Research Methodology
Collect ecommerce, O2O, instant retail, product page, review, social, store, and public market data across brand, SKU, price, and promotion dimensions.
Standardize duplicate links, invalid products, pricing anomalies, and cross-platform field differences to create a comparable data layer.
Map the same item across platforms so price, review, sales, and channel signals can be analyzed on a unified SKU basis.
Use NLP, OCR, classification models, and anomaly detection to turn reviews, screenshots, promotions, and channel changes into structured business signals.
Deliver research reports, alert dashboards, channel scores, trend analysis, and case reviews for market, ecommerce, channel, and product teams.
This methodology supports ecommerce, O2O, instant retail, review analytics, price governance, channel execution, and product innovation. The goal is to make each output traceable to source, rules, and analysis logic.
BXTData prioritizes public or authorized data and does not bypass login, payment, permissions, or technical access controls, or collect unnecessary sensitive personal data.
Completeness checks, validation, deduplication, normalization, anomaly rules, and manual sampling are used with versioned processing rules.
Pages, stock, prices, reviews, and rankings change continuously. Network conditions, page structures, samples, and refresh intervals can create short-term differences.
Monitoring represents the agreed scope and period. It does not replace audited data, statutory statistics, or total market estimates unless explicitly stated.
By combining brand, size, packaging, flavor, barcode, and title signals with rule-based and model-based validation.
Text is cleaned, deduplicated, and filtered before topic detection, sentiment analysis, and negative issue attribution.
Different datasets update daily, weekly, or near real time depending on the source and business scenario.