ChatGPT answers, unedited

If you mean “which LLMs (ChatGPT, Claude, Gemini, Perplexity, etc.) describe our brand positively/negatively, and what is the sentiment score per model?”, you’re looking for an AI brand visibility / LLM monitoring tool rather than traditional social listening.

A few good options:

My shortlist by use case:

• Need a dashboard for marketing/brand teams: Rankr or Gumshoe. Rankr Gumshoe AI
• Need API data to plug into your BI stack: MentionsAPI. MentionsAPI
• Need SEO + AI visibility in one workflow: Nightwatch. Nightwatch
• Need lightweight competitor tracking: MentionHQ. Mention

When evaluating, I’d specifically check whether the tool gives you:

1. Sentiment by model (not just an aggregate score) - ChatGPT: +72
2. Claude: +55
3. Gemini: +80
4. Raw AI responses behind each score (so you can see the wording)
5. Prompt-level breakdowns (“best CRM for startups” vs “alternatives to X”)
6. Model/version tracking (sentiment can shift after model updates)
7. Competitor comparison

If you’re an enterprise brand, I’d lean toward Gumshoe or Rankr; if you’re building an internal “AI reputation dashboard,” I’d start with MentionsAPI. Gumshoe AI Rankr MentionsAPI

If you want to measure how different AI assistants talk about your brand (sentiment by LLM/model), you’re looking for an AI visibility / LLM brand monitoring tool rather than traditional social listening.

Here are the strongest fits:

My shortlist by use case:

• Marketing / brand team: Gumshoe — probably the closest match if you want “How does GPT vs Claude vs Gemini perceive us?” because it emphasizes model-by-model visibility and sentiment. gumshoe.ai
• SEO/GEO team: Nightwatch — useful if you want to connect AI mentions back to content sources and search performance. nightwatch.io
• Engineering/product analytics: MentionsAPI — better if you want raw data piped into a warehouse or BI dashboard. mentionsapi.comgumshoe.ai

When evaluating, I’d make sure the tool gives you:

1. Sentiment by model (not just an aggregate score)
2. Exact prompt tested
3. Full assistant response capture
4. Mention context (recommendation vs criticism vs comparison)
5. Competitor comparison
6. Historical trend after model updates

A useful KPI setup would be something like:

Brand AI Sentiment Score
 ├── ChatGPT: 82/100
 ├── Claude: 74/100
 ├── Gemini: 68/100
 └── Perplexity: 91/100

Negative themes:
- pricing mentioned negatively
- missing feature comparisons
- outdated product descriptions

If this is for an enterprise brand monitoring program, I’d start by piloting Gumshoe + an API-based option (MentionsAPI): one gives the executive dashboard, the other gives you ownership of the underlying data. mentionsapi.comgumshoe.ai

Yes — the category you want is LLM/GEO brand monitoring, but specifically one that exposes sentiment by model, rather than just aggregate AI visibility.

My top picks

1. Indexly — best match for your exact requirement
   • Breaks sentiment down per AI engine
   • Positive / neutral / negative split
   • Net Sentiment Score per model
   • Tracks ChatGPT, Claude, Gemini, Perplexity, Grok and Google AI Overviews
   • Also gives you the underlying prompts, mentions and citations. indexly.ai
   • Particularly useful if you want something like:

ChatGPT: 72 sentiment | Claude: 61 | Gemini: 48 | Perplexity: 79

2. Gumshoe — best for marketing/brand teams
   • Tracks sentiment, mentions, recommendation rate and visibility across individual models
   • Supports ChatGPT, Gemini, Claude, Perplexity, DeepSeek and others
   • Lets you segment by persona/topic and compare competitors. gumshoe.ai

3. Rankr — best simple dashboard
   • Explicit 0–100 sentiment score per mention
   • Model-level sentiment trends
   • Shows the actual AI responses so you can understand why the score changed
   • Tracks ChatGPT, Claude, Gemini and Perplexity. rankr.so

4. Nightwatch AI Brand Monitoring — worth considering if you already use SEO tooling
   • Tracks ChatGPT, Claude, Gemini, Perplexity and Copilot
   • Gives sentiment + exact surrounding context
   • Combines AI brand monitoring with traditional Google/SERP tracking. nightwatch.io

If I were choosing for your use case

I'd start with Indexly if your primary KPI is:

"When different AI assistants mention our brand, how positively or negatively do they describe us?"

I'd choose Gumshoe if you're building a broader AI brand reputation / GEO program, where you also care about personas, competitors and recommendation rates.

One important caveat: don't treat the sentiment score as a ground-truth consumer sentiment score. These tools are classifying the AI's description of your brand. That's actually the more useful metric here—you want to know whether ChatGPT is framing you positively while Claude is framing you negatively, for example. Indexly explicitly calculates sentiment from the full AI response and reports it independently by engine. indexly.ai

If you tell me your brand + industry + which LLMs you care about, I can narrow this to the 2–3 best tools and compare pricing, model coverage, API access, prompt volume, and sentiment methodology.

