Best AI Visibility Platforms for Historical Trend Tracking

Answer Capsule

Profound is the consensus leader for historical trend tracking in AI visibility, named by 6 of 7 platforms (85.7%) at an average listed position of 1.5. Scrunch, Semrush, and OtterlyAI follow as the strongest alternatives for distinct buyer needs: Scrunch for citation-level date-range analysis, Semrush for teams already inside an SEO suite, and OtterlyAI for prospective daily prompt monitoring with transparent self-serve pricing. This study covered 7 platforms (openai, anthropic, deepseek, grok, perplexity, kimi, google), which named 35 unique entities; 8 qualified by being named by at least two platforms. The principal limitation is that platform recommendations are market intelligence, not verified product facts: pricing, retention windows, and snapshot immutability were frequently undocumented or contradictory across sources, and one standardized prompt was sent once to each platform.

Research Snapshot

• Topic: Best AI visibility and LLM monitoring platforms for historical trend tracking
• Target buyer: Companies seeking AI visibility platforms for historical trend tracking across AI search, generative-answer, and recommendation platforms
• Platforms included (7): openai, anthropic, deepseek, grok, perplexity, kimi, google
• Research date: 2026-09-19
• Unique entities named: 35
• Qualifying entities: 8
• Eligibility rule: Named by at least two platforms during ranking discovery
• Geography: United States
• Ranking unit: Software platform or research platform

Platform mentions count only ranking-discovery mentions. All 7 included platforms evaluated fit, but only platforms that named an entity during ranking discovery contribute to its mention count.

The Consensus Ranking

Questions This Section Answers

• What are the best AI visibility platforms for historical trend tracking in 2026?
• Which AI visibility platform has the deepest historical data retention for month-by-month visibility tracking?
• Which AI visibility platforms were named most often across ChatGPT, Claude, Gemini, Grok, Perplexity, Kimi, and Google?

Which Option Is Best for Which Version of the Buyer Need?

Questions This Section Answers

• Which AI visibility platform should a buyer choose for historical trend tracking if they need contractually documented retention and immutable snapshots?
• Is Profound or Scrunch better for historical trend tracking when citation-level date comparison matters?
• Which AI visibility platform for historical trend tracking is best for a team already using Semrush or Ahrefs?

1. Profound

Questions This Section Answers

• Is Profound worth it for historical trend tracking, and what are its main drawbacks?
• How many months of historical AI visibility data does Profound retain, and is it overwritten by newer results?
• Which AI visibility platform should an enterprise choose for historical trend tracking if it needs SOC 2 compliance and multi-engine coverage?

Profound is the consensus leader for this use case, named by 6 of 7 platforms at an average listed position of 1.5 and a best position of 1. It is the only entity in this index with a platform-reported retention figure: 18 months of historical data, with daily granularity for the most recent 6 months and weekly rollups for older periods ^[1]. Profound's Answer Engine Insights runs tracked prompts daily and reports visibility score, visibility rank, share of voice, and citation data per prompt ^[2]. Citation Share shows day-over-day changes across tracked prompts ^[4], and competitor benchmarking tracks competitor pages against historical baselines ^[5]. Data is collected from consumer-facing browser interfaces rather than APIs, which the company says reflects live retrieval-augmented answers including current citations ^[6].

Why it ranked here. Profound received first-place rankings from anthropic, deepseek, grok, openai, and perplexity, and a fourth-place ranking from google ^[1]. No other entity in this index was named by six platforms. Its combination of daily prompt-level collection, citation tracking, competitor benchmarking, and a stated retention window is the closest match to the full historical-trend-tracking brief.

Best suited for. Enterprise marketing, SEO, and content teams monitoring large prompt portfolios over time; companies needing visibility score, rank, share-of-voice, competitor, and citation-source trends across multiple AI answer engines; buyers willing to purchase quote-based software and verify data-retention and export terms.

Main strengths for the use case. Daily prompt tracking supports longitudinal monitoring rather than isolated snapshots ^[2]. Trend decomposition separates long-term direction, seasonal patterns, and anomalies ^[9]. Citation categories let teams mark citations as competitive and benchmark citation share against specific competitors ^[10]. Raw data can be exported from Answer Engine Insights to CSV ^[11]. Platform-specific trend breakdowns cover ChatGPT, Perplexity, Claude, Gemini, Grok, Microsoft Copilot, Meta AI, DeepSeek, and Google AI Overviews according to company materials ^[12].

