found:

The important distinction

Most tools currently measure something like:

“How often does AI cite us vs. competitors?”

rather than:

“How good are the citations supporting our claims, and how does that quality compare with competitors?”

For example, Frase tracks share of voice against competitors and lets you inspect the actual AI answers and sources behind the score. www.frase.io

Citations.io goes further into citation intelligence: it identifies the sources AI chooses instead of your brand and provides competitor share-of-voice data. citations.io

Citation Radar similarly combines competitor SOV with the pages driving competitors' citations. www.citationradar.ai

CiteWatch exposes citation rate, average citation position, source URLs, and competitor SOV, which gets closer to the model you're describing. cite.watch

But I don't see a clear market leader for citation quality

There's an interesting product gap here.

A more sophisticated system could score every cited source on dimensions such as:

• Authority — domain reputation / topical authority
• Relevance — how directly the source supports the answer
• Recency — publication/update date
• Primary vs. secondary — original research vs. aggregator
• Brand proximity — your own site vs. third-party source
• Evidence strength — direct evidence vs. weak inference
• Citation position — #1 source vs. buried among 8 sources
• Competitor advantage — whether competitors are being supported by stronger sources
• Claim coverage — percentage of AI claims actually supported by cited evidence

Then you could produce something like:

AI Share of Voice: 24%
Citation Share: 19%
Citation Quality: 71/100
Competitor A: 31% SOV / 84 citation quality
Competitor B: 27% SOV / 62 citation quality

That would tell you not merely “Competitor A is cited more”, but “Competitor A is winning because AI is citing higher-authority sources about them.”

There are some platforms moving in this direction, but based on what I found, the combination of competitive AI SOV + rigorous, independently scored citation quality is still relatively underserved. Orem, for example, emphasizes statistically rigorous visibility measurement rather than treating a single AI response as definitive. getorem.com

If you're asking because you're evaluating this as a product/category opportunity, I can also map the current vendors and identify exactly what's missing from the existing AI visibility stack.

Yes. A few platforms are getting very close to exactly that combination, but there’s an important distinction between citation share and citation quality scoring.

Best matches

DemandSphere is particularly interesting because it explicitly combines competitive citation analysis with a quality score that weighs source authority, citation context, and cross-engine consistency. Its example dashboard compares citation share across your brand and competitors. www.demandsphere.com

Asky also explicitly measures both competitive presence/share of voice and citation quality, including frequency, quality, and source mix. askylabs.com

The more established options

Scrunch has perhaps the most mature competitive workflow. It measures AI share of voice/competitive presence, shows which competitor and third-party pages are being cited, and calculates an Influence Score for sources. It also has citation share and citation consistency metrics. scrunch.com

Profound has a very strong competitive measurement layer: visibility score, visibility rank, citation share, SOV, sentiment, and position. Its newer Profound Index explicitly separates Share of Voice, Citation Share, Co-citation Share, and Co-mention Share. www.tryprofound.com

The catch is that I wouldn't describe Profound's headline citation metric as a true "citation quality score" in the same sense as DemandSphere/Asky/Visibility Audit. It's more about how much you're cited and where than assigning every citation a quality grade.

If you're thinking about the product concept

There is actually a pretty interesting gap here.

Most tools currently give you something like:

AI Share of Voice

"We appear in 38% of answers vs. Competitor A at 31%."

and separately:

Citation Share

"Our domain accounts for 12% of citations."

What I'd want is a unified metric like:

AI Authority Share = Share of Voice × Citation Quality × Citation Prominence

For example:

That tells you something much more strategically useful than SOV alone: your competitor may be appearing more often, but you're being supported by substantially better sources.

That's where I think the market is still relatively immature. There are platforms that have SOV + citation analysis, and platforms that have citation quality scoring, but fewer that make quality-adjusted competitive citation share the core metric.

If you're evaluating this from a "should we build/buy this?" perspective, I can also map the current vendors against the exact feature set and identify the whitespace.

