Pricing Information for Bottles Liquor Dataset
Product Data Scrape developed a structured Pricing information for Bottles Liquor Dataset for a multi-brand beverage retailer and market intelligence organization. The project focused on scalable Alcohol Price Data Scraping, capturing product names, brands, bottle sizes, prices, discounts, availability, categories, URLs, and collection timestamps. The solution transformed fragmented online pricing information into an analytics-ready resource for competitive monitoring and market analysis. Key results included 96%+ data-field completeness, 93%+ automated validation accuracy, and 70% faster recurring data processing.
Client Challenges
The client monitored spirits and liquor categories including whisky, vodka, rum, gin, tequila, and liqueurs. Manual research and spreadsheets created difficulties in standardizing product names, categories, bottle sizes, prices, and promotions. Comparing 375 ml, 750 ml, and 1 L products without normalization could distort competitive insights. Promotional prices also needed to be separated from regular prices.
Goals & Objectives
The project aimed to build a Liquor Price and Competitor Intelligence Dataset covering multiple brands, products, bottle sizes, and retailers. Objectives included automating recurring collection, normalizing product and pricing fields, reducing manual processing, detecting duplicates, enabling historical price comparisons, and creating standardized datasets for dashboards and reporting.
Our Solution
Product Data Scrape implemented a five-phase workflow:
Source & Product Mapping: Defined retailer, category, product, brand, bottle-size, price, availability, URL, and timestamp fields.
Automated Data Collection: Captured product and pricing information from selected online sources.
Data Normalization: Standardized product names, brands, categories, bottle sizes, currencies, prices, and availability.
Validation: Checked missing fields, duplicate products, abnormal prices, URLs, units, and category inconsistencies.
Recurring Monitoring: Created historical snapshots for price comparisons, promotional analysis, competitive benchmarking, and reporting.
Results & Business Value
The solution achieved 96%+ data-field completeness, 93%+ validation accuracy, 70% faster recurring processing, 60%+ reduction in manual review, and 90%+ duplicate-control effectiveness. The resulting Bottles Liquor Pricing Intelligence for Retailers dataset supported brand-level, SKU-level, and bottle-size pricing analysis across products such as Absolut, Bacardi, Grey Goose, and Jack Daniel's.
Product Data Scrape transformed scattered liquor listings into structured intelligence supporting competitive pricing, assortment analysis, promotional tracking, historical comparison, and retail market intelligence.https://www.productdatascrape.com/bottles-liquor-pricing-information-dataset.php
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