Real consumer signals. Vertical AI for marketing
Sensia structures the consumer signals that matter for your scope, then enriches them with AI built for brand, claim, audience, and category work — not generic summarization.
Consumer signals
A focused, controlled set of consumer signals — reviews, social, retailer feedback, internal materials when relevant — structured around your scope.
Amanda Smith
FOUNDER, CEO & EXECUTIVE CHAIRMAN
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Vertical AI
Models built for marketing and consumer work. They surface needs, frictions, claims, narratives, emotions, and risks in business language — not generic summaries.
The signals that actually shape consumer decisions.
Within your configured scope — not “all the internet.”
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Reviews and retailer ecosystems Product reviews, retailer comments, Q&A, and verified-buyer language across configured retail environments.
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Social conversations and creator content Posts, comment threads, and creator content within your configured platforms and topics
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Forums, communities, and comment sections Long-form discussions where consumers explain reasoning, doubts, and trade-offs.
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Internal files and studies Past studies, briefs, claim guidelines, and CRM extracts when you choose to include them.
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Competitor and category context Competitor product pages, claims, and category language within the scope you define.
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Cross-market and multilingual analysis Compare how consumers express the same need across markets and languages within your configured scope
Supported Data Streams and Connectors
Sensia natively supports structured and unstructured data from leading platforms, with seamless integration into your research workflow.
Built on broad consumer coverage, focused by your scope.
Sensia does not start from “all the internet.” It structures the consumer signals that matter for your question, market and sources.
100B+
online reviews and consumer signals available
100+
countries covered
100+
languages supported for AI analysis
See vertical AI on your category?
Bring a category, an audience, a claim, or a campaign. We’ll show you the consumer signals Sensia would structure, the enrichment it would run, and the Guided Output that would come out of it