Ecommerce Data Scraping Services

Collecting publicly accessible information is generally lawful in most jurisdictions, and courts in several have declined to treat access to public web pages as unauthorised access. But the honest answer is that it depends on what you collect, where you and the source are, and what you do with it — and we are not lawyers.

What we control is the part that determines your exposure. We collect only publicly accessible pages: no logins, no paywalls, no credentialed sessions, no personal data resale, no licensed third-party content. Every engagement comes with a written methodology document so your counsel can review the actual practice rather than a marketing claim, and a DPA is available before signature.

By being low-impact rather than by being aggressive. Sustainable collection means realistic request patterns, sensible concurrency, proper session handling and rendering only where a page genuinely requires it. Sites that are hammered eventually become inaccessible to everyone, including us, so restraint is self-interest as much as ethics.

Where a source is genuinely not viable at the frequency you want, we tell you during scoping and propose an achievable cadence instead. That conversation is uncomfortable but it is the right one — the alternative is accepting the work and quietly under-delivering, which you would discover in month three.

Yes. A growing share of price, stock and seller data loads client-side after initial page render, sometimes through internal endpoints with rotating parameters. We render where rendering is required and use the documented response structure where one is exposed.

The practical implication is cost: rendered collection is substantially more expensive per page than static fetching, so we render selectively rather than universally. During scoping we identify which sources and which field groups actually need it, which usually keeps the rendered share of your volume small.

Field-dependent, and that distinction matters. Price and stock can run every 15 minutes on priority SKUs at priority retailers. Full-catalogue sweeps across thousands of sources are daily. Product content and attributes change slowly enough that weekly is usually right. Reviews are typically daily.

We set cadence per source and per field group rather than applying one blanket frequency, because a single high frequency across everything wastes most of its cost on fields that did not change. Every record carries an observed_at timestamp so you can measure freshness directly rather than trusting our description of it.

Above 0.95 confidence on SKUs with verified GTIN or MPN, and lower on long-tail listings where identifiers are absent and titles are pure marketing copy. Rather than publishing a single accuracy figure, we deliver a match_confidence score on every record and let you set the threshold.

Pricing teams typically use 0.95 or above because a wrong match costs margin directly. Market research use cases often accept 0.85 to keep coverage broad. Records below your threshold arrive flagged rather than deleted, so you can always see what was excluded and why. Pack size and variant are treated as hard constraints, which prevents the classic 6-pack versus 12-pack error.

Both, with an important caveat. For many major retailers and popular categories we hold history and can backfill from our archive. For sources or SKUs we have not previously collected, history does not exist and no vendor can honestly conjure it.

We tell you exactly which parts of your requested scope have backfill available and which start from first collection, before you sign. Anyone offering complete historical coverage on an arbitrary source list is either estimating or reselling something with undisclosed provenance.

Either, and clients often use both. Files — JSON, JSONL, CSV or Parquet — land in S3, GCS, Azure Blob, SFTP, Snowflake, BigQuery or Databricks on your schedule, which suits warehouse and analytics use. An authenticated REST API suits applications that need on-demand access, with rate limits agreed to your load profile and a sandbox key for integration testing.

Schemas are versioned either way, with deprecation notice before any breaking change. A schema change that surprises your pipeline is an outage you did not cause, and we treat it that way.

We detect it and fix it, usually before you notice. Monitoring watches output distributions rather than just HTTP status codes, because the dangerous failure is a page returning 200 with a null price. A sudden shift in fill rate or price distribution triggers investigation.

Standard sources are triaged the same business day; sources you designate critical are inside four hours. If a fix will take longer, you are told rather than left to discover a gap. Maintenance is inside the retainer — layout changes are not billed as change requests, because that would make our incentives the opposite of yours.

We quote individually, because a real number depends on four things: how many sources, how many products, how often, and whether any of it needs rendered collection. Anyone quoting you before knowing those is guessing, and the guess is usually revised upward later.

What drives cost most is frequency multiplied by rendered share — not record count, which is what most buyers expect. A large catalogue collected daily from static pages can cost less than a small one collected every fifteen minutes from rendered ones.

The process is short: one scoping call, a free pilot on your own sources within 24 hours, then a fixed monthly quote. No per-request metering, no overage billing, and added sources or fields are handled inside the retainer rather than re-quoted. Request a quote.