Peec AI Visibility Metrics Review (2026) - Engine Coverage, Pricing, Limits

Peec AI Visibility Metrics Review

Peec.ai tracks brand visibility and share-of-voice across AI engines; base plans cover 3 engines, with the full suite reaching six. An independent look at its coverage, pricing, reporting depth, and how the numbers hold up.

Compared here with Profound, Bluefish, and Brandlight.

By Ben Tannenbaum, Founder of Aiso

Updated June 2026·Featured in Search Engine Land& Forbes

Bottom line

Aiso rates Peec.ai at roughly 72% share-of-voice capture rate and 85% sentiment classification agreement against human-labeled ground truth — directional scores from a rubric-based review of its visibility stack, cross-checked against Peec's public materials and hands-on testing. These are not audited benchmarks. Peec does not publish its prompt-sampling design or precision / recall figures, so treat exact percentages as directional and use trend lines for decision-making. For a Looker-Studio-first team monitoring Google AI surfaces, Peec is a credible entry point. For teams that need Claude coverage, topic sentiment, or uncapped prompt volumes, a broader platform is worth evaluating.

~72%
Share-of-voice capture rate (Aiso directional assessment)
~85%
Sentiment classification agreement (Aiso directional assessment)

Confidence: High for directional trends and relative ranking. Moderate for exact percentages (rubric-scored, cross-checked; not independently audited). Engine counts, caps, and tiers change — confirm details directly with Peec.ai.

This review is maintained by the team at Aiso, an AI-search visibility platform behind a 5x AI-visibility lift for Particle and AI-visibility programs for brands like Sophia High School and Stay Unique.

Visibility metrics score breakdown

Share-of-voice capture

Aiso directional score~72%

Sentiment classification

Aiso directional score~85%

Scores are Aiso's directional assessment from a structured rubric-based review, cross-checked against Peec's published materials. Peec does not publish audited precision / recall benchmarks, so treat exact figures as directional. See how we assessed this.

AI visibility metrics: what they are and how Peec measures them

What AI visibility metrics measure. When a user types a question into ChatGPT, Perplexity, or Gemini, the model assembles a response from its training data, retrieval results, or both. Your brand either appears in that response or it does not. AI visibility metrics track the rate at which your brand (or a competitor) appears across a sampled set of prompts on a given engine. The core signal is share of voice: the fraction of sampled prompts in which your brand is mentioned. Secondary signals include whether your domain is cited as a source, what sentiment the model expresses, and which competitor brands co-appear.

How Peec collects the data. Peec.ai runs a pre-defined prompt set against each tracked engine on a recurring schedule, records the full response text, and classifies each response for brand mentions, source URLs, and sentiment (positive / neutral / negative). The metrics are then aggregated into a dashboard that shows share of voice, citation frequency (the ratio of responses that explicitly cite your domain versus those that merely mention your brand name), and sentiment distribution. Regional variants of the same prompt can be run to produce country-level breakdowns, though the number of supported countries is tied to the plan tier. Peec does not publish the full prompt-sampling design, sample sizes per engine, or reproducibility methodology, so absolute point-in-time figures should be read as directional.

Engine coverage and what it means in practice. Peec covers six engines: ChatGPT, Perplexity, Gemini, Microsoft Copilot, Google AI Mode, and Google AI Overviews. The inclusion of Google AI Mode and AI Overviews is a meaningful differentiator for brands whose customers use Google Search, since those surfaces now deliver AI-generated answers at the top of results. Claude (Anthropic) is not currently covered, which is a gap for brands tracked by enterprise buyers who use Claude-powered tools. The base plan covers three engines; additional engines are available at extra cost per Peec's published tier structure.

Sentiment analysis depth. Peec classifies each response as positive, neutral, or negative for your brand. Three-class sentiment is sufficient for a top-level health check, but falls short for teams that need to understand which topics or product claims drive negative responses. A 5-class model or topic-tagged sentiment can reveal, for example, that a brand scores well overall but consistently receives negative framing when AI engines address pricing. Peec does not offer topic-level sentiment in its current product; that distinction matters when building content-optimization strategies.

Evaluating what matters. When comparing AI visibility platforms, the questions that matter most are: (1) Does the prompt set reflect the queries your actual customers ask, or is it generic? (2) Is the sampling design disclosed enough to reproduce or challenge the results? (3) Are trend lines reliable even if absolute figures are noisy? Peec's Looker Studio connector and recurring cadence make trend tracking straightforward. The undisclosed sampling design means precision-critical use cases should be validated independently.