Yes. If your key requirement is “show me sentiment for our brand separately for each LLM”, I’d shortlist these:

1. Indexly — best fit for your exact requirement.

It explicitly tracks sentiment per AI model, alongside mentions, citations, and share of voice across ChatGPT, Claude, Gemini, Perplexity, Grok, and AI Overviews. It also stores the underlying responses, so you can inspect why a sentiment score changed. indexly.ai

2. Nightwatch AI Brand Monitoring — best if you already use an SEO/rank-tracking platform.

It monitors ChatGPT, Claude, Gemini, Perplexity and Copilot, with positive/neutral/negative sentiment plus the surrounding context of each mention. nightwatch.io

3. Rankr — clean/simple option.

It gives model-level visibility, mentions and a 0–100 sentiment score, with daily tracking across ChatGPT, Claude, Gemini and Perplexity. rankr.so

4. GetMint — good for marketing/GEO teams.

Tracks sentiment, mentions, citations and share of voice across major AI engines, with filtering by competitor, market, language and intent. www.getmint.ai

What I'd pick

Indexly if your primary question is:

“When ChatGPT mentions us, is it positive? What about Claude? Gemini? Perplexity?”

Its Net Sentiment Score per model is unusually explicit about this use case. indexly.ai

I'd also make sure whichever tool you choose lets you see the raw AI response alongside the sentiment classification. A single “sentiment = 72” isn't nearly as useful as seeing what the model actually said, the prompt that triggered it, and whether the sentiment came from a recommendation, comparison, criticism, etc.

If you tell me your brand/category and roughly how many prompts/models you need to monitor, I can narrow this to the best 2–3 tools and compare pricing, LLM coverage, sentiment methodology, API/export, and historical tracking.

Yes — what you’re looking for is generally called AI brand monitoring / AI visibility tracking / GEO monitoring. The important distinction is that you want sentiment broken down by LLM, not just an aggregate “AI sentiment” score.

My top picks

1. Gumshoe — best overall for brand perception
   • Tracks ChatGPT, Claude, Gemini, Perplexity and other models.
   • Shows visibility, recommendation rate, and sentiment by model.
   • Lets you analyze different buyer personas and topics, which is useful if you want to know why sentiment differs between models. gumshoe.ai
   • I'd start here if your goal is “What does each AI assistant think of our brand?”

2. Rankr — best straightforward dashboard
   • Explicitly reports sentiment on a 0–100 scale per mention.
   • Provides a model-by-model breakdown, e.g. ChatGPT vs. Claude vs. Gemini vs. Perplexity.
   • Also tracks visibility, position, competitors, and cited sources. rankr.so

3. Nightwatch AI Brand Monitoring — good if you already use SEO tooling
   • Monitors ChatGPT, Claude, Gemini, Perplexity and Copilot.
   • Has sentiment + surrounding context, alongside brand mentions and competitor monitoring.
   • Particularly attractive if you already use Nightwatch for traditional SEO/rank tracking. nightwatch.io

4. MentionsAPI — best if you want to build this yourself
   • API-level monitoring across ChatGPT, Claude, Gemini and Perplexity.
   • Returns brand, position, sentiment, surrounding context and cited URLs.
   • This is probably the most interesting option if you want to pipe the data into your own BI/marketing dashboard. mentionsapi.com

What I'd choose

If your requirement is specifically:

“For every prompt where our brand appears, tell me whether ChatGPT, Claude, Gemini, etc. talked about us positively or negatively, and let me compare the models.”

I'd shortlist Gumshoe and Rankr first.

The dashboard I'd want to see looks roughly like:

And importantly, I'd want to be able to drill from the score into the actual response/context that generated it. Otherwise a sentiment score alone isn't very actionable.

One caveat: these platforms generally run controlled prompts against the models rather than giving you a native analytics feed of every real conversation users have with ChatGPT/Claude/etc. That's an important distinction when evaluating vendors. www.rank.ai

If you tell me your budget and whether you want a SaaS dashboard or an API, I can narrow this to the 2–3 best options and compare pricing, model coverage, sentiment methodology, and API access.

If you want sentiment per AI assistant model (e.g., ChatGPT vs Claude vs Gemini vs Perplexity) when they mention your brand, you’re looking for an AI brand visibility / LLM monitoring tool rather than a traditional social listening platform.

A few options:

My shortlist depending on your use case:

• Marketing / brand team: Nightwatch AI Brand Monitoring — probably the closest match to “show me how each LLM talks about us.”
• GEO/AI SEO team: MentionHQ or AskLab.
• Data team that wants custom reporting: MentionsAPI.

