Case Study

DealSupermarket: AI-led price comparison and deal intelligence.

Built to answer a simple question: is this a good price right now? The platform blends live offers, history context, alerts, and guided bundle decisions.

Discuss a similar build Explore DealSupermarket

Publicly visible product characteristics

Core user experience

  • Comparison flow with multiple retailer offers
  • Price history and typical-price framing on deals
  • Alerts for drops and timing-sensitive buying
  • Guide Me interaction for bundles and alternatives

Commercial structure

  • Affiliate-driven clickout model with explicit disclosure
  • Pro plan with faster refresh and deeper analytics features
  • Platform narrative focused on independent ranking
  • Consumer trust through transparent policy and legal pages

Technical blueprint

A DealSupermarket-like architecture is a data platform plus a decision engine and SEO-ready frontend.

  1. Ingest partner catalogs and normalise entities
  2. Store offer and history events in a time-series-friendly model
  3. Compute baseline and deal-scoring signals
  4. Serve fast product pages and alert evaluations
  5. Add copilot tooling with strict factual tool-calling

Execution milestones used in this blueprint

Milestone Target Outcome
Corporate Site MVP Weeks 2-4 Conversion-ready pages, SEO setup, legal baseline.
Deal Platform MVP Weeks 6-12 Ingestion, offer comparison, price history, alert delivery.
Pricing AI v1 Weeks 12-18 Typical-price model, forecast confidence, explainability.
Bundle + Copilot Weeks 16-22 Guide Me bundle optimization with governed tool calls.