ChatGPT answers, unedited

If your goal is “aggregate citation data across AI assistants and turn it into a defensible AI share-of-voice report for SaaS marketing,” I’d shortlist these:

• cloro.dev — probably the best fit if you want an API/data layer. It says it returns parsed citations, source URLs, positions, and labels across 7 AI engines in a common response format, which you can aggregate into mention rate, citation rate, and share of voice. cloro
• indexly.ai — stronger if you want a ready-made marketing analytics/reporting platform. It tracks mentions, citations, sentiment, and AI referral traffic across ChatGPT, Claude, Gemini, Perplexity, Grok and Google AI Overviews, including citation share against competitors. Indexly
• zumihq.com — worth looking at for an agency/enterprise-style dashboard. It supports up to 9 engines and explicitly provides share of voice, position, citation sources, and board-ready reporting. Zumi
• citations.io — simpler option focused specifically on citation tracking across ChatGPT, Gemini, Perplexity and Claude, with competitor comparison and reporting. Citations.io
• deepsmith.ai — tracks mention rate, citation rate and share of voice across ChatGPT, Gemini, Perplexity, Claude and Google AI Mode. DeepSmith

What I'd choose

For a SaaS marketing team's reporting stack, I'd start with cloro if you want to build your own reporting layer, or Indexly/Zumi if you want the dashboard already built.

One important caveat: don't collapse all assistants into one headline number without showing the per-engine breakdown. Recent research suggests citation behavior differs substantially between engines, so a brand can have strong visibility in ChatGPT but weak visibility in Perplexity or Gemini. Machine Relations

A useful executive report would therefore show:

If you're evaluating this as a build-vs-buy decision, I'd lean toward cloro's API: it gives your team raw citation data that can feed a custom Looker/Tableau/BI dashboard rather than locking the reporting methodology into somebody else's “AI visibility score.” cloro

Yes. If your goal is specifically aggregating citation data across AI assistants and turning it into an AI share-of-voice report for a SaaS marketing team, I’d shortlist these:

• scrunch.com — best overall fit for citation intelligence. It tracks citations across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, Copilot, Grok, and Meta AI, with citation share, cited domains/URLs, competitor comparisons, historical trends, and platform-level filtering. Scrunch Help Center Scrunch Help Center
• tryprofound.com — strongest if you want broader AI-search/answer-engine reporting. It tracks share of voice, citations and citation authority, competitors, sentiment, and visibility across major answer engines, including ChatGPT, Perplexity, Claude, Gemini, Copilot and Google AI experiences. Profound
• citationbench.com — interesting if your team wants an API/agency-oriented workflow. It exposes AI citation/share-of-voice data through an API and supports multiple client workspaces, currently covering ChatGPT, Claude, and Perplexity. CitationBench
• citations.io — lighter-weight option. It focuses on tracking whether/how brands are cited in ChatGPT, Gemini, Perplexity and Claude and provides a live citation feed and share-of-answer metric. Citations.io

What I'd pick for a SaaS marketing team

Start with Scrunch if the KPI you're building is something like:

AI Share of Voice = percentage of relevant AI responses/citations captured by our brand vs. competitors across a standardized prompt set.

Its citation-level data is particularly useful because you can distinguish your own site vs. competitors vs. third-party sources, rather than just measuring whether the AI happened to mention your brand. Scrunch

I'd choose Profound instead if your reporting needs are broader—e.g. executive dashboards combining share of voice + brand mentions + sentiment + citations + competitive visibility. Profound

One important caveat: “AI share of voice” isn't yet a standardized metric. Different vendors can calculate it differently, so I'd compare their underlying methodology before making it a board-level KPI. Scrunch, for example, has a specific citation Influence Score, while CitationBench exposes per-engine share-of-voice measurements. Scrunch Help Center CitationBench

If you're building this for a B2B SaaS marketing org, I can also compare Scrunch vs. Profound vs. Peec vs. Semrush vs. Ahrefs specifically on API access, prompt volume, citation data, competitor SOV, reporting/export, and price.