Before choosing, I’d verify these capabilities in a demo:

1. Model-level breakdown — sentiment split by ChatGPT vs Claude vs Gemini (not just one blended score).
2. Prompt-level tracking — “What prompts caused negative sentiment?”
3. Raw response storage — ability to inspect the exact AI answer behind the sentiment label.
4. Competitor comparison — “Does Claude describe competitors more positively than us?”
5. Custom taxonomy — sentiment alone is often too shallow; you usually want themes like “expensive,” “innovative,” “enterprise-ready,” “unreliable,” etc.

If this is for an enterprise brand/reputation program, I’d also look at whether you need AI perception monitoring rather than just sentiment, because LLMs can mention a brand neutrally while still framing it in a strategically important way (for example, “premium but expensive”).

Yes. What you’re looking for is usually called AI/LLM brand monitoring or AI visibility tracking: it repeatedly runs the same buyer prompts against different assistants and records whether your brand appears, where it appears, and how the model describes it.

My top picks

1. Rankr — best fit for exactly what you described
Rankr tracks ChatGPT, Claude, Gemini, and Perplexity and explicitly provides sentiment scores per mention, alongside visibility, position, competitors, citations, and prompt-level analytics. Its dashboard example shows sentiment broken out by model. rankr.so

This would be my first tool to evaluate if your KPI is:

“When each LLM mentions our brand, is the description positive, neutral, or negative?”

2. Nightwatch — good if you already care about SEO/SERP monitoring
Nightwatch AI Brand Monitoring monitors ChatGPT, Claude, Gemini, Perplexity, and Copilot, with daily scans, sentiment/context analysis, competitor monitoring, and AI share of voice. nightwatch.io

The nice part is that it classifies mentions as positive / neutral / negative and shows the surrounding context, rather than giving you only a visibility number. nightwatch.io

3. Gumshoe — strongest if you want brand/reputation analysis
Gumshoe monitors 11 AI models and compares visibility, recommendation rate, and sentiment across models, including ChatGPT, Gemini, Claude, Perplexity, DeepSeek, and others. It also lets you analyze sentiment by persona/topic and compare competitors. gumshoe.ai

One newer option worth looking at

Prism is particularly interesting if you want something lightweight. Prism tracks the same prompts across ChatGPT, Claude, Gemini, and Perplexity and reports mention rate, sentiment, position, competitors, and trends per platform. It advertises plans starting at $19/month. searchprism.io

What I'd measure

I'd set up a dashboard like:

And, crucially, retain the actual response text behind each sentiment score. Otherwise a model saying “Brand X is widely criticized for…” could get reduced to a meaningless 0–100 metric.

My recommendation: start with Rankr if you want the cleanest match to “sentiment per LLM.” Look at Gumshoe if this is becoming a broader brand/reputation program, and Nightwatch if your team already uses it for SEO.

If you tell me your brand/category and whether you need an API, dashboard, or enterprise reporting, I can narrow this to the best 2–3 and compare pricing, model coverage, sentiment methodology, API access, and historical tracking.

If your goal is specifically “how does each AI assistant model talk about our brand?” (e.g., ChatGPT vs Claude vs Gemini sentiment), you want an AI visibility / LLM brand monitoring tool rather than traditional social listening.

My shortlist:

My recommendation by use case:

• Marketing / brand team: start with Gumshoe or Nightwatch. They are closest to “AI reputation management.” nightwatch.iogumshoe.ai
• Product/PR team that needs alerts when models say something wrong: look at Visiblie or Rankr. rankr.sowww.visiblie.com
• Data team wanting custom dashboards: use MentionsAPI and pipe results into Looker/Tableau/your warehouse. mentionsapi.com

When evaluating, I would make sure the tool gives you these dimensions per LLM model, not just an aggregate score:

1. Brand mentioned? (yes/no)
2. Mention position (first recommendation vs buried)
3. Sentiment (positive/neutral/negative)
4. Context/theme (pricing, reliability, complaints, competitors)
5. Exact model response excerpt
6. Prompt used to generate the mention
7. Trend over time after model updates

One caveat: these tools generally sample AI responses by running controlled prompts rather than observing private user conversations inside ChatGPT/Claude/Gemini. So the quality depends heavily on your prompt library and sampling methodology. mentionsapi.com

If you tell me your company size (startup vs enterprise), budget range, and whether you need dashboard only vs API, I can narrow this to 2–3 options.

Yes — what you want is usually called AI visibility / LLM brand monitoring, with sentiment broken out by model.

