Case Study Leveraging AI Insights: Global Supermarket Chain Optimizes Pricing in 200 Locations

About the Client

The client is a longstanding U.S.-based grocery retailer with an annual turnover nearing $1.6 billion. With an expansive presence, it oversees close to 200 stores across multiple states, solidifying its position as one of the nation's premier supermarket chains.

Client Challenge

The client needed help aligning its products with comparable offerings from competitors and monitoring price variations across numerous zip codes. The fresh produce category and non-branded Stock Keeping Units (SKUs) posed particular challenges regarding product matching and price comparison. Additionally, the client needed help to track discounts and promotions initiated by rival competitors effectively.

Project Highlights

• Sector: Grocery, Fast-Moving Consumer Goods (FMCG) / Consumer Packaged Goods (CPG)

• Geographic Focus: United States

• Annual Revenue: Approximately $1.6 Billion

• Store Footprint: Around 200 locations

• Product Range (SKUs): 7,000

• Competitor Product Data Analyzed: 8 million SKUs
• Major Competitors: Meijer Inc, Trader Joe’s, Walgreens Boots Alliance, H-E-B, CVS, Instacart, Walmart Inc.

Scope of Work

• Competitor Websites Analyzed: 10, featuring Walmart and Instacart
• Total SKUs: 7,000
• Fresh Produce: Approximately 350
• Private Label: Roughly 250
• Other: National Brands
• Covered Zip Codes: 50
• Implementation Timeline: 4 weeks

Primary Users

• Price Management Division
• Procurement and Category Oversight
• Marketing Team
• eCommerce and Business Expansion

Product Matching

• Actowiz Solutions achieved a 98% accuracy rate in algorithm-based product matching. Continuously updated, the algorithm identifies new product matches as assortments evolve or undergo refreshment.
• For the client, fresh produce presented significant complexities. In the trial phase, Actowiz Solutions was the sole vendor delivering precise outcomes in this category. Our approach was instrumental because product comparisons in fresh produce often necessitate attribute standardization alongside data scraping.
• Our algorithm significantly improved results within the fresh produce segment. This was accomplished by integrating quality factor standardization and facilitating per-unit price calculations, simplifying and enhancing user price comparisons.

Private Label Product Comparison

Actowiz Solutions utilized its internally developed proprietary matching engine, "Sherlock.AI," enabling clients to fine-tune the algorithm for optimal "similar" matches in scenarios such as:

• Private Label versus Private Label
• National Brand against National Brand
• Private Label compared to National Brand

Comprehensive Domain Scrapping (Gap Analysis)

• Extracted data from the entire competitor catalog, aiding in decisions related to location-specific pricing strategies and product assortments.
• This approach also facilitated an in-depth brand gap analysis.

Online Delivery Partner Data Extraction

• Gathered data from third-party delivery partner platforms such as Instacart, facilitating a more comprehensive analysis of commissions and mark-ups.

Coupons Scraping

Actowiz Solutions' scrapers efficiently extracted promotions, discounts, and coupons, even when dispersed across various website sections such as:

• Product details page
• Shopping cart and checkout section
• Specialized promotions page

Project Results

Pricing Team

• It enhanced the competitive pricing for popular products, resulting in a sales volume boost of up to 5% from the second month onward.
• Optimized the pricing strategy for private label brands and supported the client in their robust promotion, culminating in a notable sales share increase of over 7% compared to previous peaks against national brands.
• It enabled the flexibility to adjust upward and downward pricing based on the store's location.

Obtaining Team

• The client enhanced their negotiation leverage with national brands by gaining more precise insights into competitor pricing. They also effectively assessed the feasibility of shipping versus local sourcing across various locations.

Marketing

• The marketing team enhanced its promotional strategy by swiftly scraping competitor data, ensuring timely promotions that countered competitors' schedules.
• They gained profound insights into competitors' tactics by extracting comprehensive promotional details from multiple website sections.
• Furthermore, they utilized zip code-specific data to establish targeted promotional zones, aligning more effectively with competitor pricing and strategies.

Empowering E-Commerce Excellence Through Precision Data

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