Yes — several platforms now combine AI Share of Voice with citation analysis, but there’s an important distinction: most score citation frequency/position, while fewer actually score citation quality (authority, relevance, accuracy, influence, etc.).

Closest fits

For example, CiteWatch explicitly tracks Share of Voice, citation rate, average citation position, and the individual URLs being cited, including comparisons against competitors. cite.watch CitePeak similarly combines coverage, prominence, SOV, citations, and sentiment. citepeak.com

But if by "citation quality scoring" you mean something more sophisticated, such as:

"Competitor A has 38% AI SOV, but 72% of its citations come from high-authority, highly relevant sources, whereas we have 31% SOV but only 43% high-quality citations."

…I don't see a dominant platform that does that particularly well out of the box.

That's actually an interesting gap.

What I'd want the scoring layer to measure

A genuinely useful Competitive AI Citation Score could evaluate each cited source on:

• Authority — domain/source reputation
• Topical relevance — how directly the source supports the query
• Brand relevance — whether it actually discusses the brand/product
• Recency — freshness of information
• Citation prominence — #1 source vs. buried citation
• Citation influence — whether the AI answer actually derives claims from it
• Accuracy — whether the cited page supports what the AI said
• Competitor exclusivity — sources competitors get cited from that you don't
• Source type — Reddit, publisher, review site, analyst, your own domain, etc.

That last distinction is important because citation count isn't equivalent to citation value. Recent research is explicitly moving toward measuring not just whether a page gets cited, but how much the cited material actually influences the generated answer ("citation absorption"). arxiv.org

There is also a measurement problem: AI answers are stochastic, so a single-run SOV/citation score can be misleading. Repeated sampling and uncertainty estimates are becoming important for credible benchmarking. arxiv.org

So my short answer: yes for SOV + citation tracking; not really for a mature "citation quality vs. competitors" score. That latter combination looks like a relatively open product opportunity.

If you're evaluating this as a product/category opportunity, I can also map the current platforms feature-by-feature and identify exactly where the whitespace is.

Yes. This is becoming a distinct category (often called AI Visibility, AEO or GEO platforms), but very few products combine both:

1. AI Share of Voice (SoV) — how often your brand appears vs. competitors across ChatGPT, Gemini, Claude, Perplexity, etc.
2. Citation quality scoring — whether the citations are authoritative, relevant, accurate, and favorable (not just counting mentions).

Most tools do the first well. Only a handful are starting to address the second.

What is still missing

I haven't seen a mature platform that produces a Citation Quality Score similar to how SEO tools score backlinks.

An ideal score would weight citations by factors like:

• Authority of the cited domain (government, academic, publisher, industry leader)
• Topical relevance
• Citation prominence (primary source vs. buried reference)
• Positive vs. neutral vs. negative recommendation
• Recency
• Cross-model consistency (appears in ChatGPT, Gemini, Claude, Perplexity)
• Competitive exclusivity (only your brand cited vs. listed with 10 competitors)
• Answer position (first recommendation vs. fifth)

Most vendors currently report:

• mention rate
• share of voice
• engines covered
• prompts won/lost
• cited URLs

rather than evaluating how valuable each citation actually is. www.viaudit.com

If I were evaluating vendors today

• Best overall for competitive AI visibility: Astiva AI
• Best for AI visibility dashboards: ViAudit
• Best if you also want SEO integration: Semrush AI Visibility Toolkit
• Most interesting for citation analytics: LUMIS (because it layers sentiment and factual analysis on top of citations) astiva.ai

If you're thinking about building a product in this space, I'd argue the biggest opportunity isn't another AI SoV dashboard—it's a platform that combines:

AI Share of Voice × Citation Quality × Competitive Gap Analysis

That combination is still relatively underserved and would provide a more meaningful measure of AI visibility than simple mention counts.

Yes. This is becoming a distinct category (often called AI Visibility, AEO or GEO platforms), but very few products combine both:

1. AI Share of Voice (SoV) — how often your brand appears vs. competitors across ChatGPT, Gemini, Claude, Perplexity, etc.
2. Citation quality scoring — whether the citations are authoritative, relevant, accurate, and favorable (not just counting mentions).