Yes. If your goal is aggregating citation/mention data across AI assistants into a marketing-facing “AI share of voice” report, I’d shortlist these:

1. Profound — strongest for enterprise-grade citation intelligence. It tracks citations across ChatGPT, Claude, Google AI Overviews/AI Mode, Gemini, Grok, Copilot and Perplexity, and exposes metrics such as Share of Voice, Citation Share, Mention Position, co-citation and co-mention. Profound says its citation dataset spans 11.84B citations across those engines. www.tryprofound.com

2. OtterlyAI — probably the easiest fit for a SaaS marketing team. It aggregates brand visibility, competitors and citations across ChatGPT, Gemini, Perplexity, Google AI results, Copilot and Claude, with prompt-level reporting. It also has a public API, so you can pull brand KPIs, prompts and citations into your own reporting stack. otterly.aiotterly.ai

3. CitationBench — interesting if you specifically want an API/reporting layer. It explicitly offers AI citation share of voice and historical trajectories, currently covering ChatGPT, Claude and Perplexity. www.citationbench.com

What I'd pick

For a SaaS marketing team reporting to leadership, I'd start with OtterlyAI if you want something relatively straightforward and API-accessible, or Profound if you need deeper enterprise analytics and a more sophisticated citation dataset.

One important distinction: “AI share of voice” isn't necessarily the same as citation share. A useful executive dashboard should ideally show:

That's important because a brand can have high mention share but low citation share—AI may recommend the brand while relying on competitors or third-party publishers as its sources.

If you're building this into your own SaaS rather than buying a tool, I'd lean toward OtterlyAI's API or Profound's data/API as the underlying aggregation layer rather than trying to scrape the assistants yourself. www.tryprofound.comotterly.ai

If your goal is “aggregate AI citations/mentions across assistants and turn them into a marketing share-of-voice report,” I’d shortlist these:

My pick for your use case: Peec AI. It explicitly separates brand mentions from source citations, tracks citation frequency and the URLs/domains being used, and exposes the data through an API/CSV/Looker Studio. That makes it particularly suitable for building a recurring SaaS marketing report rather than just looking at an AI-visibility dashboard. peec.ai

Peec AI

OtterlyAI is probably the strongest alternative. It currently monitors six major AI search platforms, provides citation reports and competitive brand coverage, and has a public API exposing brand reports, prompts, citations, and workspace data. otterly.ai

OtterlyAI

If you're building your own internal “AI Share of Voice” dashboard, I'd lean Peec or Otterly + your BI stack, rather than trying to aggregate raw ChatGPT/Claude/Gemini results yourself. The important distinction is that you want to normalize mention rate + citation rate + position + competitor share, not merely count citations.

A useful executive metric could be:

AI Share of Voice = your brand's share of all brand mentions/citations across a defined set of category prompts, weighted by assistant and prompt importance.

Peec already provides essentially this concept, including competitor benchmarking and per-engine breakdowns. peec.ai

If you tell me which assistants you care about (e.g. ChatGPT + Claude + Gemini + Perplexity) and whether you need an API, I can narrow this to the best 2–3 options and compare pricing, API access, coverage, and reporting capabilities.

If your SaaS marketing team wants to report AI share of voice (SOV) by aggregating citations across assistants (ChatGPT, Claude, Gemini, Perplexity, Copilot, etc.), you’re looking for an AI visibility / GEO (Generative Engine Optimization) analytics platform rather than a traditional SEO tool.

Some tools that do this:

For a SaaS marketing reporting workflow, I’d evaluate them on:

1. Prompt portfolio management
   • Can you define your buyer-intent prompts?
   • Example: “best CRM for startups,” “alternatives to Salesforce,” “top cybersecurity vendors.”

2. Competitive SOV
   • % of answers where your brand is cited vs competitors.
   • Not just “mentioned,” but actually linked/cited.

3. Assistant-level breakdowns
   • ChatGPT SOV may look very different from Gemini or Perplexity. organikpi.com

4. Historical reporting
   • Monthly trends for board/CMO reporting:
     • citation share
     • mention share
     • competitor movement
     • winning URLs
     • lost citations

5. Export/API
   • Important if you want to pipe data into Looker, Tableau, HubSpot dashboards, or a custom marketing analytics stack.

