How AI describes you: a census of 115 listings

The GEO practice explicitly hands sentiment work to a different 5W practice, so attribute-level perception is not part of the citation program a buyer signs for; a separate published Reputation Index scores sentiment for named individuals.

Source retrieved 2026-09-10

Sentiment analysis is bundled from the entry plan up and is scored alongside visibility and share of voice in the dashboard.

Source retrieved 2026-09-10

Sentiment is scored per aspect of the brand inside a single answer, so one response can read positive on one attribute and negative on another.

Source retrieved 2026-09-12

Sentiment is one weighted input to the vendor's composite AI visibility score, so tone is measured, though no per-attribute breakdown of what engines associate with the brand is shown.

Source retrieved 2026-09-10

Per-engine sentiment on citations (positive/neutral/negative), plus daily community sentiment from X, Reddit, HN and Product Hunt.

Source retrieved 2026-09-02

Each simulated run logs sentiment and how the model frames the brand, and sentiment drift is reported per assistant over time.

Source retrieved 2026-09-08

Sentiment themes with binary positive/negative share by model, but the dashboard is withheld from Starter, which sees a mock-data preview.

Vendor promises a view of how models describe the brand, but publishes no sentiment score or named attribute set, so the depth of that reporting is unstated.

Source retrieved 2026-09-17

Brand Sentiment Index score on every tier; the trend needs Starter and competitor BSI needs Pro.

Source retrieved 2026-09-02

Sentiment classification runs over the collected answers and reports how the brand is framed when an engine does mention it, using the buyer's own Gemini key.

Source retrieved 2026-09-16

Records whether the brand is mentioned and how it is positioned in the answer, but publishes no sentiment or attribute-association tracking.

Source retrieved 2026-09-02

An LLM classifies each response positive, negative, mixed or neutral and extracts recurring themes, which then feed recommendations.

Source retrieved 2026-09-01

Perception scores each brand on visibility against narrative strength, surfacing the recurring themes and exact phrases engines attach to it.

Source retrieved 2026-09-12

Sentiment is one of the five scored inputs and is reported as a net figure over scored mentions; no attribute- or theme-level perception breakdown is published.

Source retrieved 2026-09-02

Entity and language analysis reports the people, organisations, products and topics engines attach to your prompts over time; sentiment is not a built-in score, you obtain it by firing a follow-on question at a model of your choice.

Source retrieved 2026-09-13

Real-time sentiment intelligence on both paid tiers.

Source retrieved 2026-09-02

A sentiment score on a negative-to-positive scale, withheld until there are enough mentions to score.

A 0-100 sentiment tone score is scored per mention and averaged per run; there is no attribute or theme breakdown.

Source retrieved 2026-09-02

Sentiment, mention frequency and a direct bias score are reported, so the sheet covers how engines characterise the brand, not just whether they mention it.

Source retrieved 2026-09-09

Sentiment is tracked beside presence, and AI Catalyst surfaces the sentiment gaps and brand-voice inconsistencies it says cost citations.

Source retrieved 2026-09-11

The free Brand AI Scanner scores tone with a keyword classifier plus overlap against a positioning sentence you supply across four lenses; the paid plans list a monthly visibility report but never describe sentiment as a plan feature.

Source retrieved 2026-09-08

Sentiment is one of the reported monitoring metrics, described as how models describe the business; it is stated for the measurement programme rather than as a named platform module.

Sentiment is claimed once on the Overview page and rendered as a positive or negative marker on brand cards, but no attribute-level perception analysis is described and the paid platform's docs never mention sentiment at all.

Source retrieved 2026-09-11

Sentiment is broken down per tracked entity as positive, neutral and negative, and is meant to be read against PR activity over time rather than as a one-off score.

Source retrieved 2026-09-11

Every captured answer is classified positive, neutral or negative and charted over time, with a separate LLM-judged context-health signal for wrong-industry or wrong-language descriptions.

Source retrieved 2026-09-13

One sentiment metric on how positive the language is; no breakdown of the attributes AI associates with the brand.

Source retrieved 2026-09-02

Sentiment analysis is listed as included on every plan; the vendor does not say which attributes it extracts or how they are scored.

Source retrieved 2026-09-02

A whole module returns market position, tone of voice, core keywords and a dominant trait with a 0-100 confidence score, run against live web search or training data.

Source retrieved 2026-09-03

Analyses recurring narratives, themes and sentiment by feature, use case or persona

Source retrieved 2026-09-02

Sentiment is classified and attributed to business drivers such as price, service and quality.

