Rankscale GmbH Unclaimed
Vienna, Vienna, Austria
Rankscale helps brands monitor and improve their presence in AI-generated search results across multiple engines.
Rankscale GmbH is a software company that provides AI visibility tracking and analytics. The company helps brands, agencies, and marketing teams monitor how their brands and content appear in AI-generated answers across multiple engines, collect mentions, citations, and sentiment, and aggregate insights in centralized views. The goal is to enable measurement, identification of content opportunities, and evidence-based reporting at scale across regions and languages, with support for multi-brand management, team-based access, and enterprise-grade reporting integrations.
To empower brands and agencies with transparent, data-driven visibility across AI engines, enabling measurement, optimization, and clear reporting of AI-driven brand presence at scale.
What we offer
Rankscale Enterprise AI Visibility Platform
Optimizes brand visibility in AI-driven search across multiple platforms globally.
rankscale.ai/enterprise-ai-visibility-platformAI Citation Tracking
Optimize your content strategy by tracking and analyzing domain citations across AI search engines.
rankscale.ai/features/ai-citation-trackingRankscale MCP
Gain instant insights about your brand's AI search visibility through conversational AI.
rankscale.ai/mcpAd Analytics
Optimize your ad strategy by tracking visibility and competitive presence across AI engines.
rankscale.ai/features/ad-analyticsRankscale API
Unlock visibility metrics programmatically with the Rankscale API for seamless integration.
rankscale.ai/apiGoogle Looker Studio Connector
Easily visualize Rankscale metrics in Google Looker Studio for insightful reporting.
rankscale.ai/integrations/google-looker-studioMarket segments
Market size by segment
Growth potential (CAGR)
AI visibility monitoring
Monitoring brand presence and sentiment within AI-generated content and across large language model outputs to understand and improve representation in AI summaries and overviews.
Citation and content attribution analytics
Identification, tracing, and sentiment analysis of citations and source domains used by AI answers to optimize attribution, content targeting, and domain authority.
AI advertising measurement
Capabilities to plan, launch and measure paid campaigns targeting AI answer surfaces and in-chat placements, unifying visibility and conversion signals across Google Ads, AI overviews and social channels.
Analytics and enterprise governance
Reporting and impact measurement combined with enterprise administration and compliance features such as robust analytics, goals and milestones tracking, security and governance, enterprise panel, branding and white labeling, integrations, and invoicing controls.
Data integration and BI connectivity
API-based and downloadable data pipelines that deliver brand intelligence into BI platforms, MMMs, and marketing dashboards for cross-functional use.
More information about our offering
Rankscale Enterprise AI Visibility Platform
Rankscale’s enterprise AI visibility platform measures and improves how brands appear in AI-generated answers across 17+ engines, with global coverage and multi-brand management. It consolidates brand signals, citations, and sentiment into a single GEO platform and offers enterprise-ready features for teams and agencies, including white-label reporting, role-based access, and scalable monitoring across markets. It also includes functionalities of AI Rank Tracker and Brand Visibility Dashboard.
- Covers All Major AI PlatformsEnsure your brand visibility is monitored across all significant AI search engines to maintain competitive advantage.
- Consolidates Visibility MetricsProvide a clear overview of all brand performance metrics, making it easier to track and report progress over time.
- Facilitates Team CollaborationEmpower your teams to manage multiple brands effectively while controlling access permissions for better collaboration.
- Identify Gaps And OpportunitiesGain insights into competitor performance, enabling informed decisions to enhance your own ranking strategy.
- Streamlines Client ReportingGenerate professional reports that clearly present brand visibility metrics, campaign effectiveness, and insights for strategic decision-making.
- Supports Agile Decision-MakingEmpower teams to pivot strategies quickly based on the latest visibility data and search trends.
- Improves Citation StrategyAssess where your brand is getting recognized in AI responses and adjust your content strategy accordingly.
AI Citation Tracking
AI Citation Tracking identifies and analyzes which domains are cited in AI answers, providing metrics on citation volume, domain leadership, and brand share across AI engines to optimize content strategy.
- Connect Citations EasilyUnderstand the context of your citations and improve your content's relevance by tracking back to original sources.
- Identify Leading DomainsSpot which domains are dominating citation shares, allowing you to adjust your strategies accordingly.
- Gauge Brand PerceptionUnderstand how your brand is perceived in the AI landscape by evaluating sentiments attached to your citations.
Rankscale MCP
Rankscale MCP brings live AI-search visibility data into the assistants your team uses, delivering a read-only connection that reads data from Rankscale and presents it in chat-based interfaces across Claude, ChatGPT, Cursor, and more.
- Connect to AssistantsSeamlessly integrate with Claude, ChatGPT, Cursor, and others to access visibility data directly in chat environments.
- Real-Time InsightsAccess metrics and insights in real-time, making it easier to monitor and act on visibility changes instantly.
- Safe QueriesEnsure that AI assistants can access and summarize data without the ability to alter critical Rankscale settings.
Ad Analytics
Ad Analytics measures sponsored placements in AI shopping answers, tracking ad appearances, share of voice, advertisers, and the effectiveness of creatives across ChatGPT, Google AI Mode, and Copilot.
- Track Ad AppearancesGain visibility into your ads' performance across platforms ensuring no blind spots exist.
- Measure Market ShareAssess your ad visibility in relation to competitors to adjust your strategy.
- Gain Competitor InsightsUnderstand your competitors’ presence and strategize accordingly with detailed insights.