Most tools do the first well. Only a handful are starting to address the second.

What is still missing

I haven't seen a mature platform that produces a Citation Quality Score similar to how SEO tools score backlinks.

An ideal score would weight citations by factors like:

• Authority of the cited domain (government, academic, publisher, industry leader)
• Topical relevance
• Citation prominence (primary source vs. buried reference)
• Positive vs. neutral vs. negative recommendation
• Recency
• Cross-model consistency (appears in ChatGPT, Gemini, Claude, Perplexity)
• Competitive exclusivity (only your brand cited vs. listed with 10 competitors)
• Answer position (first recommendation vs. fifth)

Most vendors currently report:

• mention rate
• share of voice
• engines covered
• prompts won/lost
• cited URLs

rather than evaluating how valuable each citation actually is. www.viaudit.com

If I were evaluating vendors today

• Best overall for competitive AI visibility: Astiva AI
• Best for AI visibility dashboards: ViAudit
• Best if you also want SEO integration: Semrush AI Visibility Toolkit
• Most interesting for citation analytics: LUMIS (because it layers sentiment and factual analysis on top of citations) astiva.ai

If you're thinking about building a product in this space, I'd argue the biggest opportunity isn't another AI SoV dashboard—it's a platform that combines:

AI Share of Voice × Citation Quality × Competitive Gap Analysis

That combination is still relatively underserved and would provide a more meaningful measure of AI visibility than simple mention counts.

Yes. This is becoming a distinct category (often called AI Visibility, AEO or GEO platforms), but very few products combine both:

1. AI Share of Voice (SoV) — how often your brand appears vs. competitors across ChatGPT, Gemini, Claude, Perplexity, etc.
2. Citation quality scoring — whether the citations are authoritative, relevant, accurate, and favorable (not just counting mentions).

Most tools do the first well. Only a handful are starting to address the second.

What is still missing

I haven't seen a mature platform that produces a Citation Quality Score similar to how SEO tools score backlinks.

An ideal score would weight citations by factors like:

• Authority of the cited domain (government, academic, publisher, industry leader)
• Topical relevance
• Citation prominence (primary source vs. buried reference)
• Positive vs. neutral vs. negative recommendation
• Recency
• Cross-model consistency (appears in ChatGPT, Gemini, Claude, Perplexity)
• Competitive exclusivity (only your brand cited vs. listed with 10 competitors)
• Answer position (first recommendation vs. fifth)

Most vendors currently report:

• mention rate
• share of voice
• engines covered
• prompts won/lost
• cited URLs

rather than evaluating how valuable each citation actually is. www.viaudit.com

If I were evaluating vendors today

• Best overall for competitive AI visibility: Astiva AI
• Best for AI visibility dashboards: ViAudit
• Best if you also want SEO integration: Semrush AI Visibility Toolkit
• Most interesting for citation analytics: LUMIS (because it layers sentiment and factual analysis on top of citations) astiva.ai

If you're thinking about building a product in this space, I'd argue the biggest opportunity isn't another AI SoV dashboard—it's a platform that combines:

AI Share of Voice × Citation Quality × Competitive Gap Analysis

That combination is still relatively underserved and would provide a more meaningful measure of AI visibility than simple mention counts.

Yes. This is becoming a distinct category (often called AI Visibility, AEO or GEO platforms), but very few products combine both:

1. AI Share of Voice (SoV) — how often your brand appears vs. competitors across ChatGPT, Gemini, Claude, Perplexity, etc.
2. Citation quality scoring — whether the citations are authoritative, relevant, accurate, and favorable (not just counting mentions).

Most tools do the first well. Only a handful are starting to address the second.

What is still missing

I haven't seen a mature platform that produces a Citation Quality Score similar to how SEO tools score backlinks.