Main limitations. Historical retention duration and immutable snapshot behavior are not publicly verified by independent sources; openai reported that public materials do not specify retention duration, immutable snapshot controls, sampling methodology, or complete historical-data availability by plan ^[13]. Kimi could not verify daily snapshot retention, prompt-level diff history, or citation velocity from primary sources ^[14]. Deepseek rated the fit mixed because retention window, snapshot immutability, and overwrite behavior are undocumented ^[15]. There is no native GA4 integration, which limits attribution of visibility trends to traffic or revenue ^[16]. Prompt Volumes is gated behind Enterprise pricing ^[17]. Starter covers ChatGPT only with 50 prompts, and Growth covers 3 engines with 100 prompts, so meaningful multi-engine trend tracking requires Growth or above ^[18].

Pricing or cost summary. Pricing is primarily quote-based.

2. Scrunch

Questions This Section Answers

• Is Scrunch worth it for historical trend tracking, and what are its main drawbacks?
• How far back does Scrunch historical data go, and can buyers export prompt-level and citation-level time series?
• Is Scrunch or Profound better for historical trend tracking when citation-level date comparison and API access matter?

Scrunch ranked second, named by 5 of 7 platforms at an average listed position of 5.2 and a best position of 2. Its most concrete historical claim is a 12-month retention window, or since account creation, whichever is shorter, with custom date range selection in Dashboard, Prompts, and Citations views ^[19]. Each collected AI response records the cited webpages, and citation data can be viewed over time with preset or custom date ranges, including a default last-12-weeks view and week-over-week citation visualization ^[21]. The Query API returns aggregated metrics grouped by day, week, month, quarter, or year, designed for trend analysis and BI integration ^[22].

Why it ranked here. Scrunch was ranked second by openai and third by grok, with mid-table placements from perplexity (5), deepseek (7), and anthropic (9). It is the only entity besides Profound with a platform-reported retention figure and a documented API path for historical trend extraction.

Best suited for. Marketing, SEO, and digital-intelligence teams tracking recurring prompts across multiple AI answer platforms; companies needing historical citation-share, competitor movement, and prompt-level reporting rather than one-time audits; enterprise buyers willing to obtain a current quote and validate data retention, export, and platform coverage.

Main strengths for the use case. Historical citation analysis with selectable timeframes and prompt-level drill-down ^[21]. Competitor and third-party citation ownership analysis with filters for competitor presence, citation owner, and branded versus non-branded prompts ^[23]. Segmentation by prompt, topic, persona, country, funnel stage, and custom tags ^[23]. Platform-specific statistics across a reported nine AI platforms, with ChatGPT, Perplexity, Google AI Overviews, and Gemini named in help content ^[24]. Sitecore acquired Scrunch in June 2026, which google cited as a factor in enterprise viability ^[25].

Main limitations. No verified public guarantee of immutable snapshots, unlimited retention, or a defined historical lookback period beyond the reported 12 months ^[21]. The Query API returns pre-aggregated derived summaries, not raw responses, and Scrunch does not explicitly document whether historical snapshots are locked or subject to recalculation ^[22]. Query API, CLI, Looker Studio, and MCP access are Enterprise-only; Core buyers cannot automate historical trend exports ^[26]. Per-brand-per-month billing applies, so multi-brand portfolios require separate subscriptions or Enterprise negotiation ^[27]. Citation-source crawling can be incomplete when pages block bots, rely on JavaScript, or are temporarily unavailable ^[23].

Pricing or cost summary. Anthropic reported Core at $250/month (125 prompts, 4 LLMs, 1 brand workspace, 5 user licenses), Growth at $500/month monthly or $417/month billed annually, and Enterprise custom, with extra seats at $25/month and a 7-day free trial on Core ^[26]. Google reported Starter at $300/month ($250/month billed annually) and Growth at $500/month ($417/month annually) ^[29]. Perplexity reported Explorer at $83/month billed annually and Agency Core at $500/month from public FAQ pages ^[30].

3. Semrush

Questions This Section Answers

• Is Semrush worth it for historical trend tracking, and what are its main drawbacks?
• How many tracked prompts does the Semrush AI Visibility Toolkit include, and which AI platforms does it cover?
• Which AI visibility platform for historical trend tracking is best for a team that already pays for Semrush SEO tools?

