Brand mention tracking with sentiment on every row
The Brand Mentions & Sentiment dataset gathers public mentions of your brand across news, blogs, review sites, and forums into a structured table, scores each one for sentiment, and refreshes on the schedule you set so you see shifts in perception as they happen.
Why work with Brand Mentions?
One table, every channel
News, blogs, reviews, and forum posts land in a single view instead of a dozen separate tools.
Sentiment scored for you
AI operations classify tone and assign a score so you can sort for the mentions that matter most.
Catch swings early
Change detection and scheduled refreshes surface spikes in negative coverage before they escalate.
Powering Brand Mentions
AI-powered web gathering
Describe a column or dataset and ClickSet backfills it from public web sources, with no scraper scripts to maintain.
AI operations
Score, classify, extract, summarize, cluster, or detect anomalies and sentiment across rows.
Change detection
Monitor sources and log diffs into versioned tables.
Scheduled refresh
Hourly, daily, or weekly re-runs that keep data current.
API access
Every dataset is a live REST endpoint with per-key spend caps.
Who uses this?
You might also work with
People News
Marketing & Communications
Company News
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Industry News
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Local News
Marketing & Communications
National News
Marketing & Communications
World News
Marketing & Communications
Industry Trends
Marketing & Communications
Technology Trends
Marketing & Communications
Political Trends
Marketing & Communications
Hiring Trends
Marketing & Communications
Employer Reviews
Marketing & Communications
Industry Conferences
Marketing & Communications
Frequently asked questions
Where do mentions come from? +
Public news sites, blogs, review platforms, and forums, gathered in research mode with a source link on every row.
How is sentiment scored? +
Each mention is classified as positive, neutral, or negative and given a numeric score from -1 to 1 so you can filter and trend it.
Can I track competitors too? +
Yes. Add rival brands or products and they become rows in the same table, so you can compare share of voice and tone.
Further reading
See how ClickSet handles your data workload
Describe the dataset you need, enrich it with hundreds of LLMs, and query the result through one API. Start on the free plan.