ChatGPT answers, unedited

For a SaaS marketing team measuring AI share of voice (SoV) from citations across assistants, look at AI visibility / GEO analytics platforms rather than traditional SEO tools:

• mentionscout.com — tracks answers and citations across ChatGPT, Claude, Gemini, Perplexity, Grok, and Google AI surfaces; provides competitor share of voice and cited-source analysis. MentionScout
• getveritas.io — focused on AI citations, brand mentions, and share-of-voice reporting across ChatGPT, Perplexity, Gemini, and AI Overviews. Veritas
• modelmention.io — provides AI visibility, position, share of voice, and citation tracking across major assistants. ModelMention
• cloro.dev — more API-oriented; useful if you want to build your own dashboard or integrate AI citation data into marketing reporting. cloro

For a SaaS marketing reporting workflow, I’d prioritize:

1. Prompt tracking (buyer questions by category)
2. Citation extraction (which domains/pages assistants trust)
3. Competitor SoV (share of mentions/citations vs rivals)
4. Trend reporting (weekly/monthly movement)

If you need enterprise dashboards, API access, or agency-style client reports, the API/reporting capabilities matter more than the raw tracking. cloro indexly.ai

Yes. What you’re looking for is generally called an AI visibility / AI citation tracking platform. These tools run a controlled prompt set across multiple assistants, collect the answers and cited URLs, then aggregate the results into metrics such as citation rate, mention rate, competitor share of voice, and citation share.

For a SaaS marketing team, I’d shortlist:

• tryprofound.com — enterprise-oriented AI search intelligence; useful if you need deep citation/source analysis and reporting across multiple AI engines. Recent industry research is using Profound data across ChatGPT, Perplexity, Gemini, Copilot and Google AI surfaces. Tinuiti
• peec.ai — focused specifically on AI visibility/GEO tracking, including competitor comparisons.
• otterly.ai — more accessible for teams/agencies wanting recurring AI visibility and citation monitoring.
• citationly.ai — explicitly tracks citations, mentions, competitors and share of voice across ChatGPT, Gemini, Claude, Perplexity, Copilot and Grok. CITATIONLY
• cloro.dev — particularly interesting if your SaaS team wants API-accessible raw citation data rather than just a marketing dashboard. It says its API returns parsed citations, source URLs, positions and labels across seven engines, which you can aggregate yourself into SOV. cloro

If you're building a reporting stack

I'd distinguish two use cases:

"Give me a dashboard" → Profound / Peec / Otterly

"Give me the underlying citation dataset so we can pipe it into our own BI/data warehouse" → Cloro or another API-first provider.

For your specific phrase "aggregate citation data from different AI assistants", the API approach is especially attractive. Your canonical dataset could look like:

date × prompt × AI engine × brand × cited URL × citation position × mention × recommendation

Then your marketing dashboard can calculate:

• AI Share of Voice = your brand's appearances ÷ all tracked brand appearances
• Citation Share = answers citing your domain ÷ all answers
• Mention Rate = answers mentioning your brand ÷ total answers
• Citation Position = average position when your domain is cited
• Competitor SOV by prompt category
• Engine-specific SOV — ChatGPT vs. Perplexity vs. Gemini, etc.

That's important because simply combining all assistants into one number can obscure substantial differences between engines. Current AI-visibility methodologies generally recommend retaining the per-engine breakdown. organikpi.com geosoftwarerankings.com

If you tell me your SaaS category, approximate number of prompts, and whether you want an API or just a dashboard, I can narrow this to 2–3 options and compare pricing, API access, engine coverage, and reporting capabilities.

Then your marketing dashboard can calculate:

• AI Share of Voice = your brand's appearances ÷ all tracked brand appearances
• Citation Share = answers citing your domain ÷ all answers
• Mention Rate = answers mentioning your brand ÷ total answers
• Citation Position = average position when your domain is cited
• Competitor SOV by prompt category
• Engine-specific SOV — ChatGPT vs. Perplexity vs. Gemini, etc.

That's important because simply combining all assistants into one number can obscure substantial differences between engines. Current AI-visibility methodologies generally recommend retaining the per-engine breakdown.

For a SaaS marketing team trying to report AI Share of Voice (SoV) from citations across ChatGPT, Gemini, Claude, Perplexity, etc., you’re looking for an AI visibility / AI search intelligence platform rather than a traditional SEO tool.

Some options:

For a SaaS marketing reporting workflow, I’d evaluate them based on whether they can provide:

1. Prompt universe management - Track the buyer questions that matter (e.g., “best CRM for startups,” “alternatives to Salesforce,” “AI tools for customer support”).
2. Citation-level data - Which URLs/domains were cited?
3. How often?
4. By which model?
5. Competitive SoV - Your citation share vs. competitors, not just raw mentions.
6. Historical reporting - Week-over-week/month-over-month movement for board or executive reporting.
7. Export/API access - So marketing ops can push data into Looker, Tableau, HubSpot, Salesforce, or a BI warehouse.

A typical executive metric set would look like:

• AI Citation Share of Voice: % of cited sources belonging to your domain vs. competitors
• AI Mention Share: % of answers mentioning your brand
• Engine Coverage: ChatGPT vs. Gemini vs. Claude vs. Perplexity performance
• Citation Win Rate: % of tracked prompts where you appear as a source
• Lost Opportunity Prompts: high-value queries where competitors are cited instead

If you’re building a SaaS marketing stack, I’d shortlist Profound, Otterly.AI, SearchVoro, Citationly, and Veritas for evaluation, then pick based on API/export needs and the AI engines your customers actually use. SearchVoro CITATIONLY Veritas

Yes. For your use case, I’d shortlist Profound and OtterlyAI, with Peec AI as another strong option.