Semrush ranked third, named by 5 of 7 platforms at an average listed position of 5.4 and a best position of 3. Its AI Visibility Toolkit provides historical month selection and 1-month, 6-month, and all-time trend views, with historical data including brand metrics, performing topics, prompts, and cited sources for the selected period ^[31]. Competitor Research populates with six months of historical data ^[32]. Prompt Tracking monitors selected prompts daily across ChatGPT Search, Google AI Mode, and Gemini, including visibility, average position, position changes, and cited domains or pages ^[33].

Why it ranked here. Semrush was ranked third by deepseek, fourth by grok and perplexity, sixth by openai, and tenth by google. Its distinguishing feature is integration: AI visibility data sits alongside traditional SEO reporting and Position Tracking, which reduces tool sprawl for existing subscribers ^[34].

Best suited for. Marketing and SEO teams tracking brand visibility, citations, competitors, and topic-level movement over time; companies needing both broad database-based historical analysis and daily custom-prompt monitoring; organizations already using Semrush and wanting AI visibility data integrated with SEO reporting and Position Tracking.

Main strengths for the use case. Native historical trend views rather than only current-state snapshots ^[31]. Daily custom-prompt tracking for selected high-value prompts ^[33]. Citation, cited-page, source, topic, competitor, and average-position metrics ^[36]. A proprietary prompt database reported at more than 317 million prompts and responses across covered platforms and 117 regional databases ^[37]. Platform breakdown separates ChatGPT from Google AI Overviews so teams can diagnose algorithm-specific visibility changes ^[38].

Main limitations. The standalone toolkit documents only 25 Prompt Tracking prompts per account ^[40]. Prompt Tracking supports desktop searches only ^[33]. Platform coverage is not equivalent to universal monitoring of AI recommendation or shopping systems ^[41]. Visibility, audience, and AI-volume figures are modeled or estimated metrics rather than direct measurements of all user responses ^[42]. Brand Performance updates weekly, so it is less suitable for detecting daily narrative or citation changes ^[44]. The documentation does not fully establish immutable data retention, raw-response archival, methodology-versioning, or export availability for every historical report ^[31]. Regional scope is limited to six databases: US, UK, Canada, Australia, India, and Spain ^[45]. No automatic data archival exists; third-party guidance recommends exporting to CSV on a schedule to preserve historical snapshots ^[46].

Pricing or cost summary. The AI Visibility Toolkit is documented at $99 per month with no free trial, including one folder, one Brand Performance domain, 300 daily AI Analysis queries, 1,000 daily Prompt Research queries, 25 tracked prompts, AI Search Checks for up to 100 pages, and 10 daily CSV exports ^[40]. Additional Brand Performance domains or locations are documented at $99 each ^[40].

4. OtterlyAI

Questions This Section Answers

• Is OtterlyAI worth it for historical trend tracking, and what are its main drawbacks?
• Can OtterlyAI backfill historical AI visibility data from before a buyer signs up?
• Which AI visibility platform for historical trend tracking has the lowest published entry price with daily prompt monitoring?

OtterlyAI ranked fourth, named by 5 of 7 platforms at an average listed position of 5.8 and a best position of 5. It is the clearest example of a prospective-only historical tracker: data collection begins when a prompt is created, and earlier results are not backfilled ^[48]. Within that constraint, the platform stores each tracked answer and exposes individual prompt results, supporting prospective snapshots rather than overwritten-only current-state reporting ^[49]. It tracks configured buyer prompts daily and presents visibility changes over time, including brand mentions, ranking or order, sentiment, and share of voice ^[49].

Why it ranked here. OtterlyAI was ranked fifth by grok and openai, sixth by perplexity and deepseek, and seventh by anthropic. It qualified on five platform mentions despite no top-three placement, reflecting consistent mid-table recognition for daily prompt and citation monitoring.

Best suited for. Companies starting a structured AI-visibility measurement program from the purchase date onward; teams needing daily prompt, citation, competitor, and platform-level trend tracking; buyers that need exports, API access, or MCP access and can operate within prompt-volume limits.

Main strengths for the use case. Prospective historical tracking is explicit and tied to persistent prompts ^[48]. Daily collection supports regular trend lines for visibility, citations, sentiment, and competitors ^[49]. Prompt, engine, country, competitor, and cited-URL dimensions are directly relevant to longitudinal analysis ^[49]. Standard provides a practical mid-market starting point with 100 prompts plus API, MCP, and reporting integrations ^[50]. Multi-country tracking is supported across 50+ countries and 65+ language markets according to company materials ^[51].