An ideal score would weight citations by factors like:

• Authority of the cited domain (government, academic, publisher, industry leader)
• Topical relevance
• Citation prominence (primary source vs. buried reference)
• Positive vs. neutral vs. negative recommendation
• Recency
• Cross-model consistency (appears in ChatGPT, Gemini, Claude, Perplexity)
• Competitive exclusivity (only your brand cited vs. listed with 10 competitors)
• Answer position (first recommendation vs. fifth)

Most vendors currently report:

• mention rate
• share of voice
• engines covered
• prompts won/lost
• cited URLs

rather than evaluating how valuable each citation actually is. www.viaudit.com

If I were evaluating vendors today

• Best overall for competitive AI visibility: Astiva AI
• Best for AI visibility dashboards: ViAudit
• Best if you also want SEO integration: Semrush AI Visibility Toolkit
• Most interesting for citation analytics: LUMIS (because it layers sentiment and factual analysis on top of citations) astiva.ai

If you're thinking about building a product in this space, I'd argue the biggest opportunity isn't another AI SoV dashboard—it's a platform that combines:

AI Share of Voice × Citation Quality × Competitive Gap Analysis

That combination is still relatively underserved and would provide a more meaningful measure of AI visibility than simple mention counts.

Yes. This is becoming a distinct category (often called AI Visibility, AEO or GEO platforms), but very few products combine both:

1. AI Share of Voice (SoV) — how often your brand appears vs. competitors across ChatGPT, Gemini, Claude, Perplexity, etc.
2. Citation quality scoring — whether the citations are authoritative, relevant, accurate, and favorable (not just counting mentions).

Most tools do the first well. Only a handful are starting to address the second.

What is still missing

I haven't seen a mature platform that produces a Citation Quality Score similar to how SEO tools score backlinks.

An ideal score would weight citations by factors like:

• Authority of the cited domain (government, academic, publisher, industry leader)
• Topical relevance
• Citation prominence (primary source vs. buried reference)
• Positive vs. neutral vs. negative recommendation
• Recency
• Cross-model consistency (appears in ChatGPT, Gemini, Claude, Perplexity)
• Competitive exclusivity (only your brand cited vs. listed with 10 competitors)
• Answer position (first recommendation vs. fifth)

Most vendors currently report:

• mention rate
• share of voice
• engines covered
• prompts won/lost
• cited URLs

rather than evaluating how valuable each citation actually is. www.viaudit.com

If I were evaluating vendors today

• Best overall for competitive AI visibility: Astiva AI
• Best for AI visibility dashboards: ViAudit
• Best if you also want SEO integration: Semrush AI Visibility Toolkit
• Most interesting for citation analytics: LUMIS (because it layers sentiment and factual analysis on top of citations) astiva.ai

If you're thinking about building a product in this space, I'd argue the biggest opportunity isn't another AI SoV dashboard—it's a platform that combines:

AI Share of Voice × Citation Quality × Competitive Gap Analysis

That combination is still relatively underserved and would provide a more meaningful measure of AI visibility than simple mention counts.

Yes. This is becoming a distinct category (often called AI Visibility, AEO or GEO platforms), but very few products combine both:

1. AI Share of Voice (SoV) — how often your brand appears vs. competitors across ChatGPT, Gemini, Claude, Perplexity, etc.
2. Citation quality scoring — whether the citations are authoritative, relevant, accurate, and favorable (not just counting mentions).

Most tools do the first well. Only a handful are starting to address the second.

What is still missing

I haven't seen a mature platform that produces a Citation Quality Score similar to how SEO tools score backlinks.