My top picks

1. Nightwatch AI Brand Monitoring — best overall if you want a mature SEO/brand-monitoring platform. It tracks ChatGPT, Claude, Gemini, Perplexity and Copilot, and specifically reports mention frequency, sentiment, context, competitors, and share of voice by LLM. nightwatch.io

2. Gumshoe — best if you want deeper analysis of why models represent your brand differently. It compares sentiment and visibility across 11 AI models, including ChatGPT, Gemini, Claude, Perplexity and DeepSeek, and can segment results by persona/topic. gumshoe.ai

3. Rankr — best for a simple model-by-model dashboard. It explicitly shows visibility, position, sentiment and mentions for each model, e.g. ChatGPT vs. Claude vs. Gemini vs. Perplexity. rankr.so

4. GetMint — worth considering if you also care about citations and share of voice, alongside sentiment. It supports ChatGPT, Gemini, Perplexity, Claude and Google AI Overviews. www.getmint.ai

If your requirement is specifically:

“Show me every time our brand is mentioned in an AI answer, tell me whether it's positive/neutral/negative, and let me compare that sentiment across different LLMs.”

I'd start with Nightwatch or Gumshoe.

One important distinction: you probably don't want just an aggregate “AI sentiment score.” Make sure the tool gives you the underlying prompt + model + response + sentiment classification. Otherwise, a score like “72% positive” isn't very actionable. Nightwatch, for example, says it provides the surrounding context for each classification. nightwatch.io

If you're building this into an internal brand-intelligence dashboard, there's also an API-oriented option: MentionsAPI exposes prompt runs across ChatGPT, Claude, Gemini and Perplexity with mention position and sentiment, so you could build your own model-by-model reporting layer. mentionsapi.com

My pick: Gumshoe if marketing/brand intelligence is the goal; MentionsAPI if you want to integrate the data into your own stack.

Yes. What you want is generally called AI visibility / LLM brand monitoring: run the same buyer prompts against multiple assistants, capture whether your brand appears, how it is described, sentiment, position, competitors, and ideally the underlying answer.

My top picks

1. Gumshoe — best if sentiment/context is the priority
   • Tracks ChatGPT, Gemini, Claude, Perplexity and other models.
   • Gives sentiment by model, visibility, recommendation rate, competitors, and the actual framing of your brand.
   • Particularly interesting because it can evaluate responses using buyer personas, rather than treating every prompt as identical. gumshoe.ai
   • I'd shortlist this if you're trying to answer: "What does each LLM think of our brand, and does that differ by customer type?"

2. Nightwatch AI Brand Monitoring — best straightforward monitoring
   • Monitors ChatGPT, Claude, Gemini, Perplexity and Copilot.
   • Explicitly provides positive/neutral/negative sentiment plus the surrounding context, broken down by platform.
   • Also tracks competitor mentions and share of voice. nightwatch.io

3. Prism — best lightweight/affordable option
   • Tracks ChatGPT, Claude, Gemini and Perplexity.
   • Reports mention rate, sentiment and trends per platform, including the actual prompts/answers.
   • Currently advertises AI tracking starting at $19/month. www.searchprism.io

4. MentionsAPI — best if you want to build your own dashboard
   • API-based rather than primarily a dashboard product.
   • Queries multiple LLMs and returns brand position, sentiment, surrounding context and cited URLs in a standardized response.
   • This is compelling if you want sentiment data flowing into your existing BI/marketing stack. mentionsapi.com

What I'd measure

Don't just track a single "AI sentiment score." I'd want a matrix like:

And critically, store the raw response. A sentiment score of 72 doesn't tell you why the model is positive or negative.

For example, you want to discover things like:

ChatGPT: "reliable, but expensive"
Claude: "strong enterprise option, though implementation can be complex"
Gemini: "well-established, but competitors offer better value"

That qualitative layer is much more actionable than generic sentiment.

My recommendation: start with Gumshoe if you're primarily a marketing/brand team; MentionsAPI if you're technical and want to own the data; Nightwatch if you want a more conventional monitoring/SEO workflow. The category is moving quickly, so I'd also benchmark whichever you choose against the actual raw LLM responses before treating its sentiment score as authoritative. www.trymonde.com

If you tell me your brand/category and roughly how many prompts you want to monitor, I can narrow this down to the 2–3 best options and compare pricing, model coverage, API access, historical data, and sentiment granularity.

Yes — what you’re looking for is usually called AI visibility / LLM brand monitoring, but the important differentiator is per-model sentiment/perception, not just whether the brand was mentioned.

My top picks

1. LLM Visibility — best match to your exact requirement
   • Runs the same prompts across ChatGPT, Gemini, Google AI Mode and Perplexity.
   • Gives sentiment scores with context, not just positive/negative.
   • Lets you see metrics by model, prompt and time, including the exact sentence behind the score. llmvisibility.tech
   • I'd start here if your core question is: “When different LLMs mention us, how positively or negatively do they describe us?”

2. Rankr — best for a simple model-by-model dashboard
   • Explicitly reports sentiment, visibility and position per model.
   • Tracks ChatGPT, Claude, Perplexity and Gemini, with an overall sentiment score from 0–100. rankr.so

3. Gumshoe — best if you care about “what is the AI actually saying?”
   • Runs prompts as different buyer personas across ChatGPT, Claude, Gemini, Perplexity and others.
   • Shows sentiment and perception differences by model, plus competitive rankings. gumshoe.ai
   • This is particularly interesting if you want to distinguish “mentioned positively” from “actually recommended for X use case.”