Main limitations. No pre-purchase historical backfill ^[48]. Prompt limits count separately by country and may require higher tiers or add-on packs ^[52]. Base plans do not include every advertised engine; Google AI Mode, Gemini, and Claude are paid add-ons ^[53]. The public materials reviewed do not establish retention duration, immutable audit-log guarantees, timestamp granularity beyond daily tracking, or service-level guarantees for historical data availability ^[50]. Independent verification of long-term snapshot retention and non-overwrite behavior is lacking ^[55]. Citation detection accuracy was rated at approximately 91% by an independent assessment, but OtterlyAI does not publish formal audited precision or recall benchmarks ^[56]. Slow support response times have been reported ^[57].

Pricing or cost summary. Public pricing lists Lite at $29/month or $25/month annually (15 prompts), Standard at $189/month or $160/month annually (100 prompts), and Premium at $489/month or $422/month annually (400 prompts), with annual billing discounted 15% ^[50]. Additional 100-prompt packs are listed at $99/month or $1,020/year on Standard and Premium ^[50]. Add-ons for Google AI Mode and Gemini range from $9/month on Lite to $149/month on Premium; Claude ranges from $29/month on Lite to $439/month on Premium ^[50]. Enterprise pricing is custom and reported from $1,000/month ^[50].

5. Peec AI

Questions This Section Answers

• Is Peec AI worth it for historical trend tracking, and what are its main drawbacks?
• Can Peec AI backfill historical AI visibility data, and what happens to trend lines if a project is paused?
• Which AI visibility platform for historical trend tracking is best for a brand team tracking a defined prompt library across ChatGPT, Gemini, Perplexity, and Copilot?

Peec AI ranked fifth, named by 4 of 7 platforms at an average listed position of 4.25 and a best position of 2. It runs tracked prompts repeatedly and reports visibility, position, sentiment, share of voice, mention rate, and citation metrics over time ^[58]. Prompt tracking is consistent: the 100 prompts selected in September are the same 100 tracked in December, which the company says makes visibility changes reflect real performance rather than measurement drift ^[59]. Daily collection runs through AI web interfaces using UI scraping rather than official model APIs for most engines ^[61].

Why it ranked here. Peec AI received second-place rankings from deepseek and grok, fourth from openai, and ninth from google. Its average listed position of 4.25 is the second-best in this index after Profound, but it was named by only four platforms, which placed it fifth overall.

Best suited for. Marketing, SEO, and brand teams tracking a defined library of prompts over time; companies comparing AI visibility and competitor movement across ChatGPT, Gemini, Perplexity, Google AI surfaces, and Microsoft Copilot; teams needing citation and source analysis alongside brand mentions and rankings.

Main strengths for the use case. Consistent prompt tracking over time ^[59]. Citation and source reporting including domains and URLs used or cited by AI systems, citation share, source classification, and source-level analysis ^[58]. Competitor benchmarking using visibility, position, sentiment, and share-of-voice comparisons ^[63]. Data available through CSV exports, a Looker Studio connector, an API on higher tiers, and an MCP integration ^[65]. The Actions engine clusters citation sources into owned, editorial, reference, and UGC categories and scores opportunities, and is included on every plan ^[66].

Main limitations. No historical backfill: tracking starts at signup, so buyers cannot benchmark against prior performance or see how visibility trended before paying ^[67]. Pausing a project stops collection, and missed data cannot later be recovered ^[70]. Prompt methodology relies on AI-generated queries rather than real user prompts, which the evidence flags as a distinction that matters for accuracy ^[71]. Citation volatility of 40–60% monthly means trends should be read over 60–90-day windows, which cannot be backfilled ^[72]. No native CRM integration; connecting visibility data to pipeline or revenue requires manual work ^[73]. Self-serve tiers cap tracking at three models, with extra engines as paid add-ons ^[75]. Public materials do not clearly document immutable snapshot retention, historical backfill, retention duration, or whether prior observations can be overwritten after methodology changes ^[58]. .

6. Ahrefs Brand Radar

Questions This Section Answers

• Is Ahrefs Brand Radar worth it for historical trend tracking, and what are its main drawbacks?
• How accurate is Ahrefs Brand Radar for ChatGPT and Perplexity mention counts compared with dedicated AI visibility platforms?
• Which AI visibility platform for historical trend tracking provides pre-collected historical data without waiting for a baseline?

