Promotions & Offers Data Scraping Services

Two ways. First, our schema covers nine normalised mechanics that between them account for the large majority of retail promotional activity. Second, anything that doesn't map cleanly is delivered with the mechanic marked as other, the original headline text preserved verbatim, and a parse confidence score attached.

We never force an ambiguous offer into a category to make the data look tidier. Novel mechanics that recur are added to the schema as a versioned extension, announced before release.

Yes, and this is where continuous capture matters most. Many retailers publish no end date at all, or publish one and then extend it. We record first-seen and last-seen timestamps independently of any published dates, using stable offer IDs that persist across runs.

The practical consequence: true duration is only available from the point collection starts. It cannot be reconstructed retrospectively for offers that have already ended. If promotional duration matters to your analysis, starting collection earlier is strictly better.

Loyalty pricing displayed publicly on product pages — Tesco Clubcard prices, Kroger digital coupon prices, Target Circle offers — is captured as standard, including the member versus non-member gap as a computed field.

Offers visible only after authentication are a different matter: we do not create accounts or log in to extract data. For app-push and email promotional capture, we operate through a consented panel arrangement rather than account access, and we scope that explicitly with you because it carries different commercial terms.

Higher than pricing, generally, because promotional windows are short. Our recommendation: hourly for flash sales, marketplace lightning deals and any retailer running same-day events; 4-hourly for mass and electronics; daily for grocery, where campaigns typically run in weekly cycles.

The cost of under-sampling is asymmetric. A missed price point can be interpolated; a missed 6-hour flash sale is simply absent from your data forever.

The pricing feed answers what does it cost right now. The promotions feed answers what mechanic produced that price, for whom, under what conditions, and for how long. They share SKU and retailer keys and are designed to join.

Most clients start with pricing and add promotions when they discover that shelf price alone can't explain competitor behaviour — particularly in grocery and pharmacy, where loyalty and multibuy mechanics dominate. Running both is what makes effective-price analysis possible.

Yes. Alerting runs on the same pipeline as delivery: when a new offer matching your criteria is first seen, a webhook fires and can route to Slack, Teams, email or your own endpoint. Criteria can be set on retailer, category, mechanic type, depth threshold or specific SKUs.

Clients typically set narrow alert rules — for example, depth above 25% on their top 200 SKUs — and receive the full feed separately for analysis. Alerting on everything produces noise that gets muted within a week.

Limited, and we are direct about this. Promotional pages are poorly archived, and offers vanish without trace once they end. Where our own prior collection covers your target retailers and categories, we can supply history from that archive. Where it doesn't, backfill generally isn't possible.

During scoping we tell you exactly which retailers we already hold promotional history for. For anything else, the honest answer is that the series starts when collection starts.

Currently 98.2% on our validated sample set, measured as correct mechanic classification plus correct extraction of qualifying conditions. Offers scoring below our confidence threshold go to human review before delivery rather than shipping as a guess.

You can verify this directly on the pilot sample: every record includes the original headline text next to the parsed fields, so checking interpretation quality takes an analyst about twenty minutes on a few hundred rows.

We quote every promotional monitoring engagement individually, because a real number depends on scope: source count, record volume, refresh frequency and delivery method. Anyone quoting you a price before understanding those four things is guessing.

Cost is driven mainly by refresh frequency and how many retailer apps are in scope, since app-based offers cost more to collect than web pages.

The process is short: one scoping call, a free pilot on your own sources within 48 hours, then a fixed monthly quote. No per-request metering, no overage billing, and field or source additions are handled inside the retainer rather than re-quoted. Request a quote.