ETS Viewer

ETS Viewer helps SEO analysts compare ETS metrics across domains with fast filtering and exportable data views for audits and benchmarking.

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About This Tool

ETS Viewer ingests ETS data and exposes time-series and categorical metrics in ready-to-analyze formats. It enables domain-level comparisons, validation checks, and reproducible reporting without heavy dashboards. Users can load data from ETS APIs or local files, apply filters, select a time window, and view multi-metric summaries in a single workspace. Conceptually, the tool normalizes input schemas, aggregates metrics, and renders structured outputs that can be exported for sharing. It is designed for SEO teams, data engineers, and product managers who require repeatable analyses and quick insight cycles. Unique differentiators include flexible data ingestion, explicit validation, and the ability to merge multiple ETS sources for cross-domain benchmarking. Core features cover time-based aggregations, percentile calculations, delta and rank comparisons, and export-ready summaries. Use cases include weekly domain health checks, campaign performance validation, and competitive benchmarking with auditable results. The tool emphasizes data integrity, reproducibility, and lightweight integration with existing analytics stacks, making it suitable for teams that need transparent, auditable ETS insights without building full-scale dashboards.

How to Use

Provide inputs: data_source, dataset_id, time_range_start, time_range_end, metrics, filters
Choose metrics and filters to focus analysis
Run ingestion to load data and compute metrics
Review outputs: view_json, summary_metrics, chart_data
Export results as CSV or JSON for reports
Save configuration for scheduled refreshes

How to use ets viewer

Frequently Asked Questions

Find Quick Answers

What data sources are supported?
ETS Viewer supports ETS API endpoints and file imports in JSON or CSV. It validates schema compatibility and maps fields automatically to standard metrics, enabling quick ingestion and consistent calculations.
How are metrics calculated and compared?
Metrics are computed per time bucket with user-selected aggregations (sum, avg, min, max, percentile). Delta and rank comparisons are computed against a chosen baseline dataset or time window to show relative performance.
Is data handled securely and privately?
Data processing can occur client-side or server-side depending on deployment. ETS Viewer follows typical data protection practices, avoids data retention beyond exports unless configured, and ensures restricted access to sensitive datasets.

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