Editorial & data policy

Independence

DealComparer's rankings, comparison pages, and editorial content are independent from the retailers, brands, and affiliate networks we work with. Specifically:

• No retailer can buy higher placement. Our ranking algorithm is public-by-description (live price, retailer coverage, multi-offer density, freshness) and we do not accept payment to alter it.
• No paid "featured" product slots. The products that appear on the homepage and category landing pages are selected by us, by hand or by quality-score algorithm — never sold.
• Affiliate commission is uniform across our methodology. A product that earns us 1% commission ranks the same way as one earning 6%. The commission rate is invisible to the algorithm.
• No retailer review or approval of editorial. Buying-guide content and category intros are written entirely by us and never shared with the retailers we mention before publication.

How we source product data

All product, price, and availability data on DealComparer is sourced from real-time retailer feeds via affiliate networks (currently Awin and PartnerBoost, with CJ Affiliate and Tradedoubler being onboarded), or from direct retailer feed exchanges. We refresh feeds hourly via an automated ingest pipeline.

Each row goes through a multi-stage quality pipeline:

• Brand normalisation — we canonicalise brand names so "De'Longhi", "Delonghi" and "DeLonghi" collapse to a single entity.
• Junk filter — spare parts, warranty packs, replacement filters, instruction manuals, and similar non-finished-product entries are excluded from public pages.
• Per-category bouncer — products must match category-specific inclusion patterns AND avoid known false-positive patterns to surface in a subcategory.
• Image quality check — broken, placeholder, or low-resolution images are detected nightly and the corresponding products deactivated until the image is refreshed.
• Cross-retailer dedupe — when multiple retailers list the same product (matched by GTIN, MPN, or fuzzy title match), we collapse them into a single product card with all live offers attached.

How we rank products

Within any category page, the default sort order is determined by:

1. Multi-offer count — products available from more retailers rank higher because they offer the most comparison value.
2. Lowest live price — within multi-offer products, the cheapest comparable price is preferred.
3. Brand recognition signal — established consumer brands with recognisable model identifiers rank higher than unbranded private-label SKUs of similar specs, because users are typically searching by brand.
4. Freshness — products with offers refreshed in the last 24 hours rank ahead of those with stale data.

You can re-sort any category page by lowest price, highest price, or most offers using the toolbar above the product list.

Affiliate disclosure

DealComparer earns commission from qualifying purchases via affiliate links. When you click a "View retailer" or product link, you may be routed via an affiliate network before landing on the retailer's site. If you complete a purchase, the retailer pays us a small commission at no extra cost to you.

This is how we keep the site running and free to use. It does not influence which products surface, in what order, or with what editorial framing.

Adherence to partner policies

We aim to comply with every affiliate network's publisher rules and every individual merchant's programme terms — including content restrictions, tracking URL formats, brand-bidding limits, voucher-code policies, and disclosure requirements. If you're a retailer or affiliate network and believe we're displaying your content in a way that breaches your terms, email hello@digitaledge.uk and we'll fix it within one business day.

Corrections & takedowns

If you spot a factual error, an outdated price, a mismatched product, or a copyright issue with imagery, email hello@digitaledge.uk with the URL and details. We respond within one business day to confirmed corrections or takedowns.

AI agents and structured data

DealComparer publishes schema.org Product and AggregateOffer JSON-LD on every product page so AI shopping agents and search engines can consume our offer data reliably. We also publish a public llms.txt policy file describing what we offer, how to consume it, and how to attribute us. We welcome ethical AI agent traffic that respects rate limits and surfaces our pricing with attribution back to dealcomparer.com.