• tryprofound.com — probably the best fit if your marketing team specifically wants citation share + AI share of voice reporting. It aggregates responses from multiple answer engines, tracks citations, Share of Voice, visibility, sentiment, and position, and lets you break results down by platform, topic, prompt, region, etc. Profound Help Center Profound Help Center
• otterly.ai — particularly attractive for a marketing/agency workflow. It tracks ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, including mentions, citations, sentiment and share of voice, with CSV/PDF exports and API/MCP access. Otterly Otterly
• peec.ai — good if you want straightforward competitive AI-visibility reporting. It tracks visibility, position, sentiment, SOV and the sources/citations behind AI answers across major engines. Peec AI Peec AI

My pick

For a SaaS marketing team's recurring executive report, I'd start with Profound. Its distinction between Share of Voice (how often your brand is mentioned) and Citation Share (how often your domain is used as a source) is especially useful. Profound Profound Help Center

I'd structure your report around:

1. AI Share of Voice — your brand vs. competitors
2. Citation Share — your domain vs. competitor domains
3. Share of Voice by AI assistant — ChatGPT vs. Gemini vs. Perplexity, etc.
4. Top cited pages/domains — what's actually influencing AI answers
5. Mention position — whether you're #1, #2, etc.
6. Prompt-level winners/losers — where competitors appear and you don't
7. Trend over time — weekly/monthly change

One important distinction: "AI share of voice" and "citation share" aren't the same metric. A brand can be mentioned frequently while another company's content is cited much more often. For a SaaS marketing team, I'd report both. Profound Help Center

If you're building this into your own SaaS rather than buying a tool, that's a different question—the underlying architecture for aggregating citations across ChatGPT, Gemini, Perplexity, Claude, etc. is worth mapping out separately.

If your goal is one source of truth for AI share-of-voice across multiple assistants, I’d shortlist these:

• citations.io — probably the closest match to your use case. It aggregates ChatGPT, Perplexity, Gemini, and Claude, with visibility, share-of-answer, citation coverage, competitors, and reporting. Citations.io Citations.io
• citeprism.com — broader coverage: ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews/AI Mode, and Copilot. It explicitly calculates share of voice vs. competitors and shows the sources being cited. CitePrism
• citationradar.ai — good if competitive SOV is the priority. It tracks ChatGPT, Perplexity, Gemini, Claude, and Grok and provides competitor SOV and citation-gap analysis. Citation Radar
• indexly.ai — interesting if your marketing team also wants AI referral traffic, sentiment, mentions, and citation share in the same measurement layer. Indexly
• cloro.dev — the one I'd investigate if you're actually building this into your SaaS/reporting stack rather than buying a marketer-facing dashboard. It provides an API returning normalized citation data across seven AI engines, which you can aggregate into your own SOV metric/dashboard. cloro

My recommendation

For a marketing team: start with Citations.io or CitePrism.

For a SaaS product that needs to ingest the underlying data and build its own reporting: look hardest at cloro. Its positioning is explicitly as a measurement API rather than just another dashboard. cloro

One important caveat: these platforms generally cannot observe what users privately ask assistants. They measure AI visibility by repeatedly running a defined panel of buyer prompts and analyzing the resulting answers/citations. CitePrism

For a credible client-facing AI Share of Voice metric, I'd therefore structure the data around:

brand → prompt → AI engine → run → mention → citation → cited URL → competitor → position

and calculate SOV from a fixed, repeatable prompt set rather than treating a single AI response as representative.

If you tell me whether you want an API you can integrate or a ready-made marketing dashboard, I can narrow this to the 2–3 best options and compare pricing/API access/reporting.

Yes — there are now several tools specifically built for this. For a SaaS marketing team, I’d shortlist these:

• otterly.ai — probably the strongest fit if you want broad assistant coverage. It tracks mentions, citations, sentiment, average rank, and share of voice across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot, and Claude, with competitors scored on the same prompts. Otterly
• citeprism.com — particularly interesting if citation-level evidence matters. It tracks ChatGPT, Claude, Gemini, Perplexity, Google AI, and Copilot, and lets you drill from the share-of-voice number back to the actual AI response and cited sources. CitePrism
• getmint.ai — good marketing-oriented option for tracking visibility, citations, sentiment, and SOV across major engines and comparing competitors by prompt. GetMint
• citationbench.com — worth considering if you want an API-first/data-pipeline approach. It exposes citation and SOV data for ChatGPT, Claude, and Perplexity and supports multi-workspace reporting, which is useful if your SaaS wants to pipe the data into its own BI/reporting stack. CitationBench
• surva.ai — focuses heavily on citations, capturing the full response, cited URL, citation position, and competitors across ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews. Surva.ai

What I'd choose for your use case

If your goal is “give marketing leadership a defensible AI share-of-voice report”, I'd prioritize:

OtterlyAI → best broad measurement coverage
CitePrism → best for drilling into why you're getting/losing citations
CitationBench → best if you want to aggregate the raw data into your own SaaS/BI infrastructure

One important distinction: brand mention share and citation share aren't the same metric. I'd report both:

AI Share of Voice = % of tracked AI answers in which your brand is mentioned/recommended
Citation Share = % of relevant source citations going to your domain
First-mention rate = % of answers where you're the first recommended brand
Competitor displacement = which competitor appears when you're absent

That gives your marketing team something much more actionable than a generic “AI visibility score.”

If you tell me your SaaS category and which assistants you care about (e.g. ChatGPT + Claude + Gemini + Perplexity), I can also compare these tools on API access, pricing, data ownership, historical data, white-label reporting, and accuracy and recommend one.