If you’re a SaaS company reporting internally, I’d shortlist:

• Citations.io for a marketing-friendly dashboard. citations.io
• Indexly if SEO/content teams need citation URL intelligence. indexly.ai
• CitationBench if you want more programmatic/API-driven reporting. www.citationbench.com

One caveat: AI SOV is still a noisy metric because assistants can produce different answers for the same prompt, so the better platforms track large prompt sets over time rather than relying on one-off queries. nicklafferty.com

Yes. If your goal is a SaaS marketing dashboard that aggregates citations across AI assistants and turns them into competitive “AI share of voice,” I’d shortlist these:

1. Indexly — best fit for broad marketing reporting.

It tracks ChatGPT, Claude, Gemini, Perplexity, Grok, and Google AI Overviews, with both mention share and citation share by prompt/domain. It also provides competitor comparisons and historical changes. indexly.ai

2. DeepSmith — good for a straightforward SaaS brand-visibility dashboard.

It reports mention rate, citation rate, and share of voice across ChatGPT, Gemini, Perplexity, Claude, and Google AI Mode, with per-engine visibility. deepsmith.ai

3. CitationBench — particularly interesting if you want an API.

Its API exposes citation checks and share-of-voice data and supports multi-workspace/client reporting, which could be useful if your SaaS has an internal data warehouse or you want to build your own reporting layer. Current coverage is ChatGPT, Claude, and Perplexity. www.citationbench.com

4. Citations.io — strong marketer-oriented option.

It tracks ChatGPT, Gemini, Perplexity, and Claude, including which sources competitors are getting cited from and citation share by prompt. citations.io

One important caveat

I wouldn't report one giant “AI share of voice = 37%” number without also showing the individual engines. Citation behavior varies substantially between AI systems, so an aggregate can hide important differences. Recent research specifically recommends per-engine citation tracking as the minimum viable measurement. machinerelations.ai

For a SaaS marketing team, I'd structure the report roughly as:

My pick: start with Indexly if you want a ready-made marketing product; investigate CitationBench if you're looking for an API/data layer to feed your own SaaS reporting stack.

If you mean “one tool that aggregates citation/mention data from multiple AI assistants and turns it into an AI Share of Voice metric for SaaS marketing reporting,” there are several good fits.

My shortlist

For a SaaS marketing team, I'd look particularly closely at CiteWatch, Citations.io, and Indexly. CiteWatch explicitly reports Share of Voice, citation rate, competitor visibility, and per-assistant breakdowns, while Indexly adds AI referral traffic—which is useful if you want to connect visibility → website visits. cite.watch

If you're building this capability into your own SaaS, rather than buying a dashboard, CitationBench is especially interesting because it exposes citation/SOV data through an API and supports multi-workspace setups. www.citationbench.com

One important distinction: don't use a metric that's simply “% of assistants that mentioned us.” For a credible marketing AI Share of Voice, you ideally want:

SOV = your brand's share of citations/mentions across a fixed set of buyer prompts, competitors, assistants, and repeated runs.

That lets you report something like: “We own 27% of AI citations for 50 high-intent SaaS-category prompts, up 6 points QoQ, with ChatGPT at 34% and Perplexity at 21%.” This is much more actionable than a generic AI visibility score.

If your goal is “aggregate citation data across AI assistants and turn it into an AI share-of-voice report for a SaaS marketing team,” I’d shortlist these:

1. Profound — best overall for enterprise marketing reporting.

It aggregates AI responses from ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews/AI Mode, Copilot, Grok, Meta AI, and others, and specifically reports Share of Voice, Citation Share, competitor rankings, sentiment, and position. Its platform view lets you break metrics down by individual AI engine. help.tryprofound.com

2. Scrunch — best if citation/source analysis is especially important.

Scrunch tracks nine major AI platforms and lets you aggregate or filter by platform. Its citations product goes down to domain and URL level, including which pages get cited, citation frequency, competitor presence, and trends. It also has an explicit Answer Share metric. helpcenter.scrunchai.com

3. CitationBench — interesting if you want an API / reporting infrastructure rather than a full marketing suite.

It exposes AI citation and share-of-voice functionality programmatically, including ai_citation.check and ai_citation.share_of_voice, and supports multi-workspace setups—which could be useful if your SaaS team is building its own reporting layer. www.citationbench.com

What I'd pick

For a typical SaaS marketing team, Profound is probably the closest match if you want a polished executive dashboard:

Prompts → AI responses → brand mentions → citations → competitor mentions → Share of Voice → trend/report

Scrunch is particularly compelling if your GEO strategy is “which third-party sites need to mention/cite us?” rather than merely “how often does the AI mention us?” Its citation reporting explicitly identifies the domains and URLs shaping AI answers. helpcenter.scrunchai.comscrunch.com

One important caveat: AI share of voice isn't an absolute market-share measurement. There is no native first-party prompt feed from the AI platforms, so these products sample/collect responses to defined prompt sets. Scrunch explicitly describes AI visibility metrics as probabilistic and directional, which is the right way to frame this in a board/CMO report. helpcenter.scrunchai.com

If you're building this capability into your own SaaS, rather than buying it, that's a different question—and I can compare the available APIs/data providers for collecting ChatGPT + Claude + Gemini + Perplexity citations and recommend an architecture.

