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Real-Time Regional Insights with Customizable E-commerce Dashboards

Introduction

Grocery pricing in the United States isn’t uniform—it varies by city, neighborhood, and even ZIP code. This variability directly impacts FMCG brands that aim to stay competitively priced across all channels.

Actowiz Solutions partnered with a leading food & beverage company in the U.S. to develop a hyperlocal pricing intelligence system that aggregates data using Walmart, Shipt, and Target APIs. The goal: identify pricing gaps, avoid regional mismatches, and enable dynamic price adjustments at the zip code level.

Objectives

  • Extract daily product prices from Walmart, Shipt, and Target across 100+ ZIP codes.
  • Identify price disparities across neighboring zones.
  • Provide a unified dashboard for marketing and pricing teams.
  • Trigger alerts for high-variance SKUs and discount competition.

Challenges

The-Client
  • Zip-code level API access varied per platform.
  • Some platforms dynamically altered price per delivery location.
  • Data normalization was difficult due to SKU naming inconsistencies.
  • Shipt’s delivery-centric model had fewer APIs available.

Actowiz Solutions' Approach

The-Client
1. API Integration Strategy:
  • Integrated Walmart’s ZIP-specific API endpoint
  • Accessed Target’s public pricing API with ZIP parameter injection
  • Reverse-engineered Shipt’s delivery pricing module using mobile endpoints
2. ZIP-Code Data Mapping:
  • Curated a list of 120 ZIP codes across 12 metro areas (e.g., 10001, 90210, 60601, 77001)
  • Scheduled data extraction 4x daily
  • Created geo-intelligence layers to visualize city and neighborhood patterns
3. Product Matching Engine:

Used NLP-based fuzzy matching to unify SKUs with slight name or size differences, e.g.:

  • "Oreo Double Stuf 15.35 oz" vs. "OREO Double Stuffed Cookies 15.3oz"
4. Price Comparison Metrics:

Generated daily comparative analytics like:

  • % Deviation from National Average
  • Top 10 Price Volatile ZIPs
  • ZIPs with Lowest Average Price for Top 50 SKUs

Sample Data Snapshot

SKU ZIP Code Walmart Price Target Price Shipt Price Avg Price Variance %
Lay's Classic 8oz 10001 $3.89 $4.19 $4.45 $4.18 14.4%
Tropicana Orange 52oz 90210 $5.25 $5.00 $5.75 $5.33 13.9%
Cheerios Cereal 12oz 60601 $3.49 $3.79 $4.05 $3.77 15.6%

Key Deliverables

  • Real-time zip-code level price feed via REST API
  • Daily Excel/CSV exports for all ZIPs and SKUs
  • Custom-built Power BI dashboard for geo-filtering
  • Competitive variance report delivered every Monday

Impact & Results

The-Client
🔹 Regional Price Harmonization:
  • Reduced price mismatches across cities by 22% within 6 weeks.
🔹 Optimized Local Promotions:
  • Marketing targeted areas with higher competitor discounting.
🔹 Dynamic Pricing Engine Feed:
  • Data now used as input in client's AI-driven dynamic pricing module.
🔹 Expansion to 200 ZIP Codes:
  • Based on early success, coverage scaled to 2x more ZIPs.

Technology Stack

  • Languages: Python, Node.js
  • Databases: PostgreSQL, MongoDB
  • APIs Used: Walmart Open API, Target Store Price API, Shipt Mobile API (reverse-engineered)
  • Visualization: Power BI, Tableau integration
  • Hosting: AWS (Lambda, EC2, S3)

Why Actowiz Solutions?

  • 🌐 Advanced geo-based scraping & API integration
  • 🎉 NLP-powered SKU standardization
  • 🚀 Fast deployment: 10 days to MVP
  • ✅ Proven success across multiple U.S. metros

Client Feedback

"Actowiz Solutions gave us the visibility we never had before. Our teams now react to market changes in hours, not weeks."

— VP of Revenue Strategy, Grocery Client USA

What’s Next

  • Integrating Costco and Kroger ZIP-based pricing
  • Creating forecast dashboards based on price volatility
  • Real-time alerts via Slack + SMS for pricing managers

Conclusion

Hyperlocal grocery pricing is no longer a guessing game. With Actowiz Solutions' data infrastructure and U.S.-focused grocery API integrations, brands can take control of pricing strategy ZIP code by ZIP code. This leads to improved competitiveness, better ROI on promotions, and data-driven marketing at its best.

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