How We Delivered Competitive Pricing Insights on Price Wars Across FairPrice, Giant, and Sheng Siong for a Leading Retail Brand (1)
                     How We Delivered Competitive Pricing Insights 
on Price Wars Across FairPrice, Giant, and Sheng 
Siong for a Leading Retail Brand
Quick Overview
This case study highlights how a leading retail brand gained competitive clarity amid
intense supermarket competition in Singapore. Operating in one of Asia’s most price- 
sensitive grocery markets, the client faced constant margin pressure due to aggressive 
discounting, overlapping promotions, and near-instant competitor price reactions.
Through our Pricing Intelligence Services, we analyzed ongoing Price Wars Across 
FairPrice, Giant, and Sheng Siong to uncover real-time pricing movements, promotion 
triggers, and strategic gaps. The engagement spanned six months and focused on 
automation-driven insights rather than manual reporting.
Key Impact Highlights
 Near real-time competitor price visibility
 Faster price benchmarking across key SKUs
 Improved responsiveness during promotion cycles
 Higher pricing accuracy and confidence
The project enabled leadership teams to shift from reactive price matching to proactive, 
data-backed pricing strategies — critical for survival in Singapore’s highly competitive 
grocery retail environment.
The Client
The client is a large-scale retail brand operating across Singapore’s grocery ecosystem.
The market is dominated by price-conscious consumers, frequent promotions, and 
constant competitive pressure from major supermarket chains.
Digital adoption and mobile shopping penetration in Singapore have significantly
increased price transparency. Consumers routinely compare prices across FairPrice,
Giant, and Sheng Siong before making purchase decisions. Even small price differences 
can impact footfall, basket size, and brand perception.
Before partnering with us, the client relied on:
 Fragmented internal pricing reports
 Delayed market intelligence
 Manual competitor checks
Their teams struggled to analyze the FairPrice vs Giant vs Sheng Siong pricing 
intelligence dataset holistically. By the time reports were compiled, competitor prices 
had already changed — especially during weekend promotions and festive periods.
As the client expanded its product assortment and digital channels, these limitations 
became more pronounced. Manual tracking methods could not scale, and pricing
accuracy deteriorated as data sources multiplied. The absence of automation also
prevented seamless integration with tools like the Giant Food Grocery Data Scraping 
API.
To remain competitive, the client needed a centralized, automated pricing intelligence 
system capable of tracking real-time price wars without increasing operational
overhead.
Goals s  Objectives
Primary Business Goals
The core goal was to establish scalable and reliable price intelligence that could keep
pace with daily pricing fluctuations across major supermarket chains. The client wanted 
faster competitive insights, higher data accuracy, and consistent visibility across retailers.
Strategic Objectives
 Enable FairPrice vs Giant vs Sheng Siong price comparison at SKU level
 Improve response time to competitor promotions
 Protect margins during aggressive discount cycles
 Strengthen customer trust through consistent pricing
Technical Objectives
From a technology perspective, the client aimed to:
 Automate data collection across competitor platforms
 Integrate pricing feeds into internal dashboards
 Enable real-time analytics and alerts
 Leverage Competitor Price Monitoring Services without adding manual 
workload
Key KPIs
 Reduction in price monitoring time by 70%+
 Near real-time price update frequency
 Improved pricing accuracy across channels
 Faster reaction to competitor price drops
The Core Challenge
The client faced multiple operational and analytical challenges that limited pricing 
effectiveness.
Manual s  Fragmented Data Collection
Competitor price tracking was largely manual, inconsistent, and dependent on periodic 
checks. This approach failed during peak promotional periods when prices changed 
multiple times per day.
Delayed Market Signals
By the time internal pricing reports were generated, competitor strategies had already 
shifted. This delay resulted in reactive pricing decisions rather than proactive
adjustments.
Lack of Unified Intelligence
There was no centralized system to analyze supermarket pricing battles at scale. 
Without Grocery Price War Detection Using Web Scraping, the client could not 
systematically monitor how price wars evolved across retailers.
Impact on Margins s  Trust
Late responses to competitor discounts affected margins and sometimes caused price 
inconsistencies that eroded customer trust — especially among value-driven shoppers.