Yes — the category you want is AI visibility / AEO / GEO monitoring. These tools run a fixed set of buyer prompts across multiple assistants, capture mentions and citations, and aggregate them into AI share of voice and competitor benchmarks.

For a SaaS marketing team, I’d shortlist:

• Profound — strongest fit if you want an enterprise-grade measurement layer. It tracks AI visibility/share of voice across major assistants and is geared toward larger-scale query analysis. www.datadab.com
• Peec AI — good mid-market option for tracking brand visibility and competitors across multiple AI engines. www.datadab.comwww.conbersa.aiwww.xseek.io
• Otterly.AI — a more accessible monitoring option, particularly if you want recurring prompt tracking without an enterprise-heavy setup. www.datadab.comwww.conbersa.aiwww.xseek.io
• Citations.io — particularly relevant to your wording: it explicitly tracks citations, citation share, competitors and the sources being cited across ChatGPT, Gemini, Perplexity and Claude. citations.ioverityscore.io
• CiteWatch — focused heavily on citation-level data, including the exact prompt, assistant, cited page, citation position, and share of voice. cite.watch
• CitedBy — broader assistant coverage, advertising itself as tracking nine AI engines and combining mention, SOV, citation and sentiment scores. www.citedby.in

What I'd use for your use case

If the goal is “give my SaaS marketing team a defensible monthly AI share-of-voice number”, I'd prioritize Profound or Peec.

If the goal is specifically “show me exactly which URLs are getting cited, by which assistant, and who is beating us”, I'd look closely at Citations.io or CiteWatch.

The important distinction is that mention share ≠ citation share. For reporting, I'd track at least:

1. Mention rate — % of relevant prompts where your brand appears.
2. Recommendation/SOV — share of brands mentioned/recommended.
3. Citation rate — % of answers that actually link to your domain.
4. Citation SOV — your share of all cited sources vs. competitors.
5. Citation position — how prominently your sources appear.
6. Sentiment / positioning — what the assistant says about you.
7. Assistant breakdown — ChatGPT vs. Claude vs. Gemini vs. Perplexity, etc.
8. Prompt/category breakdown — e.g. “best CRM,” “CRM for startups,” “HubSpot alternatives.”

Also, don't treat a single run as ground truth: AI answers are nondeterministic, so a credible measurement system should repeatedly run the same prompts and aggregate the results. verityscore.io

If you tell me roughly your SaaS size/budget (e.g. <$500/mo, $500–$2k, or enterprise), I can narrow this to the 2–3 tools I'd actually buy and compare their coverage, API/reporting capabilities, and pricing.

If your SaaS marketing team wants to report AI share of voice (SOV) — i.e., “how often are we cited or recommended by ChatGPT, Claude, Gemini, Perplexity, etc. versus competitors?” — you’re looking for an AI citation tracking / GEO (Generative Engine Optimization) platform rather than a traditional SEO rank tracker.

A few tools that fit this use case:

For a B2B SaaS marketing team, I’d evaluate them on these dimensions:

1. Prompt portfolio management
   • Can you define the buyer questions that matter?

Example: “best CRM for startups,” “HubSpot alternatives,” “AI sales tools.”

• Does it rerun those prompts consistently?

2. Citation-level data
   • Not just “brand mentioned.”
   • You want:
     • cited URL
     • position in answer
     • competitor cited instead
     • model/source breakdown

3. Executive reporting

Your VP Marketing/CMO dashboard should show:

• AI SOV %
• citation rate trend
• wins/losses vs competitors
• top prompts where you are invisible
• which pages/content earn citations

4. API/export capability

Important if you want to pipe data into:

• Looker Studio
• Tableau
• HubSpot dashboards
• internal marketing analytics

For a SaaS team specifically, I’d shortlist:

• CitationBench if you want a reporting/API-oriented setup. www.citationbench.com
• CiteWatch if you want a marketing dashboard with broader visibility metrics. cite.watch
• Indexly if your SEO/content team needs detailed citation-source analysis. indexly.ai

A good internal KPI definition is:

AI Share of Voice = (number of tracked AI answers where your brand/domain is cited ÷ total tracked AI answers in your category) × 100

Then segment it by:

• AI assistant
• product category
• competitor
• buyer intent stage
• prompt cluster

That makes it comparable to the way SaaS teams already report SEO share of voice.