The Narrative Shaping workflow tracks which attributes and differentiators AI associates with the brand and how those descriptions drift, delivering a perception baseline and a deviation list.

Source retrieved 2026-09-15

Sentiment and share of voice sit beside mentions and position, and a free tool reports the strengths and concerns engines repeat about a brand.

Source retrieved 2026-09-13

Sentiment is collected per platform as positive/negative/neutral and shown per brand in the comparison table.

Source retrieved 2026-09-02

Sentiment is an optional AI analyst metered at $0.05 per analysed answer; presence and share of voice are the included, deterministic ones.

Source retrieved 2026-09-02

Word Association scores the words models attach to the brand for both frequency and sentiment, and tracks how that language shifts over time against rivals.

Source retrieved 2026-09-12

Sentiment is scored 0-100 across eleven attributes per engine, with a criticism feed that quotes the phrase and names the source.

Source retrieved 2026-09-08

They map and score what each platform believes about the brand across products, use cases and reputation, and track sentiment alongside citation share.

Source retrieved 2026-09-08

Sentiment is scored as a three-way polarity per mention and trended over time; the vendor never claims an attribute or theme breakdown.

Source retrieved 2026-09-03

Sentiment is one of the things Frase reads out of AI responses, but no attribute-level brand perception is described, and one of the vendor's own comparison tables records sentiment analysis as 'No' for Frase.

Classifies answer tone per model and reports distribution, trend and recurring themes.

Extracts the descriptive phrases models use about the brand, not just whether it is cited.

Source retrieved 2026-09-02

Sentiment and how engines characterise the brand are included on every plan, though the features page hedges sentiment with 'when available'.

Source retrieved 2026-09-14

Supplies a structured evidence bundle for qualitative sentiment and perception work, but no sentiment score.

Sentiment is reported as positive, neutral or factually wrong per mention rather than as an attribute map, and it arrives through monitoring or the agency's monthly reports.

Source retrieved 2026-09-14

Splits positive from negative mentions across AI platforms; advanced sentiment reporting is bundled on paid plans.

Source retrieved 2026-09-02

Sentiment tracking is a named reputation deliverable backed by in-house tooling that scores digital visibility by sentiment across search, social and reviews over time.

Source retrieved 2026-09-14

Sentiment is scored positive, neutral or negative and can be segmented by model, geography, persona and topic; the row is checked on every tier.

Source retrieved 2026-09-15

Sentiment is a single polarity score with a trend line; the vendor does not claim per-attribute association breakdowns.

Source retrieved 2026-09-02

Sentiment scored -100 to +100 with specific emotions and comparative language, and whether answers recommend or caution against the brand.

Brand associations in model outputs are reviewed from the Growth-tier technical assessment upward; there is no standalone sentiment or attribute product.

Source retrieved 2026-09-02

Sentiment plus the specific positive, neutral and negative words engines use

Three-way positive/neutral/negative classification per engine, trended over time, with competitor benchmarking.

A dedicated Sentiment page trends perception against competitors by topic and source, and separates neutral from positive and negative.

Source retrieved 2026-09-03

A sentiment score is tracked daily per model and the audit reports how LLMs describe the business, but no named attribute or theme breakdown is published.

Source retrieved 2026-09-03

Sentiment is excluded from Starter and included from Growth up; Reputation reports score seven dimensions from Scale up.

Source retrieved 2026-09-02

Sentiment is scored as positive/neutral/negative context per mention; no attribute or theme breakdown is described.

Source retrieved 2026-09-02

Brand Phrases plus a Buyer Persuasion Score from -10 to +10 describe how AI characterises the business.

Each stored response carries sentiment, key phrases and mentioned organisations, so the attributes an engine attaches to the brand can be inspected directly.

Source retrieved 2026-09-18

Sentiment is reported as a positive-share percentage and a distribution across prompts, which tells you tone but not which specific attributes the engines associate with the brand.

Source retrieved 2026-09-09

The Insights view carries a Sentiment section beside prompts, platforms and citations, and the report is promised with sentiment insights organized by topic.

Source retrieved 2026-09-02

Answers are classified positive/neutral/negative with the surrounding context; sentiment analysis is ticked on all four plans.

Source retrieved 2026-09-02

Feature-level sentiment scoring exists, but the machine-readable pricing sheet lists it as Pro and above while the plan cards show it on Growth.

Source retrieved 2026-09-02

Perception in AI engines is a stated Digital PR objective and the Convert work checked that product messaging is "displayed accurately and favorably", but no attribute or sentiment reporting is published.