4. Nightwatch AI Brand Monitoring — worth considering if you already use Nightwatch for SEO.
   • Tracks brand mentions, sentiment and competitors across ChatGPT, Claude, Gemini, Perplexity and Copilot.
   • Daily scans across the monitored LLMs. nightwatch.io

What I'd choose

If your requirement is specifically:

Brand → prompt → LLM/model → exact response → sentiment/perception → trend over time

I'd shortlist LLM Visibility and Gumshoe first.

I'd also avoid buying a tool based solely on a single aggregate “AI visibility score.” The model-level breakdown matters because the same brand can be described quite differently by different AI systems; recent research also finds meaningful cross-model differences in recommendations. arxiv.org

A useful dashboard would ultimately look something like:

One caveat: sentiment scoring can be deceptively crude. I'd prioritize a tool that stores the raw LLM response and the specific language used to describe your brand, so your team can audit why a model received a particular sentiment score. LLM Visibility and GetMentioned explicitly emphasize this underlying-response approach. llmvisibility.tech

If you tell me your brand/category and whether you're looking for an enterprise tool or something <$500/month, I can narrow this to the 3 best options and compare pricing, models covered, sentiment methodology, API/export, and historical tracking.

Yes. What you’re looking for is generally called AI visibility / LLM brand monitoring, but the key requirement is sentiment broken down by model, not just overall mentions.

My top picks

1. Gumshoe — strongest fit
   • Tracks how your brand is described across ChatGPT, Claude, Gemini, Perplexity and other models.
   • Explicitly reports sentiment by model, alongside mention frequency, recommendation rate and competitive positioning.
   • Particularly interesting because it runs consistent buyer-persona conversations rather than simply scraping a handful of public AI-search results. gumshoe.ai

I'd start here if your goal is: “What does each LLM think of our brand, and how does that differ?”

2. Rankr — simplest dashboard
   • Gives a model-by-model table with visibility, sentiment (0–100), mentions and trends.
   • Covers ChatGPT, Claude, Perplexity, Gemini and Google AI Overviews. rankr.so

This looks particularly good if you want a clean “ChatGPT = 71 sentiment, Claude = 65, Gemini = 73…” type dashboard.

3. AskLab — good for broader AI-search analytics
   • Tracks mentions, rankings, citations, sentiment and share of voice.
   • Includes ChatGPT, Gemini and Google AI surfaces, with Claude also represented in its model comparisons. asklab.ai

4. Visiblie — worth evaluating for multi-LLM monitoring
   • Specifically positions itself around unified monitoring of ChatGPT, Perplexity, Claude and Gemini. www.visiblie.com

What I'd measure

For your use case, I wouldn't settle for a single "sentiment score." I'd want this matrix:

The negative/positive themes are arguably more valuable than the headline sentiment score—for example, discovering that Claude consistently calls you expensive while Gemini consistently calls you reliable.

One caveat: AI responses are stochastic and highly prompt-dependent, so you want a tool that runs a large, repeatable prompt set rather than asking each LLM one question and calling that "sentiment." Recent research also finds meaningful differences in emotional/sentiment characteristics across LLMs. arxiv.org

My shortlist: Gumshoe → Rankr → AskLab.
If you tell me your brand + industry + which LLMs matter most, I can also recommend the best one based on your specific monitoring requirements and pricing.

Yes. What you’re describing is usually called AI brand monitoring / LLM visibility monitoring / GEO (Generative Engine Optimization) monitoring—but the important requirement is sentiment broken out by model, not just overall brand sentiment.

My top picks

1. Gumshoe — best fit if model-level analysis is the priority

Gumshoe explicitly tracks how brands are described across ChatGPT, Claude, Gemini, Perplexity, DeepSeek, and other models, and its Brand Leaderboard includes mention frequency, recommendation rate, and sentiment by model. It also lets you compare the same buyer persona across models. gumshoe.ai

That makes it closest to what you're asking for:

The ability to see "Claude is more negative about us than ChatGPT" is exactly the kind of insight I'd prioritize.

2. Indexly — best if you mainly want sentiment/reputation tracking

Indexly specifically advertises positive/neutral/negative sentiment trends, factual inaccuracies, misconceptions, and reputation alerts across ChatGPT, Claude, Gemini and Perplexity. indexly.ai

I'd choose this if your primary question is "What is AI saying about our brand, and is that perception getting better or worse?"