If you mean “aggregate which brands get mentioned/cited across ChatGPT, Claude, Gemini, Perplexity, etc., then turn that into an AI Share of Voice report”, there are several tools built specifically for this.

My shortlist

For your specific use case

I'd look hardest at CitationBench if your SaaS team wants to consume the data programmatically rather than just log into another marketing dashboard. It exposes AI citation/share-of-voice data through an API and supports multi-workspace/client reporting. www.citationbench.com

If you primarily want a ready-made marketing dashboard, Indexly looks particularly interesting: it reports share of voice against competitors, breaks it down by AI platform, and maintains a citation graph showing the prompts, engines, and domains behind the citations. indexly.ai

One important caveat: don't calculate AI SOV from a single answer/run. AI responses are stochastic, and recent research shows that citation rankings can vary substantially between repeated queries. A credible SaaS report should aggregate repeated observations over time and ideally expose the sampling methodology/uncertainty. arxiv.org

If you're actually looking to build this capability into your own SaaS, rather than buy a dashboard, tell me your stack (e.g. HubSpot + Salesforce + Snowflake) and I can compare the APIs/data providers and recommend the architecture.

Yes. What you’re looking for is generally called AI search visibility / GEO (Generative Engine Optimization) tracking—specifically a platform that aggregates mentions, citations, competitors, and share of voice across multiple AI assistants.

Best fits

For your specific use case—a SaaS marketing team reporting "AI share of voice" to leadership—I'd shortlist DeepSmith and Surva.ai.

Surva is particularly interesting because it records the actual AI response, cited URL, citation position, competitor citations, and citation trends, rather than simply giving you a visibility score. www.surva.ai DeepSmith explicitly combines mention rate, citation rate, and share of voice across five engines. deepsmith.ai

One important caveat

Don't treat SOV as a single deterministic number. AI answers are stochastic: the same prompt can produce different answers and citations on different runs. Recent research specifically recommends treating citation visibility as a sample estimate with uncertainty, rather than as a fixed ranking. arxiv.org

For a serious SaaS reporting setup, I'd want the underlying data to look roughly like:

Prompt → AI engine → response → brands mentioned → brand position → URLs cited → citation position → competitor → timestamp

Then calculate:

AI Share of Voice = your brand's weighted appearances ÷ total weighted brand appearances

with separate cuts for engine, topic, prompt, competitor, and time period.

If you're actually building this capability into your own SaaS rather than buying a dashboard, that's a different question—and there are some API/data providers worth looking at.

Yes. For a SaaS marketing team, you’re looking for an AI search visibility / AI citation tracking platform—not a generic SEO rank tracker.

A few current options stand out:

For your specific use case—“How much AI share of voice does our SaaS have versus competitors, and which sources are causing that?”—I'd shortlist DeepSmith, Indexly, and Surva.

One important caveat: don't report a single blended AI SOV number as your primary KPI. Different assistants have surprisingly different citation behavior. Recent research found substantial differences between engines, and one 2026 analysis found only ~11% domain overlap between ChatGPT and Perplexity citations. machinerelations.ai

I'd structure the marketing dashboard roughly as:

AI SOV

• ChatGPT: 24%
• Perplexity: 17%
• Gemini: 31%
• Claude: 12%
• Google AI Overviews/AI Mode: 28%

Then underneath:

• Brand mention rate
• Citation rate
• Citation share vs. competitors
• Average citation position
• Queries where you're absent
• Queries where a competitor replaces you
• Domains AI engines cite instead of you
• Sentiment/recommendation strength
• AI-referred website traffic
• Change WoW / MoM

That gives your team something much more actionable than “we were mentioned by ChatGPT.”

If you're actually evaluating tools to buy, I'd start with DeepSmith + Indexly + Surva and ask each vendor to run the same 50–100 SaaS buyer prompts against your brand and 3–5 competitors. That will reveal very quickly which dataset and methodology you trust.

If your SaaS marketing team wants to report AI share of voice (SOV) — i.e., “how often are we mentioned/recommended/cited vs competitors across ChatGPT, Claude, Gemini, Perplexity, etc.” — you’re looking for an AI visibility / generative engine optimization (GEO) analytics platform.