Yes. If your SaaS marketing team wants to aggregate citation data across multiple AI assistants and turn it into an AI share-of-voice report, I’d shortlist these:

• cloro.dev — probably the best fit if you want an API/data layer rather than another marketing dashboard. It says it returns parsed citations, source URLs, positions, and labels across 7 AI engines in a common response shape, which you can aggregate into your own SOV/reporting system. cloro
• citepower.com — more of an out-of-the-box monitoring platform. Tracks citations, SOV, competitors and sentiment across ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews. CitePower
• cite.watch — tracks ChatGPT, Gemini, Claude, Copilot and Perplexity, with citation rate, SOV, position and historical reporting. Cite Watch
• searchvoro.com — focused specifically on multi-engine SOV, including per-query citation share and the URLs that were cited. SearchVoro
• citationbench.com — interesting if you also want conventional SEO rank data alongside AI citation SOV; currently advertises ChatGPT, Claude and Perplexity coverage. CitationBench

What I'd pick for a SaaS marketing stack

If you're building your own reporting/dashboard, I'd start with cloro. The important distinction is that you're getting structured citation data that you can normalize yourself rather than buying someone else's definition of "AI visibility." cloro

Your data model could look roughly like:

prompt → assistant → response → brand mentioned → citation URL → citation position → competitor → timestamp

Then calculate:

• Citation rate = answers citing your domain / total answers
• AI share of voice = your citations or mentions / all tracked brand citations
• Engine SOV = SOV separately for ChatGPT, Claude, Gemini, etc.
• Competitive SOV = your share vs. Salesforce/HubSpot/etc.
• Source share = percentage of citations coming from your own domain vs. third-party sites
• Citation position = average/median position of your cited source
• Trend = week-over-week/month-over-month change

One important caveat: don't collapse all assistants into a single number without retaining the per-engine data. Recent research argues that cross-engine citation overlap can be quite low, so an aggregate SOV can hide meaningful differences between ChatGPT, Perplexity, Gemini, etc. Machine Relations

If you tell me whether you want an API to build into your SaaS or a ready-made tool your marketing team can use, I can narrow this to the best 2–3 options and compare API access, assistants covered, pricing, exportability, and reporting.

Yes. What you’re looking for is generally called an AI visibility / AI citation tracking / GEO platform. These tools query multiple AI assistants, capture the answers and citations, and aggregate them into metrics like AI share of voice, citation rate, competitor visibility, and source share.

Best fits for a SaaS marketing team

• citationradar.ai — Tracks ChatGPT, Perplexity, Gemini, Claude, and Grok, with competitor share-of-voice and the specific pages generating citations. It looks particularly aligned with your use case. Citation Radar
• citations.io — Tracks ChatGPT, Gemini, Perplexity, and Claude, including which competitors are cited instead of you. It also produces an implementation-oriented report. Citations.io
• mentionscout.com — Covers ChatGPT, Google AI Overviews/AI Mode, Gemini, Perplexity, Claude, and Grok, and explicitly supports competitor share-of-voice on the same prompts. MentionScout
• cite.watch — More analytics/reporting oriented: share of voice, citation rate, average citation position, model breakdowns, and historical trends. Cite Watch
• citeprism.com — Interesting if you care about how the assistants are answering, because it retains the full answer, citations, competitor mentions, and source domains behind each measurement. CitePrism

My pick for your specific use case

If the goal is “give our SaaS marketing team a defensible monthly AI share-of-voice report”, I'd shortlist Citation Radar, MentionScout, and CiteWatch.

One important caveat: don't treat a blended “AI SOV” number as equivalent to Google Search SOV. Different assistants have very different citation behavior, so a good reporting system should preserve assistant + prompt + date + citation + competitor underneath the aggregate number. Recent research specifically warns that aggregating engines without disclosing the query set, weighting, counting rules, and engine mix can produce misleading comparisons. Machine Relations

A solid executive report would therefore show:

• Overall AI Share of Voice: 18%
• ChatGPT: 24%
• Perplexity: 31%
• Gemini: 12%
• Claude: 15%
• Top 10 buyer prompts: where you win/lose
• Competitor SOV: you vs. 3–5 competitors
• Citation sources: which publications/sites are feeding the models
• Trend: MoM/quarterly change
• Citation position: first-mentioned vs. merely cited

If you're building this capability into your own SaaS rather than buying a tool, that's a different answer—I can map out the API/data architecture for aggregating ChatGPT, Gemini, Claude, Perplexity, etc. and calculating a defensible AI SOV metric.

Yes — there are several tools specifically built for this. If your goal is “aggregate what multiple AI assistants say/cite about our brand and turn it into a marketing-ready AI Share of Voice report,” I’d shortlist these:

• citations.io — best overall fit for a marketing team. It tracks ChatGPT, Gemini, Perplexity, and Claude, captures citations and competitors, and has dedicated Reports plus a shared evidence layer. It explicitly supports citation share and board-ready reporting. Citations Citations
• citationbench.com — best if you want an agency/reporting workflow. It provides AI citation Share of Voice, historical trends, competitor comparisons, multiple client workspaces, scheduling, and a REST API. It currently covers ChatGPT, Claude, and Perplexity. CitationBench
• citationradar.ai — best for broader assistant coverage. It tracks ChatGPT, Perplexity, Gemini, Claude, and Grok, including competitor Share of Voice and citation sources. Citation Radar
• provencite.com — good enterprise-style option. It covers six platforms: ChatGPT, Gemini, Perplexity, Claude, Copilot, and Grok, with citation monitoring, competitor benchmarking, and visibility scoring. Proven ROI
• citedspy.com — worth looking at for automated recurring reports. It says it runs weekly reports across six engines and provides competitor Share of Voice plus citation sources. CitedSpy

What I'd pick

For a SaaS marketing team, I'd start with Citations.io if you want a polished measurement/reporting system, or CitationBench if you're building a more programmatic reporting stack.

The metric I'd want the tool to give you is something like:

AI Share of Voice = percentage of relevant AI answers in which your brand is mentioned/recommended/cited, relative to your defined competitive set

And I'd report it by:

• AI assistant: ChatGPT / Claude / Gemini / Perplexity / etc.
• Topic or prompt cluster: e.g. “best project management software”
• Brand vs. competitors
• Mention rate
• Citation rate
• Citation position
• Share of Voice
• Trend over time
• Which URLs/sources are earning the citations
• Exact AI responses as evidence

One important distinction: “brand mention,” “recommendation,” and “citation” aren't the same metric. For SaaS reporting, I'd keep them separate rather than letting a vendor collapse everything into one opaque “AI visibility score.”

