Client Overview
Manufacturer and distributor of premium OEM 4×4 automotive parts and tools, specializing in hard-to-find components. With a catalog spanning complex parts, fitment data, and technical documentation, the company relies heavily on its eCommerce channel to serve a niche but demanding customer base.
Tech Stack
Platforms
TruPIM
Shopify
Fishbowl ERP
Integrations
ERP → TruPIM
TruPIM → Shopify
Shopify → Google Merchant Center
1. The Problem
As the company scaled its product catalog and digital operations, Shopify alone was not sufficient to manage the complexity of automotive parts data—particularly fitment relationships and hierarchical category structures.
Key challenges included:
- Difficulty modeling and managing vehicle fitment data within Shopify
- Inefficient handling of product hierarchies and fitment-specific technical notes
- High manual effort required to maintain and update catalog data
- Underperforming Google Shopping campaigns due to unoptimized product feeds
2. What Was Holding Them Back
- Lack of a centralized system to manage and govern product and fitment data
- Rigid data structures in Shopify and Fishbowl ERP limiting scalability
- Manual, error-prone catalog management workflows
- Limited control over how product data was structured and syndicated across channels
3. What They Needed
- Centralized PIM system for product, fitment, and category data
- Automated data flows between ERP, PIM, and Shopify
- Scalable way to manage complex fitment relationships
- Improved product data quality for Google Merchant Center feeds
- Reduced manual effort in catalog management and updates
4. How We Solved It
StrikeTru designed and implemented a PIM-led commerce architecture to centralize and operationalize the company’s product data across systems.
At the core of the solution was a centralized PIM system that unified:
- Product data
- Vehicle fitment relationships
- Fitment-specific technical notes
- Product hierarchy and category structures
This approach enabled business users to manage all catalog data in a single system, with full visibility and control over data structures, enrichment workflows, and syndication rules.
To streamline data flow and eliminate manual effort:
- An ERP-to-PIM integration automated the ingestion of base product data
- A configurable PIM-to-Shopify connector enabled near real-time synchronization of product, pricing, and category data
- Data governance rules and automations were implemented to standardize and scale catalog operations
Critically, StrikeTru introduced data automation workflows that significantly reduced manual intervention, including:
- Automated product categorization and hierarchy assignment
- Auto-assignment of ancestor categories to improve on-site search
- Fitment assignment logic based on category relationships
To address the complexity of automotive fitment data, the solution leveraged Shopify metafields to power a scalable Year-Make-Model (YMM) experience:
- Fitment data could be synced as structured key-value pairs, labels, or short codes
- The architecture supports syncing over 60,000 fitments per product, enabling scalability for highly complex catalogs
This PIM-first approach ensured that Shopify functioned as a high-performance storefront, while PIM handled the complexity of data modeling, enrichment, and governance.
5. The Impact
Before StrikeTru
- Manual product onboarding and updates
- No scalable fitment management
- Limited category structure in Shopify
- Inconsistent product content
- High operational complexity
After StrikeTru
- Significant reduction in time spent managing product catalog and fitment data
- Improved scalability of automotive parts data operations
- Enhanced on-site search and product discovery through better category and fitment structuring
- Higher quality product data feeds for Google Merchant Center, contributing to improved ROAS
- Greater control and visibility over product data, enabling faster updates and iteration
6. Why It Matters
For automotive and other complex B2B catalogs, commerce success is tightly coupled with how well product data is structured, governed, and activated across channels.
By implementing a PIM-led architecture, the company transformed product data from a bottleneck into a strategic asset—enabling:
- Scalable catalog growth without proportional operational overhead
- More effective digital merchandising and search experiences
- Improved marketing performance driven by high-quality product data
This engagement highlights StrikeTru’s ability to design and implement data-centric commerce architectures that go beyond platform limitations—helping clients scale efficiently while delivering superior customer experiences.
Modern Commerce Starts with Better Product Data
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