AI 도구Brandwatch
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Brandwatch
Consumer intelligence from a decade of social conversation
0
저장
Custom
시작 가격
2007
출시
Brandwatch (Cision)
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Brandwatch
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Brandwatch이란?

최종 검증일 May 4, 2026 · AI Tools Set 리서치 팀

Brandwatch is the enterprise standard for social listening: an archive of consumer conversation stretching back to 2010 across social networks, forums, reviews, and news, with AI that turns billions of posts into answers about your brand, market, and customers.

Its Consumer Research product lets analysts query that archive with surgical precision, brand sentiment shifts, emerging trends, campaign impact, crisis signals, with AI-powered Iris summarizing anomalies and drafting insights in plain language. Audience tools profile the communities discussing any topic; the social media management suite handles publishing, engagement, and advertising alongside listening, unified after its merger with Falcon.io. Data depth is the moat: full-archive access and enterprise-grade query language that lighter tools cannot approach.

Who is it for?

Brand, insights, and comms teams at large organizations, agencies running research for clients, and PR functions monitoring reputation at scale. SMBs sampling sentiment have cheaper options.

How much does Brandwatch cost?

Enterprise contracts, custom-priced by data volumes, seats, and modules via demo, a research-infrastructure investment rather than a team tool expense.

Our verdict

For serious consumer intelligence, Brandwatch's archive depth and query power remain best-in-class, and Iris makes that depth accessible beyond analyst specialists. It is priced like the enterprise research platform it is.

Brandwatch의 주요 기능

  • Full-archive listening: Conversation data back to 2010.
  • Iris AI insights: Anomalies explained automatically.
  • Audience profiling: Who is talking, and how.
  • Unified management: Publishing and engagement included.

Brandwatch 활용 사례

  • Track brand sentiment
  • Detect emerging trends
  • Measure campaign impact
  • Monitor crises early
  • Research consumer segments

장점 & 단점

장점
Unmatched data archive
Powerful query language
AI-summarized insights
Full suite breadth
단점
Enterprise pricing
Analyst learning curve

요금제

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Custom
Module licensing
Data volume scoping
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