If you're building this capability into your own SaaS/marketing data stack rather than buying a dashboard, that's a different question — there are APIs/open-source approaches that can aggregate the underlying AI responses and calculate your own SOV methodology.

Yes — there are now several tools specifically built for this. For a SaaS marketing team, I’d shortlist these:

• Citations.io — probably the closest fit to what you described. It aggregates citations from ChatGPT, Gemini, Perplexity, and Claude, lets you define buyer prompts, tracks competitors, and produces a competitive share-of-voice view. It also keeps the underlying AI answers/citations as evidence for reporting. Citations Citations

citations.io

• CiteWatch — broader assistant coverage: ChatGPT, Gemini, Claude, Copilot, and Perplexity. It specifically reports Share of Voice, Citation Rate, and an AI Visibility Score, and can connect citations to actual site clicks. Cite Watch

cite.watch

• Citation Radar — covers ChatGPT, Perplexity, Gemini, Claude, and Grok, with competitor SOV and the questions/pages responsible for winning citations. This is interesting if your team cares heavily about competitive intelligence. Citation Radar

citationradar.ai

• CitationBench — particularly interesting if you want to integrate the data into your own SaaS/BI stack. It has API endpoints for citation checks, share of voice, and historical trends, currently covering ChatGPT, Claude, and Perplexity, with multi-workspace support. CitationBench CitationBench

citationbench.com

What I'd pick

For a normal SaaS marketing/Growth team, I'd start with Citations.io if the priority is a polished dashboard and recurring reporting.

If you're building a data warehouse / internal reporting layer, I'd investigate CitationBench first because its API and workspace model make it much more suitable for programmatic aggregation. CitationBench

One important distinction: don't just measure "does the assistant mention my brand?" For meaningful AI share-of-voice reporting, you ideally want prompt → assistant → answer → brand mention → citation URL/domain → citation position → competitor mentions → timestamp. That lets you answer not only "What's our AI SOV?" but "Why did our SOV change, and which competitors/sources are taking it?"

If you tell me your SaaS category and roughly how many prompts/competitors you want to track, I can compare these tools on coverage, API access, pricing, reporting, and data quality and recommend one.

Yes. What you’re looking for is generally called AI visibility / GEO (Generative Engine Optimization) tracking: a platform that runs the same buyer-intent prompts across multiple AI assistants, captures mentions + citations + competitor mentions, and aggregates them into an AI share-of-voice metric.

Best fits for a SaaS marketing team

• discoveredby.ai — probably the closest match to your description. It tracks ChatGPT, Gemini, Perplexity, Claude, and Grok, archives the exact URLs cited, benchmarks competitors, and reports Share of Voice. It also connects AI visibility to GA4/revenue. DiscoveredBy
• serps.io — particularly interesting if your team already cares about conventional SEO. It runs the same prompts across five engines and turns the resulting citations into share-of-voice, alongside Google rankings. SERPs
• citations.io — built specifically around citation intelligence, with tracking across ChatGPT, Perplexity, Gemini, and Claude plus prompts, competitors, citations, and reporting. Citations.io
• citationbench.com — worth a look if you want to feed the data into your own SaaS reporting stack. It exposes an AI-citation API with share-of-voice and historical data and supports multi-client workspaces. CitationBench

If I were building the marketing reporting stack

I'd shortlist DiscoveredBy for an out-of-the-box marketing dashboard and CitationBench if your team wants an API/data layer that you can pipe into your own BI or client-reporting system.

One important distinction: don't measure SOV from a single response. AI answers are nondeterministic, so good systems run multiple samples per prompt and across engines, then aggregate the results. verityscore.io

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 agency/client reporting tool, I can narrow this to the 3 strongest options and compare pricing, APIs, engines, and reporting.

If your goal is SaaS marketing reporting on AI share of voice (SoV) — meaning “how often do AI assistants cite or recommend us vs competitors” — you’re looking for an AI visibility / Generative Engine Optimization (GEO) analytics platform, not a traditional SEO tool.

Some tools that aggregate AI citation data across assistants:

For a SaaS marketing team, I’d evaluate them based on these reporting requirements:

• Prompt portfolio management

Can you track your actual buyer queries (“best CRM for startups”, “alternatives to X”, “enterprise project management tools”)?

• Citation-level evidence

The report should show:

• AI assistant
• prompt asked
• answer text
• cited URLs
• cited competitors
• citation position
• Competitive AI SoV formula

A useful metric is:

AI Citation Share of Voice = Your citations ÷ (Your citations + competitor citations)

• Breakdown by assistant

Avoid a single blended score. ChatGPT, Perplexity, Gemini, Claude, and AI Overviews can behave differently, so reports should show each separately. Citare

• Agency/client reporting

Look for:

• scheduled reports
• PDF exports
• dashboards
• competitor benchmarks
• historical trends

If you’re building this as a SaaS product yourself, the API route is probably the most flexible: collect AI responses → parse citations → normalize entities/domains → calculate SoV → expose dashboards. cloro

A typical stack would be:

1. AI response collection layer
2. Citation extraction/entity resolution
3. Competitor database
4. SoV calculation engine
5. Marketing dashboard (Looker, Metabase, custom UI)

For an internal marketing team, I’d shortlist CitePower, CiteWatch, Citations.io, and DeepSmith. For a product you want to sell, I’d look harder at an API-first provider like Cloro. CitePower Cite Watch cloro

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

A few worth evaluating:

• citepower.com — Tracks citations, share of voice, competitors, and narrative across ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews. This looks particularly close to your reporting use case. CitePower
• cite.watch — Tracks ChatGPT, Gemini, Claude, Copilot, and Perplexity, with citation-level drilldowns, SOV, sentiment, and historical reporting. Cite.watch
• citationradar.ai — Focuses on competitive citation tracking across ChatGPT, Perplexity, Gemini, Claude, and Grok, including which pages generate citations. Citation Radar
• searchvoro.com — Specifically normalizes multi-engine results into AI share of voice, with per-query and competitor comparisons. SearchVoro
• cloro.dev — Interesting if your SaaS team wants to build its own reporting layer: it positions itself as an API returning parsed citations, source URLs, positions, and labels across seven AI engines. cloro

For a SaaS marketing team

I'd shortlist CitePower if you want an out-of-the-box marketing dashboard, and cloro if you're looking to pipe the raw citation data into your own BI/reporting stack.