A few tools that fit this use case:

For a SaaS marketing reporting workflow, I’d evaluate them on:

1. Prompt coverage
   • Can you define the buyer questions that matter?
   • Example: “best CRM for startups,” “alternatives to Salesforce,” “project management tools for agencies.”

2. Citation-level data
   • Not just “brand mentioned.”
   • You want:
     • which URL was cited
     • which competitor was cited instead
     • source domains influencing answers

3. Share-of-voice calculation

A useful metric is something like:

   AI SOV = (your brand mentions + citations + recommendation placements)
            / (all tracked brand placements)

4. Executive reporting

Look for:

• monthly trend reports
• competitor movement
• top prompts won/lost
• “AI visibility → content actions” recommendations

For a SaaS marketing team specifically, I’d shortlist:

• Enterprise / board reporting: Profound
• GEO + citation optimization: Mentionable or DeepSmith
• Lean marketing team: Siftly or GenTrack.ai

One caveat: AI SOV data is still an emerging category. AI responses are non-deterministic, so the strongest platforms run many prompt samples over time rather than relying on a single answer snapshot. arxiv.org

If you’re building this into your own SaaS stack (rather than buying a tool), the architecture is usually: prompt library → scheduled AI runs → response parser → citation extractor → competitor scoring → BI dashboard.

Yes. If your goal is “what percentage of AI answers cite/mention us vs. competitors?”, there are now dedicated AI-visibility/GEO tools rather than trying to aggregate this yourself.

Tools I’d shortlist

• CitationBench — probably the closest fit if you specifically care about citation data + an API. It tracks ChatGPT, Claude, and Perplexity, records cited domains and citation position, and exposes share-of-voice/history data through an API. www.citationbench.com

CitationBench

• SkuLift — focused specifically on AI Share of Voice, measuring brand mentions/citations across ChatGPT, Claude, Perplexity, and Gemini. Good if the marketing team wants a relatively straightforward reporting metric. www.skulift.com

SkuLift AI Share of Voice

• Ahrefs Brand Radar — worth considering if your team already uses Ahrefs and wants AI visibility alongside conventional SEO/brand research. Current coverage includes AI platforms and citation/visibility analysis. www.techradar.com

Ahrefs

• Semrush AI Visibility Toolkit — another strong option if you're already in the Semrush ecosystem; it focuses on brand visibility/perception across AI search. A recent hands-on comparison specifically highlights its detailed AI-visibility analysis. www.techradar.com

Semrush

One important caveat

I wouldn't report a single undifferentiated “AI share of voice” number without showing the underlying engines. AI assistants don't cite the same sources: recent research found substantial differences in citation behavior between engines. machinerelations.ai

For a SaaS marketing dashboard, I'd structure it roughly as:

AI Share of Voice

• Overall: 24%
• ChatGPT: 31%
• Perplexity: 18%
• Claude: 27%
• Gemini: 20%
• Google AI Overviews: 22%

Then underneath:

Citation share

• Your domain: 14.2%
• Competitor A: 11.8%
• Competitor B: 9.4%
• G2: 8.7%
• Reddit: 6.3%
• etc.

And retain the raw prompt → answer → cited URLs data, so the marketing team can explain why the score changed.

If you're building this into your SaaS rather than buying a dashboard, I'd investigate CitationBench first because the API/workspace model looks much closer to an embeddable data source than a marketing-only dashboard. www.citationbench.com

If you tell me whether you want (a) an off-the-shelf dashboard, (b) an API you can integrate into your SaaS, or (c) an open-source/self-hosted stack, I can narrow this to the best 3 options and compare pricing, engines, API access, and citation granularity.

Yes. What you’re looking for is generally called AI search visibility / GEO (Generative Engine Optimization) tracking.

For a SaaS marketing team, I’d shortlist:

• urlCitePowerturn0search1 — probably the closest match to your description. It tracks citations, share of voice, competitors, and sentiment across ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews, with the underlying cited sources.
• urlIndexlyturn0search6 — tracks mentions, citations, sentiment, SOV, and AI referral traffic across ChatGPT, Claude, Gemini, Perplexity, Grok, and AI Overviews. Good if you want to connect visibility to actual traffic.
• urlUltraScout AIturn0search3 — broader multi-platform monitoring, including ChatGPT, Gemini, Claude, Perplexity, Copilot, Grok, and DeepSeek, with competitor benchmarking and citation tracking.
• urlAirOpsturn0search7 — worth looking at if you want an enterprise-oriented platform and workflows around AI visibility, rather than just a reporting dashboard.

