Opinion intelligence

Sentiment Analysis Services

Convert unstructured feedback into clear signals with multilingual sentiment scoring, topic clustering, trend detection, and entity-level analysis.

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Core capabilities

  • Multilingual models
  • Topic clustering
  • Trend scoring

Clearer customer voice analytics

Designed for dependable delivery, validated fields, and business-ready reporting.

Faster reputation monitoring

Designed for dependable delivery, validated fields, and business-ready reporting.

Better product and market feedback loops

Designed for dependable delivery, validated fields, and business-ready reporting.

Workflow

Built for production data operations

CrawlXpert handles source analysis, extraction design, data validation, delivery, and monitoring so your team can focus on decisions instead of scraper maintenance.

Source mapping

Targets, fields, locations, cadence, and edge cases are documented before build.

Pipeline build

Extraction, retries, parsing, validation, and delivery are configured for your use case.

Monitoring

Jobs are watched for quality, freshness, volume, source changes, and delivery health.

Governance

The pipeline is structured around controlled access, auditability, and compliant data handling.

Use cases

Where sentiment analysis fits

Review intelligence
Brand reputation tracking
Social and news sentiment reporting

Related services

Combine this service with adjacent CrawlXpert capabilities when your data workflow spans web, app, and analytics requirements.

Live Crawling Service

Real-time crawl fleets that monitor millions of URLs and stream changes the moment they happen.

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Mobile App Scraping Services

Capture pricing, catalogs, and reviews from iOS and Android apps that have no public web surface.

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Web Scraping APIs

Production-grade scraping APIs for any site at scale, with auto-rotating infrastructure and structured output.

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Ready to scope sentiment analysis?

Share your sources, fields, target volume, and refresh needs. CrawlXpert will turn it into a clear extraction plan.

Analyze sentiment

Questions, answered

Frequently Asked Questions

Can't find what you're looking for? Our data engineers are one message away.

Contact Our Engineers
Sentiment analysis uses AI/NLP to determine whether text data (reviews, social media, feedback) expresses positive, negative, or neutral sentiment.
Product reviews, social media posts, customer feedback forms, news articles, and any text-based data source.
Accuracy depends on the model and data quality, but modern NLP-based sentiment analysis typically achieves high accuracy for clear positive/negative expressions.
To track brand perception, identify customer pain points, monitor competitor reputation, and inform product or marketing decisions.