Metrics covered

Available metrics

Gaps

Key features evaluation

Strengths

Areas for improvement

How we assessed this

Sourcing methodology

We score every tool in this series on the same rubric — share-of-voice capture, sentiment classification, methodology transparency, engine breadth, and pricing clarity — and triangulate each figure from:

The resulting scores are directional estimates, not audited lab benchmarks. Where a number could not be traced to a primary, methodology-backed source, we mark it as reported or estimated. Peec does not publish its prompt-sampling design, sample sizes per engine, or independent validation, which is why precision-critical use should be validated directly with Peec. We refresh this page as new public information appears.

Competitive analysis

Metric Peec AI Profound Bluefish Aiso
Engines covered 6 4 (Enterprise) 4 5
Claude coverage No No Yes Yes
Sentiment classes 3-class 3-class 5-class 5-class + topics
Google AI Mode / Overviews Yes Limited Limited Yes
Looker Studio integration Native Via export Via API Native
Prompt cap (entry tier) ~25 Limited Quote-based Custom
Methodology transparency Limited Limited Limited Published

Reported / estimated ratings compiled from vendor materials and third-party reviews; not independently audited. Engine counts, caps, and tiers change over time, so confirm current details with each vendor. See how we assessed this.

Pricing and value

Peec publishes entry-level pricing, which is uncommon in this category. Reported tiers (from Peec's public materials as of mid-2026):

Base (reported)

~€89/mo

Mid-market (reported)

Higher tier

Enterprise

Custom

Reported figures from Peec's public pricing pages. Additional engines are reported at roughly €20–30/mo each above the base. Euro prices; USD equivalent varies with exchange rates. Confirm current tiers with Peec before committing.

What to trust Peec for, and what to verify

Trust it for

Verify before relying on

Recommendations

1

For Looker Studio-centric teams

Peec is the strongest pick if your marketing team already lives in Google Looker Studio. The native connector makes it straightforward to blend AI visibility data with other channel metrics without custom engineering.

2

For Google AI surface coverage

If Google AI Mode and AI Overviews are your primary concern, Peec is one of the few platforms that tracks both explicitly. Confirm the current list of supported surfaces before committing.

3

For teams needing Claude or topic sentiment

Consider Aiso, which adds Claude coverage, topic-level sentiment, and transparent prompt-sampling methodology, with no per-tier prompt caps. If prompt volume or analytical depth matters more than Looker Studio convenience, that is worth the comparison.

Frequently asked questions

How many AI engines does Peec AI track?

Peec.ai tracks brand visibility and share-of-voice across AI engines; base plans cover 3 engines. The full suite extends to six: ChatGPT, Perplexity, Gemini, Microsoft Copilot, Google AI Mode, and AI Overviews. Claude is not currently covered. Additional engines are available at extra cost per Peec's published tier structure. Confirm the current engine list directly with Peec, as coverage changes.

How accurate are Peec AI's visibility metrics?

Aiso's directional assessment scores Peec at roughly 72% share-of-voice capture rate and 85% sentiment classification agreement against human-labeled responses. These are rubric-scored estimates, cross-checked against Peec's published materials and hands-on testing — not independently audited benchmarks. Peec does not publish its sampling design or precision/recall figures, so treat these as directional. Confidence is high for relative comparisons and trend direction; lower for exact point figures.

How much does Peec AI cost?

Peec's base plan starts around €89/mo (approximately $95/mo at mid-2026 rates), with mid-market tiers higher. The base plan covers 3 AI engines; extra engines are reported at roughly €20–30/mo each. Prompt volume is capped by tier (roughly 25 / 100 / 300+ prompts), and the number of countries is also tied to plan. These figures are from Peec's public materials; confirm current pricing with Peec directly as tiers change.

Does Peec AI integrate with Looker Studio?

Yes. Peec exposes its metrics natively in-app and through a native Google Looker Studio connector, which makes it convenient for teams that already run marketing dashboards there. This is one of Peec's differentiating features compared with competitors that require manual export or API wiring to achieve the same result.

What is a good Peec AI alternative for visibility metrics?

If you need Claude coverage, topic-level sentiment, or prompt sets without per-tier caps, platforms like Aiso track every major engine and report daily share of voice, sentiment, and source attribution on transparent methodology. Profound covers 4 engines at enterprise scale. Bluefish specializes in citation analysis. The right choice depends on whether your priority is engine breadth, prompt depth, or budget.