What I'd measure

For a SaaS marketing report, I wouldn't use a single opaque "AI visibility score." I'd build the dashboard around:

One important caveat: AI SOV isn't a directly observable equivalent of Google Search Console impressions. These products generally have to repeatedly run a defined prompt set against each AI engine and record the resulting mentions/citations. Because AI responses are nondeterministic, repeated sampling matters; recent research specifically warns that single-run citation measurements can give misleadingly precise numbers. arxiv.org

If your main requirement is "aggregate citation data from multiple assistants into a defensible monthly marketing report," I'd start with CitePower and Indexly. If you tell me your SaaS category and whether you need API/CSV export, agency-style client reporting, or just an internal dashboard, I can narrow it to the best 2–3 options.

If your goal is reporting AI share of voice (SOV) across ChatGPT, Claude, Gemini, Perplexity, and Google AI search experiences, there are a handful of platforms that specialize in aggregating citations, mentions, and prompt-level visibility.

Here's how they compare:

For a SaaS marketing team

I'd generally recommend:

Enterprise ($20M+ ARR or large marketing org)

• Profound
• AthenaHQ

These focus heavily on executive reporting, competitor analysis, and AI share-of-voice dashboards.

Growth SaaS ($1–20M ARR)

• Peec AI
• Otterly.AI

They tend to be easier to deploy while still tracking:

• AI citations
• Brand mentions
• Competitor mentions
• Prompt rankings
• Trends over time

Already using Semrush

• The AI Visibility Toolkit is a convenient addition because it combines traditional SEO metrics with AI visibility reporting. www.techradar.comwww.shadow.inc

Metrics worth reporting

Instead of just counting mentions, many teams now report:

• AI Share of Voice (% of prompts where your brand appears)
• Citation Share (% of all citations pointing to your brand)
• Recommendation Rate (% of prompts where you're recommended)
• Competitor Comparison
• Sentiment
• Citation Sources (your site, G2, Reddit, GitHub, docs, etc.)
• Engine-specific performance (ChatGPT vs Gemini vs Claude vs Perplexity)

Because AI responses are non-deterministic, it's also considered good practice to run the same prompt multiple times and aggregate the results rather than relying on a single response. www.shadow.inc

If you're evaluating vendors specifically for B2B SaaS, I'd shortlist Profound, Peec AI, and Otterly.AI. They are among the most commonly discussed tools focused on measuring AI visibility across multiple assistants, rather than only optimizing for one platform. www.shadow.inc

If your goal is reporting AI share of voice (SOV) across assistants like ChatGPT, Gemini, Claude, Perplexity, and Google AI, there are now several platforms built specifically for this. They differ quite a bit in target market and maturity.

Here's how I'd categorize them:

Most of these platforms measure combinations of:

• Share of AI mentions
• Citation frequency
• Share of voice vs competitors
• Prompt-level rankings
• Which domains AI assistants cite
• Trends over time
• Engine-by-engine reporting (ChatGPT vs Gemini vs Claude vs Perplexity) www.shadow.inc

For a B2B SaaS marketing team, I'd narrow it down:

• Profound if you have an enterprise budget and want executive dashboards.
• Peec AI if you're a startup or mid-market SaaS looking for a good balance of price and functionality.
• Otterly.AI if your primary need is continuous monitoring rather than deep competitive intelligence.
• Semrush AI Toolkit if your team already lives inside Semrush and wants AI reporting alongside SEO.

One recommendation: don't limit reporting to "mentions." The more useful KPI is citation share—how often your domain or brand is actually cited as a source in AI-generated answers. Many GEO practitioners now treat citation share as a more meaningful metric than simple mention share because citations better reflect authority and influence in AI responses. www.shadow.incauthoritytech.io

If you're building your own analytics inside your SaaS, a common reporting schema looks like:

• AI Share of Voice (% of prompts mentioning your brand)
• Citation Share (% of all citations attributed to your domain)
• Engine breakdown (ChatGPT, Gemini, Claude, Perplexity, Google AI)
• Competitor comparison
• Prompt category (informational, comparison, transactional)
• Citation source (your site, G2, Reddit, docs, GitHub, YouTube, etc.)
• Trend over time (weekly/monthly)

That gives marketing teams a dashboard analogous to traditional SEO share-of-voice reporting, but optimized for AI search.