One important distinction: don't rely on a single blended "AI visibility score." For a credible marketing report, I'd want:

AI SOV → by assistant → by prompt/category → citation rate → citation position → cited URL → competitor SOV → trend over time.

That matters because the assistants behave quite differently; recent B2B SaaS research found substantial differences in citation behavior across ChatGPT, Perplexity, Gemini, and Claude. bevisibleiq.com

If you tell me your SaaS category and whether you want an off-the-shelf tool or an API, I can narrow this to the best 2–3 options and compare pricing, assistant coverage, API/export capabilities, and reporting quality.

For a SaaS marketing team trying to report AI share of voice (SOV) — meaning “how often do AI assistants mention us, cite us, or recommend us vs. competitors” — you’re looking for an AI visibility / generative engine optimization (GEO) monitoring platform, not a traditional SEO rank tracker.

Some tools that do this:

For a B2B SaaS marketing reporting stack, I’d evaluate them on these metrics:

• Prompt coverage: Can you define your buyer-intent questions (“best CRM for startups,” “HubSpot alternatives,” etc.)?
• Engine coverage: Does it track ChatGPT, Perplexity, Gemini, Claude, and Google AI experiences separately? Foglift
• Citation share: What percentage of cited sources belong to you vs. competitors?
• Mention share: How often your brand appears even without a citation.
• Position/ranking in answers: Are you the first recommendation or buried?
• Source intelligence: Which publications, communities, docs, or pages are causing competitors to win citations?
• Export/API: Can you push weekly numbers into Looker Studio, Tableau, HubSpot, or a board report?

A typical executive dashboard would show:

• AI Share of Voice: Brand 32% vs Competitor A 27% vs Competitor B 18%
• Citation Share by AI engine: - ChatGPT: 28%
• Perplexity: 41%
• Gemini: 22%
• Top winning prompts
• Lost prompts
• Top cited URLs
• Competitor sources you need to beat

One caveat: don’t collapse everything into one “AI visibility score.” AI engines often cite different sources and behave differently, so per-engine reporting is more actionable. Machine Relations

For a SaaS marketing team, I’d shortlist:

1. Profound or Otterly.AI for a mature enterprise GEO program.
2. Citepower / DeepSmith / Foglift if your main goal is citation-level reporting.
3. Semrush or Ahrefs if you want AI visibility bundled into an existing SEO workflow. Foglift

I can also help you build a vendor evaluation matrix (features, pricing, integrations, reporting quality) specifically for a SaaS marketing team.

Yes. If your goal is “aggregate what ChatGPT, Claude, Gemini, Perplexity, etc. say/cite about our SaaS and turn it into a defensible AI share-of-voice metric,” there are several purpose-built tools now.

My shortlist

• citations.io — probably the closest match to your description. It tracks ChatGPT, Gemini, Perplexity, and Claude, records citations and mentions, compares competitors, and produces share-of-answer/citation metrics and reports. Citations.io
• indexly.ai — broader analytics layer: ChatGPT, Claude, Gemini, Perplexity, Grok, and Google AI Overviews, with share of voice, citations, sentiment, and AI referral traffic. Indexly
• foglift.io — particularly interesting if your marketing team cares about auditable SOV. It retains the underlying prompt, answer, competitors, cited URLs, sentiment, and measurement window behind each score. Foglift
• deepsmith.ai — tracks mention rate, citation rate, and SOV across ChatGPT, Gemini, Perplexity, Claude, and Google AI Mode. DeepSmith
• cite.watch — good if you want to drill into individual citations and see model-by-model breakdowns, including ChatGPT, Gemini, Perplexity, Claude, and Copilot. CiteWatch
• citationbench.com — worth considering if you're building this into your own SaaS/reporting stack because it explicitly exposes citation/SOV APIs and multi-workspace functionality. CitationBench

For a SaaS marketing team, I'd pick based on the use case

One important distinction: “AI share of voice” isn't yet a universally standardized metric. Some platforms count whether your brand was mentioned, while others measure actual citations, citation position, or share of citation slots. Christian Lehman Foglift

For an executive SaaS report, I'd recommend defining your primary KPI as something like:

AI Citation Share = citations of our brand ÷ total citations earned by tracked brands across a fixed set of buyer prompts

Then report it by assistant and combined, rather than hiding everything behind one score. That's important because the assistants can produce materially different answers and citations for the same query. Foglift

If you're evaluating vendors to plug into your existing SaaS marketing stack, I can also compare these on API access, pricing, white-label reports, HubSpot/Looker/Tableau integration, prompt volume, and which assistants they actually query.

If your goal is AI share of voice reporting for a SaaS marketing team (e.g., “How often is our brand cited vs competitors across ChatGPT, Gemini, Perplexity, Claude?”), you’re looking for an AI visibility / generative engine optimization (GEO) analytics platform rather than a traditional SEO tool.

Some tools in this category:

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

• Prompt tracking: Can you define your buyer-intent prompts (“best CRM for startups”, “alternatives to X”, “X vs Y”) and run them continuously?
• Citation extraction: Does it capture the URLs/domains each assistant cites, not just whether your brand is mentioned?
• Competitive share of voice: Can it calculate: - % of answers mentioning your brand
• % of citations pointing to your domain
• competitor citation share
• sentiment/recommendation rank
• Export/API: Can you push data into Looker, Tableau, HubSpot, Salesforce, or your marketing BI stack?
• Historical reporting: Can you show month-over-month movement for executives?