Our Solution
We implemented a structured, phased pricing intelligence solution tailored to 
Singapore’s grocery retail dynamics.
Phase 1: SKU s  Market Mapping
We identified high-impact SKUs across key categories such as:
 Staples
 FMCG products
 Fresh C  packaged foods
Relevant data sources were mapped across FairPrice, Giant, and Sheng Siong platforms 
to ensure comprehensive coverage.
Phase 2: Automated Price Scraping
We deployed advanced scraping frameworks capable of handling:
 Dynamic websites
 Flash promotions
 Regional pricing variations
These systems were optimized to Compare FairPrice, Giant s  Sheng Siong Prices in 
Real Time, enabling continuous monitoring without manual intervention.
To strengthen coverage, we also integrated:
 Extract FairPrice Grocery s Gourmet Food Data
 Web Scraping Sheng Siong Data
Phase 3: Data Normalization s  Validation
Raw pricing data was cleaned, standardized, and normalized across retailers. Intelligent 
validation rules flagged:
 Sudden price drops
 Promotion-driven anomalies
 SKU mismatches
This ensured consistent and reliable insights during volatile price wars.
Phase 4: Dashboards, Alerts s  Insights
Processed data was integrated into custom dashboards used by pricing, procurement, 
and marketing teams. Real-time alerts notified stakeholders when:
 Competitor prices dropped below thresholds
 New promotions launched
 Price gaps widened
This empowered teams to act immediately instead of waiting for reports.
Results s  Key Metrics
Key Performance Outcomes
 Near real-time price updates using Giant Singapore Price Monitoring Service
 75%+ reduction in manual price tracking effort
 Significantly improved pricing accuracy across monitored SKUs
 Faster price adjustments during promotional cycles
Results Narrative
With automated monitoring in place, the client transformed its pricing operations. 
Teams could identify emerging price trends early, respond instantly to competitor 
promotions, and align pricing decisions with live market conditions.
Enhanced visibility improved collaboration across departments, ensuring procurement, 
marketing, and pricing teams worked from the same real-time intelligence. This 
alignment strengthened the brand’s competitive position in Singapore’s grocery market.
What Made Product Data Scrape Different?
Our solution stood out due to domain-specific optimization rather than generic 
scraping.
Key Differentiators
 Proprietary automation frameworks
 Adaptive crawling logic for promotions
 Smart validation and anomaly detection
 Enterprise-scale reliability
Unlike traditional tools, our approach was purpose-built to analyze Price Wars Across 
FairPrice, Giant, and Sheng Siong, delivering actionable insights instead of raw data 
dumps.
This allowed leadership teams to focus on strategy rather than data management.
Client’s Testimonial
“The insights we gained from analyzing Price Wars Across FairPrice, Giant, and Sheng 
Siong completely transformed our pricing strategy. We now have real-time visibility and 
the confidence to act fast. The automation and accuracy exceeded our expectations.”
— Head of Pricing s  Market Intelligence
Conclusion
This case study demonstrates how automated pricing intelligence can redefine 
competitive strategy in grocery retail. By leveraging advanced scraping and analytics, 
the client achieved clarity, speed, and precision in pricing decisions.
Our expertise in Web Scraping Sheng Siong Data and multi-retailer intelligence
enabled continuous monitoring at scale. As supermarket price competition intensifies, 
brands that invest in real-time pricing intelligence will lead the market.
Product Data Scrape remains committed to empowering retailers with data-driven 
strategies that deliver measurable impact.
FAQs
1. Why is competitive price monitoring critical in grocery retail?
Prices change frequently due to promotions and demand shifts. Continuous monitoring 
ensures timely and accurate pricing decisions.
2. How does web scraping support price war analysis?
It automates competitor data collection, enabling real-time detection of pricing trends 
and anomalies.
3. Is the solution scalable across categories?
Yes, it supports thousands of SKUs across multiple categories and retailers.
4. How accurate is the extracted pricing data?
Advanced validation and normalization ensure high reliability.
5. Can it integrate with existing pricing systems?
Absolutely. The solution integrates seamlessly with BI tools and pricing engines.
Source >>
https://www.productdatascrape.com/competitive-pricing-insights-fairprice-giant- 
sheng-siong.php