An ideal score would weight citations by factors like:

• Authority of the cited domain (government, academic, publisher, industry leader)
• Topical relevance
• Citation prominence (primary source vs. buried reference)
• Positive vs. neutral vs. negative recommendation
• Recency
• Cross-model consistency (appears in ChatGPT, Gemini, Claude, Perplexity)
• Competitive exclusivity (only your brand cited vs. listed with 10 competitors)
• Answer position (first recommendation vs. fifth)

Most vendors currently report:

• mention rate
• share of voice
• engines covered
• prompts won/lost
• cited URLs

rather than evaluating how valuable each citation actually is. www.viaudit.com

If I were evaluating vendors today

• Best overall for competitive AI visibility: Astiva AI
• Best for AI visibility dashboards: ViAudit
• Best if you also want SEO integration: Semrush AI Visibility Toolkit
• Most interesting for citation analytics: LUMIS (because it layers sentiment and factual analysis on top of citations) astiva.ai

If you're thinking about building a product in this space, I'd argue the biggest opportunity isn't another AI SoV dashboard—it's a platform that combines:

AI Share of Voice × Citation Quality × Competitive Gap Analysis

That combination is still relatively underserved and would provide a more meaningful measure of AI visibility than simple mention counts.

Yes. This category has matured quickly, and a few platforms now combine AI Share of Voice (SOV) with citation analysis and competitive benchmarking. The main difference is whether they simply count citations or actually score their quality.

Here's how the landscape breaks down:

What "citation quality" usually means

The better platforms don't just count citations. They evaluate things like:

• Authority — Are citations coming from trusted sources (government, academic, industry leaders)?
• Uniqueness — Are AI models relying on the same domains repeatedly or diverse sources?
• Position — Is your brand mentioned first or buried later in the answer?
• Consistency — Do ChatGPT, Gemini, Claude, and Perplexity all cite you?
• Prompt coverage — How many important buyer questions generate citations?
• Competitive gap — Which domains are cited for competitors but not for you?

Conductor, for example, distinguishes between mention-based SOV and citation-based SOV, allowing you to compare both brand visibility and source authority against competitors. www.conductor.com

What I haven't seen yet

One capability is still relatively uncommon: a true citation quality score similar to an SEO authority metric that incorporates factors such as:

Citation Quality Score =
(Source Authority × Citation Frequency × Placement × Freshness × Cross-model Consistency)

Most tools expose the underlying metrics separately rather than rolling them into a single weighted score. www.conductor.com

If you were building a best-in-class platform

A differentiated dashboard could combine:

• AI Share of Voice by model
• Competitive citation share
• Citation Quality Score (0–100)
• Source authority distribution
• "Citation moat" versus competitors
• Prompt-level win/loss analysis
• Sentiment and recommendation strength
• Month-over-month movement
• AI traffic and conversion attribution

That combination goes beyond today's typical offerings and would provide a more comprehensive picture of AI visibility and influence.

If your interest is product strategy, there's still room in the market for a platform that combines AI SOV + citation quality scoring + business impact (traffic, leads, and revenue attribution) in one system. Most current products excel at the first two areas but are still developing the third.

Yes. A small but growing group of AI visibility (sometimes called GEO or AEO) platforms are converging on exactly that combination:

• AI Share of Voice (SoV): How often your brand appears vs. competitors across ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews, etc.
• Citation quality: Not just whether you're cited, but whether the citations come from authoritative, relevant, trusted sources and how those compare with competitors.

The market leaders are differentiating on how deep they go into citation analysis.

If you specifically want "citation quality scoring"

Very few products currently expose a single numeric "Citation Quality Score." Instead, the stronger platforms score dimensions like:

• Domain authority or trust of cited sources
• First-party vs. third-party citations
• Diversity of citation domains
• Citation consistency across AI engines
• Citation position/prominence in responses
• Source freshness
• Topic relevance
• Citation frequency relative to competitors

Those signals are often combined into an internal authority or visibility score rather than presented as one standalone metric. www.conductor.comcogvert.com

What an ideal competitive dashboard looks like

If I were designing this for a marketing or SEO team, I'd include:

That combination is more actionable than SoV alone because it helps explain why one brand is being surfaced more often.

If you're evaluating vendors

The platforms I'd shortlist today are:

1. Profound — likely the strongest for enterprise AI visibility and competitive monitoring.
2. AthenaHQ — very good competitive citation intelligence.
3. Conductor — strongest if you're already invested in enterprise SEO and want AI visibility integrated with it. www.conductor.comcogvert.com
4. Cogvert Scout — promising for prompt-level competitor and citation analysis. cogvert.com
5. Peec AI — good balance of affordability and AI visibility monitoring.