3. Prism — good lightweight option

Prism runs your customer questions across ChatGPT, Claude, Gemini and Perplexity and tracks mention rate, sentiment and trends per platform, including where you appear in the answer and which competitors appear ahead of you. searchprism.io

One important distinction

I'd avoid a tool that gives you only an overall "AI sentiment score." You really want the underlying model × prompt × response data:

Prompt → Model → Exact response → Brand mention → Sentiment → Recommendation → Competitors → Citations

That's because the models can behave quite differently on the exact same question. Recent cross-model testing has found substantial differences in which brands get recommended, so averaging them together can hide useful information. www.reddit.com

If I were evaluating vendors for your use case, I'd start with Gumshoe and Indexly, then specifically ask each vendor whether their sentiment score is calculated per response/model and whether you can export the raw responses. That's more valuable than a black-box "8.2/10 AI sentiment" score.

If you tell me your brand/category and roughly how many prompts you want tracked, I can also give you a shortlist of 5–7 tools with pricing, models covered, sentiment granularity, API/export, and best fit.

If you mean “track how different LLMs (ChatGPT, Claude, Gemini, Perplexity, etc.) describe our brand and score the sentiment of those mentions”, you’re looking for an AI visibility / LLM brand monitoring tool rather than a traditional social listening platform.

My shortlist:

My recommendation by use case

• Enterprise brand / PR team: Meltwater — strongest if you already do media monitoring and reputation management. www.meltwater.com
• Growth marketing / SEO / GEO team: GetMint — closer to measuring “are LLMs recommending us vs competitors?” www.getmint.ai
• You specifically care about sentiment per LLM model: Sentaiment or MentionGEO are the closest fits. mentiongeo.aiwww.sentaiment.com

A good evaluation checklist:

1. Model-level breakdown: “ChatGPT says X, Claude says Y, Gemini says Z”
2. Prompt library control: ability to define buyer questions (“best vendors for…”, “alternatives to…”, “is X trustworthy?”)
3. Sentiment dimensions: positive/neutral/negative + themes (price, quality, reliability, trust)
4. Competitor comparison: not just “mentioned/not mentioned”
5. Raw response archive: you should be able to inspect the exact LLM answers, not only a score

One caveat: LLM sentiment is less stable than social sentiment because answers vary by prompt, model version, geography, and sampling time. The better platforms repeatedly run standardized prompts and track trends rather than treating a single answer as truth. www.techradar.com

If you tell me your brand category (B2B SaaS, consumer, ecommerce, etc.) and whether you need enterprise procurement, I can narrow this to the top 2–3.

Yes — you’re looking for an AI brand-monitoring / LLM visibility tool, but specifically one that breaks sentiment down by model, rather than just telling you whether your brand was mentioned.

My top picks

1. LLMWatch — best match
   • Tracks your brand across ChatGPT, Claude, Perplexity, and other LLMs
   • Explicitly tracks mentions, sentiment, and visibility
   • Lets you see how the same brand is being discussed across different AI assistants. llmwatch.io
   • I'd start here if your primary requirement is “show me sentiment for my brand separately in each LLM.”

2. CitationLab — good for brand perception
   • Tracks ChatGPT, Gemini, Perplexity and Google AI Overviews.
   • Captures whether mentions are positive, neutral, or negative, the context, and changes over time. citationlab.ai
   • Good if you care about what the AI is actually saying about the brand, not just mention counts.

3. AskLab — good if competitive positioning matters
   • Tracks mentions, rankings, sentiment, citations and share of voice.
   • Its dashboard explicitly breaks results down by ChatGPT, Gemini and Claude, including model-specific competitive results. asklab.ai

4. Stratus Analytics — broader enterprise-style option
   • Tracks mentions, citations, sentiment and competitors across ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews. truststratus.com

What I'd measure

Don't settle for just “brand mentioned: yes/no.” I'd want a dashboard like:

And ideally drill down to the actual response, so you can distinguish:

“Brand X is a leading solution with excellent support”

from

“Brand X is popular, but expensive and less suitable for enterprise users.”

That distinction is important because AI models can differ substantially in which brands they recommend—even when given the exact same prompt. www.reddit.com

If you tell me your brand/category and whether you're looking for a free/cheap tool or an enterprise platform, I can narrow this to the 2–3 best options and compare pricing + exactly which LLMs each one monitors.

Yes — what you’re looking for is generally called AI visibility / LLM brand monitoring, but the important distinction is whether the tool gives you sentiment/perception broken out by individual model, rather than just an overall visibility score.

My top picks

My first choice would be Nightwatch if you want something mature and easy to operationalize. It explicitly tracks brand visibility, sentiment, share of voice and competitor mentions across five LLMs, with daily scans. nightwatch.io

Ranqo is particularly close to your exact requirement. It says it captures three signals from every AI answer: whether you're mentioned, where you're positioned, and how the model describes you, with results broken down by ChatGPT, Claude, Perplexity, Gemini and Grok. ranqo.ai

One thing I'd verify before buying

Ask the vendor to show you a report like:

Brand sentiment by model

	ChatGPT	Claude	Gemini	Perplexity
Positive	72%	61%	48%	79%
Neutral	21%	31%	38%	17%
Negative	7%	8%	14%	4%
Avg. sentiment	+0.65	+0.51	+0.34	+0.72

That's materially more useful than an aggregate "sentiment = positive" score.

