WebDataGuru

Start by telling us which sites and regions matter to you. Create a project, drop in URLs or categories, choose target locales, and define how often we should collect updates (hourly, daily, or weekly). Add rules for languages, currencies, and units so product names, attributes, and prices are captured consistently across countries. If pages rely on JavaScript or logins, enable browser emulation and credential vaulting; we handle cookies, sessions, and rotating locations. Map products you care about using SKUs, GTINs, or fuzzy matching. Preview sample results, approve the schema, and lock the schedule. From there, new data lands automatically in your chosen destination.

Use the pricing workspace to track rivals and react quickly. Set thresholds and business rules (undercut by 2%, match the lowest within your margin, hold MAP). Turn on real-time alerts when a competitor moves, a product goes out of stock, or a new variant appears. Normalize currencies with live FX and convert package sizes to comparable units. View side-by-side price ladders, promo badges, and shipping fees, then push actions to your pricing engine or storefront. Export fresh snapshots to Google Sheets or Excel for quick reviews, or pipe them to Snowflake, BigQuery, S3, or your data warehouse via API or webhook.

Go beyond prices to understand the shelf. Audit product content at scale - titles, images, specs, ratings - and flag gaps against your content standards. Track assortment coverage by category and retailer to spot missing listings or exclusives. Monitor stock status, delivery promises, and buy-box changes to assess execution. Schedule weekly briefs for category managers, or build custom dashboards that trend share of shelf, promotional intensity, and new item launches. Feed these insights into campaign planning, negotiation prep, and range reviews.

Data quality is built into every run. Each feed passes schema checks, deduplication, outlier detection, and link health validation; ambiguous records are queued for analyst review. Versioned histories let you roll back, compare time periods, and model seasonality. Work in your tools: fetch JSON or CSV, write to Parquet, or query via REST. Use our Python snippets to join extracted data with your sales and inventory, then publish a single source of truth. For multilingual markets, apply locale-aware extraction and automated translation so teams can collaborate on the same dashboard. Start small with a pilot, tune the match rules, and scale to thousands of URLs without changing your workflow.