Ahrefs Brand Radar ranked sixth, named by 3 of 7 platforms at an average listed position of 4.67 and a best position of 3. Its distinguishing capability is pre-collected history: Brand Radar reports historical AI responses back to 2025 for the AI Visibility Index, with AI chatbot-source history listed from May 2025 ^[76]. Google reported historical data from August 2024 for Google AI Overviews and May 2025 for AI chatbots ^[77]. The index uses prompts modeled from Ahrefs keyword data, People Also Ask, semantic expansion, and real search demand, with location mirroring its keyword data ^[78].

Why it ranked here. Ahrefs Brand Radar was ranked third by openai and perplexity and eighth by deepseek. It was named by only three platforms, which limited its overall position despite strong fit ratings from openai ("strong") and google and grok ("good").

Best suited for. Enterprise and mid-market teams benchmarking AI visibility across multiple AI search and answer platforms; SEO, AEO, and content teams needing historical competitor, citation, topic, and share-of-voice analysis; companies that value pre-collected historical data and do not want to wait for tracking data to accumulate.

Main strengths for the use case. Pre-collected historical responses reduce the need to establish a baseline before analysis ^[76]. Mentions, citations, AI Share of Voice, impressions, competitors, cited pages, domains, topics, and platform filtering are all supported ^[79]. Combines broad index coverage with custom prompts for exact buyer questions ^[80]. Search-demand-derived prompts can make trend comparisons more market-relevant than purely synthetic prompt sets ^[78]. Reporting and data access run through Report Builder, Looker Studio, API, and MCP where available ^[76].

Main limitations. AI chatbot indexes are refreshed monthly, so the product may miss short-lived changes or provide less timely monitoring than daily systems ^[76]. Historical custom-prompt data starts only after prompts are configured ^[80]. Search-demand-derived coverage can underrepresent low-volume, new, niche, or non-search-driven categories ^[78]. Results are collected from public web versions without stored user context and may not represent logged-in, personalized, enterprise, or API-only experiences ^[76]. Grok collection is temporarily unavailable according to Ahrefs documentation ^[76]. Public materials do not fully establish archival guarantees, immutable snapshots, export retention, or independent accuracy validation ^[76]. Independent testing documented severe accuracy gaps on ChatGPT and Perplexity: one test reported 3 ChatGPT mentions versus 123 actual, and 6 Perplexity mentions versus 212 actual, attributed to snapshot-based keyword methodology rather than real prompt-level tracking ^[81]. Ahrefs pages report different database sizes, including approximately 405M, 454M, 455M, 459M, and 475M prompts ^[78].

Pricing or cost summary. The AI Visibility Index is listed at $199/month per individual AI platform index or $699/month for all platforms, with 2,500 custom-prompt checks per month included in the all-platform bundle ^[85].

7. Wellows

Questions This Section Answers

• Is Wellows worth it for historical trend tracking, and what are its main drawbacks?
• How much does Wellows cost per domain for daily AI citation snapshots, and which AI platforms does it track?
• Which AI visibility platform for historical trend tracking is best for proving before-and-after citation gains on specific prompts?

Wellows ranked seventh, named by 2 of 7 platforms at an average listed position of 4.5 and a best position of 3. Its Citation Performance History feature stores daily snapshots, permits comparison of any two dates, and shows citation score, total citations, tracked prompts, and prompt-level new-versus-lost citation changes ^[87]. The company states that each date is retained as a fixed snapshot captured every 24 hours and that historical comparisons use the captured snapshot rather than reconstructing prior results ^[87]. Google reported that older results are preserved and not overwritten by subsequent updates ^[88].

Why it ranked here. Wellows was ranked third by kimi and sixth by google, and it was named by only those two platforms. Its average listed position of 4.5 is strong, but the two-platform mention count placed it seventh overall.

Best suited for. Marketing, SEO, brand, and agency teams needing defensible before-and-after AI visibility reporting; buyers tracking citation movement and competitors across ChatGPT, Google AI Overviews, Google AI Mode, Perplexity, and Gemini; teams that need prompt-level explanations for changes rather than only aggregate visibility scores.

Main strengths for the use case. Fixed daily snapshots and date-to-date comparisons are directly aligned with historical trend analysis ^[87]. Prompt-level citation diffs help attribute changes to specific prompts and sources ^[87]. Per-platform views address differences among AI answer engines instead of relying only on a blended score ^[89]. Competitor, region, topic, intent, and sentiment filters support segmented trend analysis ^[87]. Export functionality is relevant to recurring client, board, and campaign reporting ^[87]. Every plan includes full access to historical data according to company materials ^[90].