I'd also want the raw AI responses, the prompt that generated each response, the sentiment rationale/perception themes, competitors mentioned, and citations/sources. Otherwise you can't really diagnose why Gemini is more negative toward your brand than Claude.

If you tell me your brand/category and whether this is for marketing, PR, SEO/GEO, or executive reporting, I can narrow this down to the 2–3 strongest tools and compare pricing/features.

If your goal is to measure how different AI assistants (ChatGPT, Claude, Gemini, Perplexity, Grok, etc.) talk about your brand, you're looking for a relatively new category often called AI brand monitoring, LLM visibility, or AI search analytics. Traditional social listening tools generally don't measure this well.

Here are the strongest options:

If you specifically need sentiment broken down by LLM

The ideal workflow is:

1. Query each model with the same prompts.
2. Capture the full response.
3. Run a secondary classifier (another LLM or sentiment model) that scores:
   • Overall sentiment (-100 to +100)
   • Confidence
   • Key themes
   • Competitor mentions
   • Hallucinations/factual errors
4. Track scores over time.

This gives dashboards like:

If you're building this internally

Many companies build this using:

• A prompt orchestration framework (e.g., Langfuse, Helicone, or custom infrastructure)
• APIs from multiple LLM providers
• An evaluation framework to score sentiment and factuality
• A BI dashboard (Looker, Tableau, Metabase, or Power BI)

This approach provides more flexibility than most off-the-shelf tools and lets you define your own sentiment rubric.

My recommendations by company size

• Startup / SMB: Otterly.AI
• Growth-stage marketing team: Goodie
• Large enterprise: Profound
• Need custom sentiment scoring and benchmarking across many prompts: Build an internal evaluation pipeline with a tool like Hall or a custom LLM evaluation stack.

If your objective is competitive intelligence (e.g., "How does every major LLM describe us versus our competitors?"), Profound is currently one of the more mature purpose-built platforms in that category.

If your goal is to understand how different AI assistants (ChatGPT, Claude, Gemini, Perplexity, Copilot, Grok, etc.) talk about your brand, you're looking for a newer category often called AI visibility, LLM monitoring, or AI brand intelligence. These tools differ from traditional social listening because they repeatedly query multiple models and track mentions, sentiment, recommendations, and share of voice.

Here are some strong options:

If sentiment is your primary KPI

I'd shortlist:

1. Profound
   • One of the most mature products in this category.
   • Tracks how various LLMs answer prompts about your company.
   • Measures positive/neutral/negative framing.
   • Alerts when responses change.
   • Good for larger marketing teams.

2. Goodie AI
   • Focuses specifically on how brands appear in AI assistants.
   • Tracks sentiment and recurring themes.
   • Helps identify why one model is more favorable than another.

3. Scrunch AI
   • More enterprise-focused.
   • Includes recommendations for improving how AI systems represent your brand.
   • Useful if you want both monitoring and optimization.

If no tool gives exactly what you want

Many teams build a custom pipeline because they want finer control over sentiment.

Typical architecture:

• Query 10–20 prompts against:
  • ChatGPT
  • Claude
  • Gemini
  • Perplexity
  • Grok
  • Copilot
• Store every response.
• Use an LLM or classifier to score:
  • sentiment (-1 to +1)
  • confidence
  • recommendation likelihood
  • key themes
  • factual accuracy
• Compare results over time and against competitors.
• Visualize in a BI tool such as Tableau or Looker.

This approach is especially useful if you need brand-specific sentiment (e.g., "Would this response make a buyer more likely to choose us?") rather than generic positive/negative sentiment.

Recommendation by company size

• Startup / SMB: Otterly.AI or Goodie AI
• Mid-market: Profound
• Enterprise: Profound or Scrunch AI
• Custom research or product analytics: Build an internal LLM evaluation pipeline with scheduled prompts and sentiment scoring.

If you're evaluating vendors for procurement, I can also compare them specifically on:

• number of AI models covered,
• historical tracking,
• sentiment methodology,
• API availability,
• pricing,
• and dashboard quality.

If your goal is to measure how different AI assistants talk about your brand (rather than traditional social listening), you're looking for an emerging category sometimes called LLM visibility, AI search analytics, or AI brand monitoring.

Here are the strongest options:

If sentiment is your primary KPI

Most current tools measure:

• Positive recommendation
• Neutral mention
• Negative mention
• Share of voice
• Recommendation frequency
• Citation frequency
• Competitive comparisons

Few perform sophisticated sentiment analysis the way Brandwatch or Sprinklr do for social media.

