Observed Signal · May 27, 2026 · Product Launch · Source: Hello Partner · Impact: 3/5 · Sentiment: Positive
Tradedoubler Launches Emna.ai for AI Search Visibility
Tradedoubler has launched Emna.ai, a platform that measures and helps improve brand visibility within large language model (LLM) search and generative-AI answers. Emna.ai connects to major LLMs to calculate a brand’s AI share of voice, identify cited domains, articles and publishers, surface content gaps, and attribute which assets influence AI answers. Unlike pure SaaS insights tools, Tradedoubler positions Emna.ai as a campaign tool that combines measurement with execution — generating content, activating publishers and tracking impact over time. Early results cited include a skincare GEO campaign that increased a client's AI visibility from under 5% to 30% in under two weeks and moved the brand into the top five in France.
Introduces a measurement+activation product addressing the industry shift toward LLM-led search and GEO; relevant to brands, publishers and affiliate ecosystems but not a major-platform policy or industry-wide structural change.
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Key Takeaways & Evidence Grounding
- Tradedoubler launched Emna.ai to help brands understand and improve how they appear in LLM-generated answers.
- Emna.ai connects to major LLMs, calculates AI share of voice, identifies cited domains/articles/publishers, and breaks down drivers of visibility.
- The product combines measurement with execution: it can generate content, activate publisher campaigns and track daily impact aligned to brand prompts and goals.
- Tradedoubler reported an early GEO campaign in skincare increased a client's AI visibility from under 5% to 30% in less than two weeks and moved the brand to #4 in France.
- The launch is framed as relevant to brands and publishers adapting to a zero-click, LLM-led discovery shift.
Connected Companies & Entities
6 Entities mappedOntology Mapping & Concepts
Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
Publishers Monetize AI Visibility in LLMs
Publishers are packaging a new performance metric—AI visibility in large language models—into commercial offerings for brands, pitching GEO (Generative Engine Optimization) products that aim to improve how often brands are surfaced and cited in AI answer engines. Major and regional publishers (Axios, Forbes, Time, The Washington Post, German media houses) are exploring measurement and monetization strategies, but analytics methodologies vary widely and lack standardization. Some publishers use proxies such as AI bot traffic; others buy third-party measurement. Agencies and brands are rethinking visibility metrics as AI chat interfaces become part of the discovery journey. Incidental data points: many publishers block AI crawlers, AI-driven traffic grew rapidly in 2025, and publisher coalitions and tooling (e.g., SPUR, Profound) are emerging to track AI usage and citations.
Sprinklr Launches LLM Insights for Brand Visibility
Sprinklr announced LLM Insights, a new AI-native capability within Sprinklr Insights that helps enterprises measure, benchmark and influence how their brands are represented in AI-generated answers from large language models. The solution provides real-time analysis of brand visibility, sentiment, recommendations and competitive positioning across LLM-driven queries, and links visibility signals to downstream metrics such as traffic and conversions. Sprinklr says LLM Insights generates prompts from real customer conversations across its unified platform (social, reviews, communities, care), connects insights to content/knowledge/engagement workflows, and is activated within the existing Sprinklr Insights environment. Karthik Suri, Sprinklr Chief Product and Corporate Strategy Officer, framed the product as a way for brands to detect and correct misrepresentations in generative AI results.
Boost Your Brand's Visibility in AI Search Today!
In a recent AdExchanger Talks episode, Tracy Morrissey, SVP of Media & Performance at Innocean USA, explains how brands can gain visibility in AI-generated search. She warns that you cannot simply bid your way to the top of large-language models; success hinges on creating content that directly answers real questions and on understanding how prompts indicate user intent. Brands should publish information on trusted sources—Wikipedia, retailer sites, and a brand’s own site—and verify origins by tracing sources used by AI. The episode notes firms that measure how often brands appear in AI search results, including Profound, Bluefish, and Semrush; it also notes Semrush was acquired by Adobe for $1.9B a week after recording. Morrissey discusses AI tool fragmentation, the need for better orchestration, the enduring value of human guidance in media planning, and a personal note about how dog training influenced her leadership.
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