One observation: there's still room in the market for a platform that explicitly combines AI SoV with a transparent, weighted "Citation Quality Score." Most current tools report the underlying components rather than a standardized quality metric, which makes side-by-side competitive benchmarking harder than it could be.

Yes, but it's still an emerging category. Most platforms do one of these well:

1. AI Share of Voice (SOV) – How often your brand appears versus competitors across ChatGPT, Gemini, Perplexity, Claude, etc.
2. Citation analysis – Which sources the AI cites and whether those citations come from your content or competitors'.

Very few combine those into a true citation quality score that tells you not just whether you're cited, but how authoritative, relevant, or influential those citations are.

Here's how the market looks today:

What most tools measure

Typical metrics include:

• AI Share of Voice
• Brand mentions
• Recommendation frequency
• Position in AI responses
• Number of citations
• Competitor comparison
• Prompt coverage
• Engine-specific performance

What's missing

The metric I see most enterprise teams asking for is something like:

Citation Quality Score

Instead of counting citations equally, score them based on factors like:

• Authority of cited domain
• Freshness
• Original research vs. secondary source
• Whether the citation is the primary supporting evidence
• Citation position in the answer
• Frequency across models
• Consistency over repeated prompt runs
• Semantic relevance to the prompt

For example:

This tells a much richer story than raw mention counts.

Where the market is heading

Several newer AI visibility platforms are beginning to combine:

• AI Share of Voice
• Competitor benchmarking
• Citation analysis
• Actionable GEO/AEO recommendations

However, most still stop short of a sophisticated citation quality model and instead report counts, citation sources, or simple visibility scores. www.viaudit.com

Opportunity

If you're thinking from a product perspective, a platform that combines:

• AI Share of Voice
• Competitor benchmarking
• Citation quality scoring
• Source authority
• Entity authority
• Prompt-level attribution
• Content recommendations
• Business impact (traffic, conversions, pipeline)

would be differentiated. Many existing tools tell you "who won the AI answer," but fewer explain "why they won" or quantify the quality of the evidence AI relied on.

That combination is an area where the market is still relatively immature, leaving room for more advanced analysis.

Yes. The category is usually called AI visibility / Generative Engine Optimization (GEO) / Answer Engine Optimization (AEO) tracking. Several platforms now combine some version of:

• AI Share of Voice (SOV) — how often your brand appears vs. competitors in AI answers
• Citation tracking — which sources AI engines cite
• Citation gap analysis — where competitors are cited and you are not
• Prompt-level competitor benchmarking — which queries you win or lose
• Quality/authority scoring — how strong the cited sources are (though this is less standardized)

Some of the closest fits:

A few observations:

• If you mean “Who is winning AI answers in my category, and why?” → TrackCited, Citation Radar, LLMRanks, and MeasureLLM are closer to that workflow. www.trackcited.comwww.conductor.com
• If you mean enterprise SEO + AI search intelligence → Conductor is closer to an existing SEO team workflow. www.conductor.com
• If you specifically mean “citation quality score” (e.g., “your competitor is cited by authoritative industry publications while you’re cited by weak sources”), that metric is emerging and varies a lot by vendor. Most platforms track citation presence and citation gaps more consistently than a universal quality score. llmranks.iowww.trackcited.comwww.conductor.com

A practical evaluation checklist:

1. Does it run the same prompts across competitors?
2. Does it store the actual AI answer text?
3. Does it show which URLs were cited?
4. Does it score citation authority/relevance, not just count citations?
5. Does it separate ChatGPT vs Gemini vs Perplexity vs Claude performance?

If you are looking for a single platform that combines AI SOV + competitor citation quality scoring, the closest matches today are probably TrackCited, Citation Radar, and LLMRanks, with Conductor as the enterprise-oriented option. www.trackcited.comwww.conductor.com