The closest today are:

1. Profound
2. Goodie AI
3. Custom pipeline (best accuracy)

If you're an enterprise

Many companies build their own monitoring stack:

Scheduled prompts
        ↓
ChatGPT
Claude
Gemini
Perplexity
Copilot
        ↓
Capture responses
        ↓
LLM sentiment classifier
        ↓
Dashboard

This lets you calculate metrics like:

• Brand favorability
• Recommendation likelihood
• Competitive win rate
• Brand associations
• Hallucination rate
• Message consistency
• Citation quality
• Sentiment over time

Ironically, another LLM (or a smaller classifier model) often scores the responses for sentiment.

My recommendation by company size

Startup / SMB

• Otterly.AI
• Peec AI

Growth company

• Goodie AI
• Scrunch AI

Enterprise

• Profound (probably the most mature platform)
• Custom monitoring + warehouse + LLM evaluation

If your objective is "How does ChatGPT vs Claude vs Gemini describe our brand over time?", I'd lean toward Profound. It was built specifically for monitoring brand presence across AI assistants and includes competitive benchmarking, recommendation tracking, and perception analysis rather than just keyword rankings.

If your goal is to measure how different AI assistants (ChatGPT, Claude, Gemini, Perplexity, Grok, etc.) talk about your brand—including sentiment, recommendation frequency, and citation patterns—you'll want an AI search/LLM monitoring platform rather than a traditional social listening tool.

Here are some of the strongest options:

If you specifically want sentiment by LLM

The most mature options today are:

Profound

• Runs prompts across multiple AI assistants
• Tracks whether your brand is recommended
• Measures positive, neutral, or negative positioning
• Shows citations and sources each model uses
• Lets you compare results by model and over time

Best if you're an enterprise or larger B2B company.

Scrunch AI

• Monitors visibility in ChatGPT, Claude, Gemini, Perplexity, and others
• Detects messaging changes
• Competitor benchmarking
• Good dashboards for marketing teams

If you're willing to build your own

Many companies create a more customized pipeline:

• Schedule hundreds of prompts daily
• Query multiple APIs (OpenAI, Anthropic, Google, xAI, Perplexity where available)
• Store every response
• Use an LLM to score:
  • sentiment (-1 to +1)
  • recommendation strength
  • purchase intent
  • accuracy
  • messaging alignment
  • competitor mentions
• Build dashboards in tools like Looker, Tableau, or Power BI

This provides much more control than off-the-shelf dashboards.

Traditional social listening tools

Platforms like Brandwatch, Meltwater, or Sprinklr are excellent for web and social sentiment, but they generally do not natively measure how individual LLMs describe your brand.

Recommendation

• Enterprise: Profound
• Mid-market SaaS: Scrunch AI
• SEO/GEO team: Peec AI
• Cost-conscious startup: Otterly.AI
• Maximum flexibility: Build a custom evaluation pipeline across LLM APIs

If your company is already running prompts against multiple models, a custom pipeline can often produce richer sentiment and messaging insights than current commercial tools, especially if you want to compare responses across models, track trends over time, and evaluate specific aspects of brand perception.

If your goal is tracking how different AI assistants (ChatGPT, Claude, Gemini, Perplexity, etc.) talk about your brand, including sentiment, share of voice, and competitor comparisons, there are several tools built specifically for this emerging category ("AI visibility" or "LLM visibility").

Here's how I'd rank them:

If sentiment is your primary KPI

I'd look first at:

1. Meltwater GenAI Lens — strongest enterprise-grade sentiment and narrative tracking across models. It doesn't just count mentions; it tracks how the model portrays your brand and which sources influence those responses. www.meltwater.com

2. Ranqo — includes sentiment alongside:
   • mention frequency
   • ranking within responses
   • source citations
   • competitor comparisons
   • historical trends ranqo.ai

3. MeasureLLM — one of the more complete dashboards if you want visibility by model and competitive benchmarking. www.measurellm.com

Metrics I'd recommend collecting

Instead of only "sentiment," I'd capture:

• Brand mention rate
• Positive / neutral / negative sentiment
• Recommendation rate ("Would the model recommend us?")
• Share of voice vs competitors
• Position in the answer (1st mention vs 5th)
• Sources/citations the LLM relied on
• Prompt categories (pricing, security, integrations, support, etc.)
• Changes over time by model

This gives much more actionable insight than sentiment alone.

If you're building your own internal dashboard

A common architecture is:

• Schedule 100–500 representative prompts weekly.
• Query each model (ChatGPT, Claude, Gemini, Perplexity, Grok, etc.).
• Store raw responses.
• Use an LLM to score:
  • sentiment
  • recommendation strength
  • confidence
  • cited sources
  • competitors mentioned
  • key themes
• Visualize results in a BI tool such as Looker, Tableau, or Power BI.

Many teams are moving toward this approach because it lets them customize prompts and scoring beyond what off-the-shelf tools provide. www.reddit.com

For most companies, MeasureLLM is a strong choice for an out-of-the-box solution, while Meltwater GenAI Lens is better suited to enterprise PR and communications teams that need deeper narrative and reputation monitoring.