A typical executive KPI set would look like:

• AI Mention Share: % of tracked AI answers where your brand appears
• Citation Share of Voice: your cited URLs ÷ all cited competitor URLs
• AI Recommendation Rank: average position when recommended
• Citation Velocity: new citations gained/lost per month
• Engine Breakdown: ChatGPT vs Gemini vs Perplexity vs Claude performance

One caveat: don’t rely only on an aggregate score. AI assistants have different retrieval and citation behaviors, so strong platforms report performance per engine as well as an overall score. Machine Relations

For a SaaS marketing team, I’d shortlist:

1. Profound — if you need enterprise-grade reporting.
2. Citations.io / DeepSmith / Indexly — if your main KPI is citation share and competitive visibility.
3. Otterly.AI or Peec AI — if you want a more marketing-ops-friendly starting point.

If you’re building this as a SaaS product yourself rather than buying one, the architecture is different: you’d typically need an LLM query runner, response parser, citation extractor, entity resolver, competitor database, and reporting layer.

Yes. What you’re looking for is usually called AI search visibility / GEO tracking / AI citation monitoring. These tools run a fixed set of buyer prompts across multiple AI assistants, capture the answers and citations, and aggregate them into share of voice, citation rate, competitor visibility, and source/domain data.

Best fits for a SaaS marketing team

• citations.io — probably the closest match to your description. It tracks ChatGPT, Gemini, Perplexity, and Claude, shows which sources are cited, and provides citation share per prompt/engine plus competitor share of voice. Citations.io
• indexly.ai — broader analytics: ChatGPT, Claude, Gemini, Perplexity, Grok, and Google AI Overviews, with share of voice, citations, sentiment, and AI referral traffic. Good if you also want to connect visibility to traffic. Indexly
• deepsmith.ai — tracks mention rate, citation rate, share of voice, competitors, and the actual answers behind the metrics across five AI surfaces. DeepSmith
• pierview.ai — particularly oriented toward brands/marketing teams, with daily citation tracking, competitor gap analysis, and citation-source mapping across ChatGPT, Claude, Perplexity, and Gemini. Pierview
• citationbench.com — interesting if you want an API/agency-style infrastructure rather than just a marketing dashboard. It exposes citation/share-of-voice data programmatically and supports multi-workspace reporting. CitationBench

What I'd choose

For a SaaS marketing team reporting to a VP/CMO, I'd shortlist Citations.io, Indexly, and Pierview.

The important thing is not simply "how often are we mentioned?" I'd want your reporting model to separate:

1. Mention share — % of relevant AI answers mentioning your brand.
2. Citation share — % of cited sources attributable to your brand/domain.
3. Position/prominence — whether you're the first recommendation vs. citation #8.
4. Competitor share — who is taking the visibility you're missing.
5. Source share — which third-party sites AI is using instead of your site.
6. Per-assistant performance — ChatGPT vs. Claude vs. Gemini vs. Perplexity.
7. Intent — informational vs. "best X" vs. comparison/buying prompts.

That last point matters: don't collapse everything into one AI share-of-voice number. Different assistants have substantially different citation behavior, so an aggregate score can hide the fact that you're dominant in Perplexity but nearly invisible in Claude, for example. Machine Relations

If your goal is specifically "give me one dashboard that I can plug into our SaaS marketing reporting stack", I'd lean toward Indexly. If your goal is "I want the underlying citation data/API so we can build our own reporting", I'd investigate CitationBench first. Indexly CitationBench

If you tell me your budget and whether you need an API, dashboard, or both, I can narrow this to the 2–3 strongest options and compare pricing, assistants covered, API access, and reporting capabilities.

Yes. If your goal is specifically “aggregate citations/mentions across multiple AI assistants and turn them into a SaaS marketing share-of-voice report,” there are now dedicated AI-visibility platforms for this.

My shortlist

• citations.io — probably the closest match to what you described. It tracks ChatGPT, Gemini, Perplexity, and Claude, records citations and competitors, and has a dedicated competitive SOV/reporting layer. Citations.io Citations.io
• citationradar.ai — broader assistant coverage: ChatGPT, Perplexity, Gemini, Claude, and Grok, with competitor SOV and recurring tracking. Citation Radar
• indexly.ai — particularly interesting if your marketing team wants to connect AI mentions + citations + sentiment + AI referral traffic. It reports SOV by platform across six surfaces, including AI Overviews. Indexly
• citationbench.com — worth considering if you're building this into an agency/reporting workflow. It has an API and multi-workspace architecture and exposes AI citation SOV data programmatically. CitationBench
• provenroi.com — covers ChatGPT, Gemini, Perplexity, Claude, Copilot, and Grok, with citation monitoring, accuracy auditing, and competitor benchmarking. Proven ROI

What I'd use for a SaaS marketing team

I'd start with Citations.io if you want an out-of-the-box marketing dashboard, or CitationBench if you want to pull the underlying data into your own BI/reporting stack.

The important distinction is that you don't really want a generic "AI visibility score." For a credible monthly SaaS marketing report, I'd want the tool to give you:

That last one is important: AI responses aren't deterministic, so a defensible SOV number should come from repeated sampling of a fixed prompt set rather than one query per keyword. Current tools explicitly address this with recurring/multiple sampling. Citations.io citedspy.com

If you're building a SaaS marketing reporting product/workflow rather than just buying a dashboard, I can also map out the best API/data source + schema for aggregating ChatGPT, Claude, Gemini, Perplexity, Copilot, etc. into a single AI Share of Voice metric.