Source retrieved 2026-09-02

A named Sentiment Analysis feature covering how engines and cited sources characterise the brand by topic, with competitor comparison; the free brand report adds how AI classifies you and what you seem known for.

Source retrieved 2026-09-03

Baseline reports what LLMs currently say about the brand, but no sentiment or attribute scoring is described.

Source retrieved 2026-09-02

The benchmark captures the positioning language models use about the brand, and the vendor treats competitor-framed descriptions as a problem it exists to fix.

Source retrieved 2026-09-03

Sentiment split into positive, neutral and negative mentions per engine.

Source retrieved 2026-09-02

Sentiment analysis is named as part of what the platform returns.

Source retrieved 2026-09-02

A dedicated Brand Perception module extracts the attributes models attach to your brand, scores them 0 to 100, and ranks you against tracked competitors on each one.

Source retrieved 2026-09-03

Monthly reports state what sentiment AI platforms associate with the brand.

Source retrieved 2026-09-02

Sentiment reporting extracts the themes and narratives AI attaches to the brand rather than only counting mentions.

Source retrieved 2026-09-09

Sentiment is named twice in prose as part of the platform, but no dashboard module, plan row or feature page describes attribute-level perception, so the depth is unpublished.

Source retrieved 2026-09-03

Sentiment is scored on a 100-point scale per response with a trend, distribution and prompt-type breakdown, and drills down to the responses dragging the score; no attribute taxonomy is documented.

Source retrieved 2026-09-02

Perception snapshots compare configured brand attributes against how each provider describes you, alongside a 0-100 sentiment score broken down by provider; a snapshot costs 10 credits per provider.

Reports sentiment of brand mentions in AI responses, split positive/mixed/negative with recurring attribute insights.

Source retrieved 2026-09-02

Sentiment and how AI describes the brand are tracked and folded into the Search Performance Index.

Every captured response is sentiment-classified per platform, and sentiment is 10% of the AI Citation Score.

Reports are run against an attribute 'brand match' type, and the vendor states over 200 such intents are selectable.

The Brand Audit scores accuracy, completeness, sentiment and competitive positioning across the engines.

Sentiment tracked by brand, topic and model with positive/negative keyword themes.

Source retrieved 2026-09-02

Sentiment analysis surfaces themes, topics, strengths and weaknesses AI associates with the brand.

Source retrieved 2026-09-02

0-100 sentiment score per response, for the brand and each competitor named

Sentiment classified positive, mixed or negative, filterable by platform, persona, funnel stage and country.

Source retrieved 2026-09-02

Sentiment and competitor framing measured across AI answers.

Brand Performance analyses sentiment, share of voice and the narrative drivers behind mentions, then produces AI-generated positioning recommendations, refreshed weekly rather than daily.

Source retrieved 2026-09-18

Sentiment and narrative tracking records how engines portray the brand, but the comparison table shows AI Sentiment Analysis starting on Starter, with full sentiment tracking reserved for Pro.

Source retrieved 2026-09-15

Sentiment ships today and is returned per answer through the API, but the deeper sentiment product with source attribution behind each shift is badged coming soon on its own page.

Source retrieved 2026-09-17

Sentiment Analysis is included by default in AI Brand Visibility and benchmarks a sentiment score against competitors.

Brand sentiment and framing versus competitors, sold as a plan line item from Pro upward

Answers are scored across twenty perception dimensions with the quotes behind them, and the same twenty scores are exposed as metrics in the Looker connector.

Source retrieved 2026-09-16

Each answer is scored positive, neutral or negative per engine, which is tone rather than attributes: no extraction of the qualities or themes a model associates with the brand is described.

Source retrieved 2026-09-17

Sentiment is reported alongside mentions and share of voice across the sampled AI responses.

Source retrieved 2026-09-02

Sentiment framing of brand mentions is sold from the Pro subscription upward; the free and one-off Starter audits do not list it.

Source retrieved 2026-09-18

An Evaluation metric reports what AI presents as strengths and weaknesses; mentions are split into recommended, neutral and negative.

Source retrieved 2026-09-02

Sentiment and themes per mention, positive / neutral / negative.

Per-citation sentiment plus brand-attribute framing classified from the stored answer text and rolled up.

Sentiment scores, keywords and themes exist but start at the Growth plan.

Source retrieved 2026-09-02

Sentiment polarity is tracked and the product page lists Brands' Sentiment, but no attribute or theme extraction is described.