Main limitations. Daily snapshots are not real-time and may not capture intra-day volatility ^[91]. Historical retention length, snapshot immutability controls, audit logs, and data correction policies are not publicly specified ^[87]. The product measures observed AI answers and citations; it does not establish actual prompt volume or guarantee recommendation inclusion ^[87]. Public pricing and plan names conflict across Wellows pages ^[92]. Coverage is limited to the five platforms publicly listed unless Wellows confirms additional coverage ^[89]. Company-published feature claims were not independently validated in the reviewed sources ^[87]. Wellows does not provide prompt volume data, making it harder to know whether tracked prompts have meaningful audience demand ^[93]. Per-domain pricing scales linearly: managing five domains on the Starter tier costs $1,485/month with no publicly documented volume discount ^[94].

Pricing or cost summary. The current pricing page lists Lite at $37 per domain/month, Essential at $97 per domain/month, Starter at $297 per domain/month, and Pro at $497 per domain/month, with a 7-day trial ^[92].

8. Maya

Questions This Section Answers

• Is Maya worth it for historical trend tracking, and what are its main drawbacks?
• How long does Maya retain historical AI visibility data, and does it backfill history for newly added AI engines?
• Which AI visibility platform for historical trend tracking is best for a team that needs weekly snapshots and multi-language query execution?

Maya ranked eighth, named by 2 of 7 platforms at an average listed position of 5.5 and a best position of 3. It states that it records responses to monitored prompts and supports retrospective examination of a past observation together with the question, platform, date, answer passage, and source links ^[96]. Anthropic reported that Maya retains historical data indefinitely and delivers time series and weekly topic snapshots instead of single-day verdicts ^[97]. The company states it does not backfill invented history when a new AI engine is added, preserving snapshot integrity ^[99].

Why it ranked here. Maya was ranked third by google and eighth by kimi. Its average listed position of 5.5 reflects that split, and its two-platform mention count placed it eighth overall.

Best suited for. Companies establishing a repeatable baseline across selected prompts and AI platforms; teams comparing brand mentions, citations, sentiment, share of voice, and competitors over recurring runs; enterprise buyers needing broad platform coverage, higher scan frequency, API access, reporting, and custom support.

Main strengths for the use case. Designed around recurring monitored prompts, model comparison, answer-level evidence, citations, and competitor visibility ^[96]. Methodology explicitly addresses retrospective traceability and comparison of historical observations ^[100]. Enterprise plan is publicly positioned for broad platform coverage, higher scan frequency, competitor tracking, topic visibility trends, API access, and custom reporting ^[101]. Daily query execution across 7+ platforms captures real-world AI response volatility without manual intervention ^[102]. Multi-language query execution runs queries in the language buyers actually use rather than translated English prompts ^[103]. Competitor tracking is included on every plan according to company materials ^[105].

Main limitations. Historical retention duration and immutable, non-overwriting snapshot guarantees are not publicly specified beyond company statements ^[96]. Trend validity depends on stable prompts, platforms, markets, languages, competitor grouping, denominators, and collection conditions ^[100]. Selected prompt monitoring is not equivalent to measuring all real-user AI searches or recommendations ^[100]. Public pricing and plan tables contain an internal platform-count inconsistency: one section says Premium supports four AI platforms of choice, while the comparison text says Premium supports two ^[101]. Model-version, personalization, sampling, and failed-response handling may limit reproducibility unless documented in the customer workspace or contract ^[100]. Kimi could not access the official website or verify any product claims ^[106]. Deepseek found no independently verifiable documentation of time-series retention, snapshot immutability, or historical backfill ^[107].

Pricing or cost summary. Public pricing lists Starter at $99/month and Premium at $399/month on monthly billing, with a yearly option displayed as 17% lower and Enterprise custom ^[101]. Starter includes ChatGPT tracking, 1 project, 50 prompt runs/month, 1,500 LLM responses/month, daily scans, citations and source tracking, and weekly email reports ^[101].

What the Cross-Platform Study Reveals About This Market

Questions This Section Answers

• What does the cross-platform AI consensus reveal about which AI visibility platforms are best for historical trend tracking?
• Why do AI platforms disagree about historical retention and snapshot immutability in AI visibility tools?

Three patterns define this market as the seven platforms described it. First, historical depth is the primary differentiator and the least documented attribute. Only Profound (18 months, anthropic-reported) and Scrunch (12 months, anthropic-reported) carried specific retention figures from any platform ^[108]. Every other entity's retention was either unstated, described as indefinite without technical specification, or contradicted across sources. Buyers asking "how far back does the data go" received a different answer depending on which platform they asked.

