Hourly Pricing Across 12 Uk Supermarkets

By Author: Actowiz Solutions
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Introduction
How a London-based consumer app went from manual price checks to 4.8 million product updates a day — with zero downtime in the first 180 days
Actowiz Solutions | Case Study | Industry: Consumer Apps / Retail Tech
Client Snapshot
The client is a London-headquartered consumer app helping UK households save on their weekly grocery shop by comparing prices across major supermarkets in real time. Backed by a seed round in 2024 and a Series A in 2026, the company set out to be the most accurate, most current grocery price comparison platform in the UK — a market with notoriously fast-moving prices and aggressive private-label dynamics.
Client name and exact retailer breakdown are anonymized at the company’s request.
The Business Challenge

In its first year, the app relied on a combination of manual price checks, weekly flyer ingestion, and best-effort scraping built by two backend engineers. As user growth accelerated past 380,000 monthly active users, three problems became existential:
Price freshness was inconsistent. Some categories refreshed weekly, others ...
... daily, others not at all. A growing share of user-reported errors traced back to stale data.
Coverage was patchy. Only seven of the twelve major UK supermarkets were tracked. Users repeatedly asked why Lidl, Aldi, M&S Food, Iceland, and Ocado were missing.
Engineering capacity was being burned on infrastructure maintenance instead of product features. The in-house scraping stack broke an average of 3.4 times a week.
"Every hour of bad data was an hour of churn risk. We needed a partner who treated price data as a first-class product, not as a side gig." — Head of Product
Project Scope

Retailers
Tesco
Sainsbury’s
Asda
Morrisons
Aldi
Lidl
Co-op
Waitrose
M&S Food
Iceland
Ocado
Amazon Fresh UK
Postcode Coverage
All UK postcode districts
Store-anchored pricing where retailers expose location-specific pricing
Products Tracked
Approximately 168,000 active SKUs
Coverage across all 12 retailers
Refresh Cadence
Hourly for promotion-sensitive categories
Every 4 hours for long-tail SKUs
Daily for assortment updates
Field Depth
Selling Price
Was-Price
Loyalty-Card Price
Multi-Buy Promotions
In-Stock Flag
Unit Price
Delivery
REST API with sub-200ms p95 latency
Nightly Parquet files delivered to the client’s S3 bucket

Solution Architecture
1. Postcode-anchored crawler fleet
Actowiz deployed a distributed crawler fleet anchored to representative postcodes across all UK regions, capturing store-level pricing where retailers expose it (notably Tesco and Sainsbury’s) and chain-level pricing where they do not. Crawlers ran on residential IPs with mobile-app traffic patterns to maintain stability against anti-bot systems.
2. Loyalty-pricing capture
Clubcard prices on Tesco and Nectar prices on Sainsbury’s were captured as a second price field alongside the everyday price. This single capability differentiated the client’s app from every competitor in the market.
3. Real-time promotion engine
Multi-buy mechanics ("3 for £5", "2 for £1.50"), BOGOs, and percentage-off offers were parsed into a structured promotion schema so the client app could surface the cheapest equivalent basket, not just the cheapest unit price.
4. Self-healing schema monitoring
Each retailer module ran continuous schema validation. Any deviation from the expected response shape triggered an engineering alert before user-visible errors could spread.
5. Two delivery channels
A low-latency REST API powered the live in-app comparison experience. A nightly Parquet dump replicated the full dataset into the client’s data warehouse for analytics, personalization, and CPI-style historical analysis.
Implementation Timeline

Discovery & Pilot
Activities:
Schema design
Sample delivery on Tesco, Sainsbury’s, and Asda
Duration: Weeks 1–2
Core Rollout
Activities:
Onboarding remaining 9 retailers
Loyalty price capture
Promotion parser implementation
Duration: Weeks 3–6
Cut-Over
Activities:
API go-live
In-app integration
Parallel run versus legacy stack
Duration: Weeks 7–8
Hyper-Care
Activities:
Daily SLA monitoring
Schema drift triage
Performance optimization
Duration: Weeks 9–12

Results in the First 180 Days
4.8 million product price points refreshed per day, up from 380,000 with the legacy stack — a 12.6x increase in data throughput.
Retailer coverage grew from 7 to 12 of the UK’s major grocery chains, with Lidl, Aldi, M&S Food, Iceland, and Ocado added in the first 10 weeks.
Zero unplanned downtime on the production data feed in the first 180 days. Schema drift was detected and patched proactively in 14 separate instances before any user-facing error.
User-reported price accuracy complaints dropped 71 percent quarter-on-quarter.
In-app session length grew 28 percent, attributed by the product team to the addition of loyalty-card pricing and the new "cheapest basket" recommendation.
Engineering hours redirected: approximately 1,100 hours per quarter previously consumed by scraper maintenance moved to product feature work.
The client closed its Series A on the strength of the data moat — investors cited Actowiz-powered freshness and coverage as a differentiator in due diligence.
"Actowiz turned price data from our biggest operational risk into our biggest product strength." — CTO
Why It Worked
Treating data as a product, not a script. SLAs, schema versioning, and proactive monitoring were table stakes — not stretch goals.
Loyalty pricing as a differentiator. Capturing what other comparison tools missed gave the client a marketing story and a measurable UX uplift.
Engineering offload. Letting the client team stop maintaining scrapers was as valuable as the data itself — it converted into product velocity.
Promotion intelligence, not just prices. Surfacing the cheapest basket required structured promotion data, not raw price lists.

Learn More >> https://www.actowizsolutions.com/uk-supermarket-price-comparison-app.php

Originally published at https://www.actowizsolutions.com