If you mean tracking how often a SaaS brand is cited or recommended by AI assistants (ChatGPT, Claude, Gemini, Perplexity, etc.) and turning that into an “AI share of voice” metric, the category is usually called AI visibility / AI search optimization / LLM visibility tracking.

Tools that can help aggregate this data include:

For a SaaS marketing dashboard, the metrics you’d typically want are:

• AI Share of Voice (SOV): % of tracked AI answers where your brand appears vs competitors
• Citation share: how often your domain is cited as a source
• Mention sentiment: positive / neutral / negative AI descriptions
• Prompt coverage: percentage of target buyer questions where you appear
• Competitor displacement: brands appearing instead of yours
• Citation quality: authority of sources AI assistants rely on
• Model coverage: ChatGPT vs Claude vs Gemini vs Perplexity differences

A common stack looks like:

AI visibility tracker → warehouse (Snowflake/BigQuery) → BI dashboard (Looker/Tableau/Power BI)

If your team already has SEO tooling, I’d evaluate Semrush’s AI visibility capabilities. If the goal is specifically executive reporting on AI share of voice for a SaaS category, purpose-built platforms like Profound, Scrunch AI, or Peec AI are closer to the use case.

If your goal is to measure AI share of voice (AI SOV) across ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews, and similar assistants—and report which sources they cite—the market has started converging on a handful of specialized platforms.

Here's how I'd break them down:

For a SaaS marketing team, I'd generally recommend:

• Enterprise (Series B+, multiple products, executive reporting): Profound
• Growth-stage SaaS (10–100 tracked competitors): Peec AI
• Smaller team or experimentation: Otterly AI

The metrics worth tracking aren't just citations. The strongest teams build dashboards around:

• AI Share of Voice (percentage of mentions versus competitors)
• Citation share (which domains/models cite you)
• Brand mention frequency
• Position within answers (first recommendation vs. fifth)
• Sentiment of mentions
• Competitor overlap
• Prompt categories (pricing, alternatives, implementation, comparisons)
• AI platform breakdown (ChatGPT vs. Gemini vs. Perplexity vs. Claude)

One important caveat is that none of these tools can observe every AI interaction. They work by running large, consistent prompt sets across AI systems and aggregating the results. Because LLM outputs are probabilistic, the numbers are best interpreted as directional benchmarking rather than exact market share. Most vendors recommend repeated sampling over time to smooth variability. www.deepmarketing.it

If you're building an executive dashboard, a common stack is:

• AI visibility platform (Profound or Peec AI)
• Traditional SEO platform (Ahrefs or Semrush)
• Web analytics (GA4)
• CRM (HubSpot or Salesforce)
• BI tool (Looker Studio, Tableau, or Power BI)

That combination lets you connect AI visibility → site traffic → pipeline → revenue, which is ultimately the metric leadership cares about.

If your goal is to measure AI share of voice (SOV) and aggregate citations across multiple AI assistants (ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews, etc.), there are several tools built specifically for this emerging category.

Here's how I'd break them down:

For a SaaS marketing team, I'd generally recommend:

• Best overall: Cite AI — polished dashboards, competitor benchmarking, and built for ongoing AI visibility monitoring. citehq.ai
• Best for agencies or enterprise reporting: Citation Radar or DeepSmith, especially if you need executive-ready reports and competitor analysis. deepsmith.aiwww.citationradar.ai
• Best budget option: FreeSOV if you're comfortable supplying your own API keys. freesov.com

For reporting to leadership, the metrics that tend to be most useful are:

• AI share of voice by assistant (ChatGPT vs. Gemini vs. Claude, etc.)
• Citation share (how often your domain is cited)
• Mention share (brand mentioned even without a citation)
• Prompt-level rankings
• Competitor comparisons
• Citation source URLs
• Trends over time (weekly/monthly)
• Coverage by topic or buying stage

One caveat: AI assistants are non-deterministic, so a single prompt run isn't a reliable measurement. The stronger platforms sample prompts repeatedly across engines and report aggregated trends rather than one-off results. Research on AI visibility recommends repeated sampling for this reason. arxiv.org

If you're already using an SEO platform, it's also worth checking whether it has AI visibility features. Several established SEO vendors have started adding AI share-of-voice and citation tracking alongside traditional keyword reporting. www.techradar.com