Second, the market splits into two architectures. Prospective trackers (OtterlyAI, Peec AI, and to a lesser degree Maya) begin collecting at setup and cannot reconstruct prior visibility ^[110]. Pre-collected trackers (Ahrefs Brand Radar, and Profound's pre-indexed prompt volumes) offer immediate historical lookups without a cold start ^[112]. This distinction matters more than feature lists for buyers who need to analyze trends that predate their purchase.

Third, snapshot immutability is asserted more often than it is documented. Wellows states that each date is retained as a fixed snapshot ^[114]. Maya states it does not backfill invented history ^[115]. Profound describes cumulative historical snapshots not overwritten by newer results in company materials ^[108]. In each case, the claim originates from company-owned sources, and independent verification was not located.

Where the AI Platforms Agreed

Questions This Section Answers

• Which AI visibility platforms do ChatGPT, Claude, Gemini, Grok, Perplexity, Kimi, and Google all agree are strong for historical trend tracking?

Profound is the only entity named by six of seven platforms, and it received first-place rankings from five of them ^[116]. No platform disputed its relevance to the use case; disagreements concerned verification depth, not fit.

All platforms that assessed the category agreed that daily or recurring prompt execution is the foundation of trend tracking. Profound, Scrunch, Semrush, OtterlyAI, Peec AI, Ahrefs Brand Radar, Wellows, and Maya all describe recurring prompt runs as the mechanism that produces trend data ^[118].

Platforms also agreed that citation tracking is a core historical metric, not a secondary feature. Every ranked entity reports cited URLs or source domains as part of its trend surface ^[126].

A third area of agreement: AI visibility measurement is an immature category without a universal standard. Anthropic reported that AI visibility lacks a universal standard matching traditional keyword rank tracking, and that Profound is designed for trend analysis and strategic intelligence rather than a single-number score ^[129]. That framing applies across the index.

Where the AI Platforms Disagreed

Questions This Section Answers

• Why did some AI platforms rate the same AI visibility tool as strong while others rated it uncertain or weak?
• Which AI visibility platform for historical trend tracking has disputed accuracy or disputed pricing across platforms?

Fit ratings diverged sharply for most entities. Profound ranged from "strong" (google) to "uncertain" (kimi) ^[131]. Scrunch ranged from "strong" (google, grok) to "uncertain" (deepseek, kimi) ^[133]. Semrush ranged from "good" (openai, anthropic, google) to "weak" (deepseek) ^[135]. Peec AI ranged from "strong" (grok) to "weak" (deepseek) ^[137]. Ahrefs Brand Radar ranged from "strong" (openai) to "weak" (kimi) ^[139]. Wellows and Maya both ranged from "strong" (google) to "uncertain" (kimi) ^[141].

The most consequential disagreement concerns accuracy. Independent testing cited by anthropic documented Ahrefs Brand Radar reporting 3 ChatGPT mentions versus 123 actual and 6 Perplexity mentions versus 212 actual, attributed to snapshot-based keyword methodology ^[145]. Openai and google rated the same product strong or good for historical coverage ^[139]. Buyers should read these as different evaluation lenses: coverage breadth versus measurement precision.

Pricing disagreements are pervasive. Semrush AI Visibility Toolkit pricing was reported at $99/month by openai and anthropic, with anthropic adding Semrush One bundles at $199–$549/month and a 10-domain agency estimate of roughly $1,090/month ^[150].

How Buyers Should Choose

Questions This Section Answers

• What should a buyer check before choosing an AI visibility platform for historical trend tracking?
• Which AI visibility platform for historical trend tracking has the lowest published cost, and what fees apply?

Start with the retention question, not the feature list. Ask each vendor for the exact number of months or years retained per prompt, platform, competitor, and citation, and whether prior AI responses are stored as immutable, timestamped raw snapshots or only as aggregated metrics ^[152]. Profound and Scrunch are the only entities in this index with platform-reported retention figures, and both require verification in the contract ^[154].

Second, determine whether you need backfill. If your analysis requires visibility history from before your purchase date, prospective-only trackers (OtterlyAI, Peec AI) cannot deliver it ^[156]. Pre-collected options (Ahrefs Brand Radar) can, but with documented accuracy tradeoffs on some platforms ^[158].