Rankscale API
Rankscale API provides authenticated REST API access to metrics, enabling programmatic access to visibility data, production-grade integration with internal tooling, and shareable live dashboard links.
- Enable Seamless IntegrationsAccess extensive visibility and analytics data programmatically to integrate with your internal systems and workflows.
- Streamline Stakeholder ReportingEasily distribute live views of important metrics to stakeholders without giving full access to accounts.
Google Looker Studio Connector
Google Looker Studio Connector brings Rankscale data into Looker Studio, enabling flexible dashboards and BI-style reporting with Rankscale metrics across AI engines, prompts, and citations.
- Streamline ReportingSeamlessly transfer data into Looker Studio to create tailored visualizations and reports, enhancing decision-making and strategic insights.
- Utilize Diverse Data TypesChoose between different data outputs like overall brand visibility metrics or detailed execution-level data to suit your reporting needs.
- Build Tailored DashboardsUtilize customizable options to design dashboards that fit your reporting requirements, allowing detailed analysis of metrics over time.
References
Methodology and sourcing behind the figures shown above.
AI visibility monitoring
Estimates draw primarily from two search results for the AI visibility / AI search visibility category. Mordor Intelligence reports a market size of USD 4.39B in 2026 with a 19.55% CAGR to 2031; AmICited (industry blog) reports a larger estimate of USD 20.4B in 2024 and a 24.8% CAGR to 2030. Given variance in definitions and timing, I use Mordor’s 2026 market-size figure (conservative, research-report baseline) and its 19.55% CAGR as the primary estimate. A related market report (AI in observability) shows similarly high growth (CAGR ~22.5%), supporting the view of strong multi-year expansion in adjacent AI monitoring markets.
Citation and content attribution analytics
Estimate derived by treating “citation and content attribution analytics” as an early, specialized subsegment of the broader marketing attribution and content-analytics markets. Search results show marketing attribution platforms at roughly USD 3–5.5B (2025–2026) with high growth (CAGR ~14–29%) and content analytics at ~USD 11–13B (2025) with ~18–19% CAGR. Conservatively assuming the niche represents a small portion (≈2–4%) of the combined adjacent markets in 2025–2026 yields an addressable market around USD 0.4–0.6B today; given AI-driven adoption and faster uptake for AI-visibility tools, a higher-than-category CAGR (≈25%) is applied as the growth potential.
- was estimated at USD 4.81 billion in 2025
- projected to grow from USD 3.2 billion in 2025 to USD 41.0 billion by 2035, at a CAGR of 29.1%
- likely to be valued at US$ 5.4 billion in 2026 and is expected to reach US$ 14.5 billion by 2033, growing at a CAGR of 15.2%
- Content Analytics Market size was valued at USD 11.03 billion in 2025
AI advertising measurement
Relevant search results show nascent but rapidly growing ad spend on AI-native surfaces (WPP: generative search $5.1B in 2026 with ~100% five‑year CAGR) and strong growth across adjacent digital/retail media channels (retail media to $90B by 2028 at ~17% CAGR; major platform spends such as TikTok ~$18.5B). Given (a) AI ad surfaces are a small but fast-growing subset of overall digital ad spend, (b) measurement/attribution/verification typically captures a small percentage of ad budgets but commands a premium for specialized AI capabilities, and (c) the broader AI market expansion, a conservative estimate for the global market for AI advertising measurement (planning, execution, and unified measurement across AI answer surfaces, in-chat placements and social/search channels) is ~ $10B today with strong upside. Growth potential is high (estimated CAGR ~35%) reflecting rapid adoption of generative search and AI-native ad channels, while remaining below the extreme CAGR WPP projects for purely generative search ad revenue because measurement monetization scales differently.
- For 2026, WPP Media forecasts that generative search ad revenue will reach $5.1 billion globally
- grow at a compound annual growth rate of nearly 100% over the next five years
- retail media networks... grow at a 17% compound annual rate to $90 billion by 2028
- TikTok Ads reached $18.5 billion in annual spend
- global AI market size is predicted to grow to $1,847.58 billion by 2030
Analytics and enterprise governance
Search results show eGRC/data-governance estimates ranging ~13–55+ billion USD in the early-to-mid 2020s with reported CAGRs ~10.8–14.7%. I used multiple vendor reports (Mordor, Fortune, Polaris, Transparency) and selected a conservative midpoint (~50B) and median CAGR (~12.5%) to reflect the aggregated market for analytics + enterprise governance features.
Data integration and BI connectivity
Estimated segment size derived from published global data integration market values (2025) combined with reported share for the marketing/business-application segment (~26%). Sources show 2025 global market estimates of roughly USD 17–19B; applying the ~26% marketing share yields an addressable market ~USD 4.4–5.0B (rounded to USD 4.8B). CAGR for this marketing/BI connectivity subsegment is estimated at ~12% based on reported overall data-integration CAGRs (≈11.7–13.6%) across multiple research providers.
- The global data integration market size was valued at USD 19.14 billion in 2025.
- Market Size in 2025: USD 17.10 Billion.
- By business application, the marketing segment contributed more than 26% of revenue share in 2025.
- Market expands from USD 17.58 billion in 2025 to USD 33.24 billion by 2030, at a CAGR of 13.6%.
- Data integration software market valued at US$ 6.8 billion in 2026 and projected to reach US$ 16.1 billion by 2033, CAGR 13.1%.
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