Collect the right public data
We collect relevant data from social media, news, public documents, e-commerce, and market sources based on your monitoring scope.
01Data scraping with contextual understanding.
AA Scraper collects publicly available data, enriches every record with contextual tags, and delivers analysis-ready insight, so your team can measure meaning, not just volume.
Multi-source collection
Custom tag logic
Traceable outputs
To structured insightWith contextual depth
From public data
Selected teams already working with AA Scraper
Built for analysts and researchers
Everything you need to turn public data into decisions.
One managed service covers collection, contextual understanding, and analysis-ready delivery.
Understand what it means
Each record is classified by topic, sentiment, stakeholder, message, competitor, and the custom criteria your team actually uses.
02Receive insight you can use
Get structured datasets, traceable records, dashboards, trends, and summaries ready for research, reporting, and decisions.
03 The foundation of good analysis
Good analysis starts with well-classified data.
Collecting more data is not enough. Every record needs a defined label before it can reveal a useful pattern.
Contextual tagging
A tag system designed around your specific needs.
We translate your monitoring framework into a custom tag library, then apply it consistently across every collected record.
- Combine direct text fields with context-based interpretation
- Build custom hierarchies for your domain
- Apply complex criteria across large datasets
- Filter, group, compare, and export any combination
Textual tagContextual tag
BrandTextual tag
NikeAdidasASICSNew Balance
Brand mentionedTextual tag
YesNo
Content formatTextual tag
News articleSocial postVideo adReport
IdeologyContextual tag
Social democraticMarket liberalConservative
InterestContextual tag
Performance runningSustainable productsPremium sportswear
Market movement contextContextual tag
Event-drivenSector-ledMarket-wide
FavorabilityContextual tag
FavorableMixedUnfavorable
Purchase intentContextual tag
ExploringComparingReady to buy
Cultural valueContextual tag
AchievementIndividual agencyCommunity belonging
Context in practice
See how contextual tagging turns raw data into specific findings.
Context can be implied by language or revealed through relationships across datasets. These examples show what becomes visible when records are interpreted together.
01 Source record
02 Context labels
03 Contextual finding
The copy expresses Nike’s action-first brand code without naming Nike or repeating “Just Do It.”
From raw data to insight
From question to insight.
You define what matters. We handle collection, classification, infrastructure, and delivery.
- 01
Scrape public data
Collect relevant posts, reviews, articles, market data, and public documents.
- 02
Build the tag hierarchy
Define the layers of context and nuance that keyword rules usually miss.
- 03
Classify by context
Apply contextual labels, confidence, and source traceability to every record.
- 04
Generate insight
Turn structured data into trends, signals, summaries, and findings.
Output examples
Go from “what was mentioned?” to “what does it mean?”
Contextual tags unlock specific narrative summaries, precise counts, and transparent evidence behind every finding.
EXECUTIVE SUMMARY
Signals that shaped the conversation
Tagged records14,820+12.6%
Positive sentiment62%+8.2%
Priority signals23Review
Context volumeLast 30 days
Notable contextLive
A competitor launch is gaining traction among price-sensitive consumers.
Threat signalCompetitor
AI-grounded summaryTraceable
The narrative moved from product features to proof of everyday performance.
Every statement is grounded in tagged source records and remains available for verification.
Fully tagged records98.4% tagged
Launch conversation accelerates…Growth
Price remains a key objection…Risk
Community story earns trust…Advocacy
Built around public data
Built around the questions your team needs to answer.
Choose a starting point. The sources, taxonomy, and output are configured around your workflow.
Brand and media intelligence
Track coverage, public conversations, sentiment, key messages, and reputation signals.
Market and competitor intelligence
Monitor product launches, pricing, competitor activity, demand, and emerging risks.
Research and policy monitoring
Structure public documents, government publications, market data, and policy debates.
Articles and explainers
Understand the ideas behind contextual data.
Short, structured guides to meaning, language models, inference, and data labeling.
Frequently asked
FAQ
The essentials about scope, customization, outputs, and traceability.
Ask a different questionStandard scraping stops at collection. AA Scraper adds a custom contextual taxonomy, ML-assisted classification, source traceability, and outputs ready for analysis.
Yes. The hierarchy can reflect your brands, topics, stakeholders, key messages, risks, narratives, or other domain-specific criteria.
Typical outputs include structured datasets, fully tagged records, interactive dashboards, monitoring reports, trend maps, summaries, and notable-signal alerts.
Yes. Source provenance is preserved so analysts can inspect, audit, verify, and cite the evidence behind a result.
Start with your question
Turn the public data around your market into intelligence your team can act on.
Tell us the question you need to answer. We’ll map the right sources, contextual logic, and output.