Third, match platform coverage to your actual answer surfaces. Semrush Prompt Tracking covers ChatGPT Search, Google AI Mode, and Gemini, with Perplexity coverage contested ^[160]. Wellows covers five platforms and excludes Claude, Grok, DeepSeek, and Copilot ^[162]. Ahrefs Brand Radar covers six core indexes with Grok temporarily unavailable and Claude only in custom prompts ^[163].

Fourth, model total cost including add-ons. OtterlyAI's base plans exclude Google AI Mode, Gemini, and Claude, which are paid add-ons ranging from $9 to $439/month depending on tier ^[164]. Peec AI caps self-serve tiers at three models with per-model add-ons ^[165].

Methodology

This index was produced from a single standardized prompt sent once to each of 7 included platforms on 2026-09-19: openai, anthropic, deepseek, grok, perplexity, kimi, and google. The prompt asked which AI visibility platforms would be recommended for historical trend tracking, covering historical recommendation data, citation trends, competitor movement, prompt-level changes, platform differences, and reliable snapshots not overwritten by newer results.

Platforms named 35 unique entities. Entities named by at least two platforms qualified for the final ranking, producing 8 qualifying entities. The ranking order is determined by platform mentions first, then average listed position, then best listed position. The final ranking table is the sole authority for rank, platform mentions, platform share, average rank, and best rank.

Each qualifying entity was then evaluated for fit against the use case. Fit assessments, feature claims, pricing, strengths, limitations, and disagreements come from the entity evidence bundles, which draw on platform-reported citations. Citations are platform-reported evidence, not independently verified facts. Company-owned sources are distinguished from independent sources where the evidence bundles provide that information.

Methodology Limitations

• One standardized prompt was sent once to each included platform. AI answers can vary by date, wording, location, account state, model, interface, browsing configuration, and the sources retrieved. Repeating this study could produce different rankings.
• Platform mentions count only ranking-discovery mentions. All 7 included platforms evaluated fit, but only platforms that named an entity during ranking discovery contribute to its mention count.
• Platform-reported research dates differ from the authoritative run date of 2026-09-19. Deepseek responses carried dates of 2026-06-15, 2026-06-18, 2026-01-15, and 2026-06-12 across different entity bundles; anthropic carried 2026-01-15 for Scrunch. These are provenance metadata and do not independently prove freshness.
• The supplied URLs were collected from platform responses and were not independently validated by the writer stage. Several official-site retrievals failed or returned unrelated content, including Profound's legacy URL, Scrunch's pricing page, Peec AI's oversized homepage, and Ahrefs' pricing pages.
• Company-owned citations materially outnumber independent citations for several entities, including Scrunch, OtterlyAI, Wellows, and Maya. Company claims are not described here as independently verified.
• Pricing, plan names, platform coverage, and retention windows conflict across sources for most entities. Conflicts are described rather than resolved, and buyers should verify current terms directly.
• The deterministic identity audit noted that official-site retrieval failed for one or more mentions of Profound, Scrunch, and Peec AI, and that company-name variants were collapsed onto one canonical brand before minimum-mentions qualification.
• Platform recommendations are market intelligence, not independent customer reviews or proof of product quality.

Final Verdict

Profound is the consensus leader for AI visibility platforms focused on historical trend tracking, named by 6 of 7 platforms at an average listed position of 1.5. Its platform-reported 18-month retention with daily granularity for the most recent 6 months is the deepest documented window in this index, and its daily prompt-level collection, citation tracking, and competitor benchmarking map directly to the use case ^[166]. The caveat is verification: retention, immutability, and export terms are not independently documented, and pricing is quote-based ^[167].

Scrunch is the strongest alternative for buyers who need citation-level date-range analysis with an API path, within a reported 12-month window ^[169]. Semrush is the pragmatic choice for teams already inside its SEO suite, accepting a 25-prompt cap on the standalone tier and contested Perplexity coverage ^[171]. OtterlyAI offers the lowest published entry price with daily prompt monitoring, but only prospectively ^[173]. Peec AI delivers consistent prompt tracking and citation analysis but no backfill ^[175]. Ahrefs Brand Radar provides pre-collected history back to 2025 with documented accuracy gaps on ChatGPT and Perplexity ^[177]. Wellows offers daily fixed snapshots with any-two-date comparison on five platforms ^[179]. Maya offers time series and weekly snapshots with retrospective answer-level review, with pricing and retention requiring verification ^[180].

No entity in this index should be purchased on the strength of its ranking alone.