Yes — there are now several tools specifically built for this. If your SaaS marketing team wants cross-assistant AI share of voice + citation reporting, I’d shortlist these:

• citations.io — probably the closest match to your requirement. It tracks ChatGPT, Gemini, Perplexity, and Claude, including mentions, citations, competitor share of voice, and the actual sources being cited. Citations Citations
• zumihq.com — strongest if you want broad coverage. It says it tracks up to nine engines, including ChatGPT, Gemini, Perplexity, Claude, Copilot, Grok, AI Overviews, AI Mode, and DeepSeek, with board-ready reporting. Zumi
• indexly.ai — interesting if your team also wants to connect AI visibility to AI referral traffic. It tracks mentions, citations, sentiment and referrals across six engines/platforms. Indexly
• foglift.io — particularly appealing for marketing reporting because it keeps the underlying prompt, answer, competitors, cited URLs and measurement window behind the aggregate SOV number. Foglift
• deepsmith.ai — tracks mention rate, citation rate and SOV across ChatGPT, Gemini, Perplexity, Claude and Google AI Mode, with the underlying answers available for investigation. DeepSmith

My pick for a SaaS marketing team

I'd start with Citations.io if your primary KPI is:

“What percentage of AI answers about our category mention/cite us versus our competitors?”

Its four-engine coverage is clean, and it explicitly supports competitor SOV and citation-source analysis. Citations

If executive/board reporting across the maximum number of AI surfaces is more important, I'd look at Zumi.

One important caveat: don't treat a single aggregate SOV number as the whole story. AI assistants behave quite differently. Recent research indicates substantial divergence in which brands and sources different engines cite, so your dashboard should show SOV by engine first, then an aggregate number. Machine Relations

A good SaaS AI-SOV dashboard would therefore have:

Brand → Engine → Prompt category → Mention rate → Citation rate → Citation position → Competitor SOV → Cited URLs → Trend

For example:

That gives marketing a much more defensible story than simply saying “we're visible in AI.”

If you're evaluating these as vendors for your SaaS, I can also compare the top 5 on pricing, API access, number of prompts, historical data, white-label reporting, Slack/webhooks, and whether their SOV methodology is actually statistically sound.

Yes. What you’re looking for is generally called an AI visibility / AI search visibility platform: it runs the same buyer prompts across multiple assistants, captures mentions and citations, and aggregates them into share-of-voice reporting.

For a SaaS marketing team, I’d shortlist:

• citepower.com — particularly close to your use case. It tracks citations, share of voice, competitors, and cited sources across ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews, with daily monitoring. Citepower
• deepsmith.ai — tracks mention rate, citation rate, and SOV across ChatGPT, Gemini, Perplexity, Claude, and Google AI Mode, with the underlying answers available for inspection. DeepSmith
• indexly.ai — broader analytics: mentions, citations, sentiment, SOV, and AI referral traffic across ChatGPT, Claude, Gemini, Perplexity, Grok, and AI Overviews. Indexly
• zumihq.com — good if you need a more comprehensive enterprise-style view; it supports up to nine AI surfaces and explicitly breaks visibility into mention rate, SOV, answer position, and citation sources. Zumi
• cloro.dev — interesting if you want to build your own reporting layer. Its positioning is API-first: it returns normalized citations, source URLs, positions, and labels across seven engines, which you can aggregate into your own SOV metric/dashboard. cloro

My pick for your specific requirement

If the goal is “give our SaaS marketing team a defensible monthly AI share-of-voice report”, I'd start with Citepower or Indexly.

If the goal is “we want the raw citation data/API and will build our own analytics into our existing marketing stack,” I'd investigate cloro first.

One important distinction: don't report a single blended “AI SOV” number without showing the engine-level breakdown. ChatGPT, Gemini, Claude, and Perplexity can cite very different sources, so a useful report should look something like:

That makes the metric much more actionable than simply saying “our AI visibility is 42%.” Recent SaaS-focused research also emphasizes separating direct citations, unlinked mentions, first-/third-party source share, and source density, rather than collapsing everything into one score. onemetrik.com

If you're evaluating vendors to buy, I can also compare the top 5 on pricing, API access, number of assistants, historical data, exports, white-label reporting, and agency/multi-client support.

For a SaaS marketing team trying to report AI share of voice (SOV) from citations and mentions across assistants (ChatGPT, Claude, Gemini, Perplexity, etc.), you’re looking for an AI visibility / GEO (Generative Engine Optimization) tracking platform rather than a traditional SEO tool.

Some tools that specifically aggregate AI assistant citation data:

For a B2B SaaS marketing reporting workflow, I’d evaluate them against these metrics:

• Citation share of voice: % of AI-cited sources that belong to your domain vs competitors
• Mention share of voice: how often your brand appears in answers
• Prompt coverage: which buyer-intent prompts you win/lose
• Assistant breakdown: ChatGPT vs Claude vs Gemini vs Perplexity performance
• Source attribution: which pages, reviews, communities, or publications AI systems cite
• Trend reporting: month-over-month movement for exec dashboards

A common reporting model is:

AI SOV = Your brand mentions (or citations) ÷ Total tracked brand mentions (or citations) across the same prompt set

The important part is keeping the denominator consistent: same prompts, competitors, assistants, and time period. Foglift

For a SaaS marketing team, I’d shortlist:

1. MentionScout — if you want a richer GEO workflow with recommendations and competitor analysis. MentionScout
2. Citations.io — if your reporting is primarily about “who gets cited and why.” Citations.io
3. AISoV — if you mainly need repeatable share-of-voice reports. AISoV

If you already have a data warehouse/BI stack, another route is building your own pipeline: scheduled prompt runs → capture responses → extract mentions/citations → normalize by prompt → push into Looker/Tableau/HubSpot dashboards. Some newer trackers also expose APIs or MCP-style integrations for pulling visibility data into workflows. MentionScout

For a SaaS marketing team trying to report AI share of voice (SOV)—i.e., “how often do AI assistants cite or recommend our brand vs. competitors”—you’re looking for an AI visibility / GEO (Generative Engine Optimization) monitoring platform, not a traditional SEO rank tracker.

Some tools that fit this use case:

For a SaaS marketing reporting workflow, I’d evaluate them against these requirements:

• Prompt tracking: Can you define buyer-intent prompts like “best CRM for startups” or “HubSpot alternatives”?
• Citation share: Does it calculate your percentage of appearances/citations vs. competitors?
• Assistant breakdown: Can you show “ChatGPT SOV: 18%, Perplexity SOV: 31%, Claude SOV: 12%”?
• Historical trends: Can you report month-over-month movement?
• Competitor benchmarking: Can you see who is replacing you in answers?
• Export/API: Can you push data into Looker, Tableau, HubSpot dashboards, or board reports?

A typical executive dashboard would include:

• AI Share of Voice %
• Citation rate
• Mentions by assistant
• Competitor comparison
• Top prompts won/lost
• Sources/pages earning citations
• Sentiment of AI mentions
• Trend line over time

If you’re a B2B SaaS company, I’d generally shortlist:

1. Profound for enterprise-grade reporting.
2. Citations.io or CiteWatch for marketing-team visibility.
3. CitationBench if you want to integrate AI citation data into your own SaaS dashboards or workflows. CitationBench Citations

One caveat: “AI share of voice” is still an emerging metric. Different vendors define it differently (mention frequency, citation frequency, answer position, or weighted visibility), so make sure the denominator matches how your marketing team wants to report success. Geo Software Rankings

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

• peec.ai — probably the best fit for a SaaS marketing team. It tracks visibility, position, sentiment, and share of voice, and identifies the sources most frequently cited for your prompts. It covers ChatGPT, Gemini, Perplexity, AI Overviews, and AI Mode. Peec AI
• tryprofound.com — stronger choice if you're an enterprise marketing org wanting deeper citation intelligence and reporting.
• citationbench.com — particularly interesting if you want API-accessible citation/SOV data that your team can pipe into its own reporting stack. It explicitly supports ChatGPT, Claude, and Perplexity and has multi-workspace reporting for agencies. CitationBench
• cite.watch — worth looking at if you care about the actual cited URLs as much as brand mentions. It tracks citations across ChatGPT, Gemini, Perplexity, Claude, and Copilot and provides per-assistant breakdowns. CiteWatch
• citationradar.ai — focused specifically on competitor citation/SOV analysis across ChatGPT, Perplexity, Gemini, Claude, and Grok. Citation Radar

What I'd choose for your use case

If your reporting question is:

“Across the AI assistants our prospects use, what percentage of relevant answers cite or recommend us versus our competitors, and which sources are driving that?”

I'd start with Peec AI or Profound.

If you want to build the reporting layer yourself—e.g. pull data into Looker/Tableau/BigQuery and calculate your own weighted AI SOV—I'd investigate CitationBench first because its API is explicitly designed around AI citation and SOV data. CitationBench

One important distinction: brand mention SOV ≠ citation SOV. For SaaS marketing, I'd report both:

• Mention SOV — how often the AI names your company.
• Citation SOV — how often your domain/content is actually cited.
• Citation share by source — which publications, review sites, Reddit, etc. are feeding the answers.
• Assistant-level SOV — ChatGPT vs Claude vs Gemini vs Perplexity, rather than hiding everything in one aggregate number.
• Competitor displacement — prompts where a competitor is cited/recommended but you aren't.

That's becoming particularly important because citation patterns can move substantially between assistants and over time; recent analysis, for example, found Reddit's share of ChatGPT citations changing materially within just a few weeks. Axios

If you tell me your SaaS category and roughly how many prompts/competitors you want to track, I can narrow this to the 2–3 tools I'd actually buy, including API/reporting capabilities and likely pricing.

• Mention SOV — how often the AI names your company.
• Citation SOV — how often your domain/content is actually cited.
• Citation share by source — which publications, review sites, Reddit, etc. are feeding the answers.
• Assistant-level SOV — ChatGPT vs Claude vs Gemini vs Perplexity, rather than hiding everything in one aggregate number.
• Competitor displacement — prompts where a competitor is cited/recommended but you aren't.

That's becoming particularly important because citation patterns can move substantially between assistants and over time; recent analysis, for example, found Reddit's share of ChatGPT citations changing materially within just a few weeks.

Yes — there’s now a fairly mature category for this: AI visibility / GEO / AEO monitoring platforms. They query multiple assistants with the same buyer prompts, capture mentions and citations, and calculate competitive share of voice.

For a SaaS marketing team, I’d shortlist:

My pick for your use case

If the requirement is specifically:

“Aggregate citation data from different AI assistants so our SaaS marketing team can report AI share of voice.”

I'd start with Zumi or SKYA.

The important distinction is that you don't really want a generic “AI visibility score.” You want the underlying evidence layer:

Buyer prompt → assistant → answer → brand mentions → competitors mentioned → cited URLs → citation position/prominence → timestamp

Then aggregate that into something like:

• AI Share of Voice: 23%
• Mention rate: 41%
• Citation rate: 18%
• Recommendation rate: 27%
• Citation share: 14%
• Competitor A: 31%
• Competitor B: 19%
• Competitor C: 12%
• Top sources AI assistants cite in your category
• SOV by assistant — ChatGPT vs Gemini vs Perplexity vs Claude
• SOV by buyer-intent prompt
• Change vs. last month/quarter

That distinction matters because being mentioned isn't the same as being cited, and being cited isn't necessarily the same as being recommended. Current AI-visibility research/tools increasingly separate these signals rather than collapsing them into one score. onemetrik.com

Also, don't treat the resulting SOV number as perfectly deterministic: AI answers vary between runs, so a good measurement system should repeatedly sample prompts and report trends/ranges rather than pretending one snapshot is exact. verityscore.io

If you're evaluating this as a SaaS buyer, I'd choose based on whether they let you export the raw answer/citation data via API, not just whether they have a pretty SOV dashboard. That's what will let your marketing team eventually build its own reporting in Looker, HubSpot, Salesforce, or your warehouse.

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