About the Client
The client manages a large product catalog in NetSuite and sells across multiple channels. To keep listings complete and accurate, it relies on Icecat, a product content platform that supplies detailed descriptions, specifications, images and more. But getting that content into NetSuite was a manual, time-consuming job.
The Challenge
Keeping a large catalog accurate by hand created seven problems.
Manual Data Gathering
Product information was entered by hand, which led to errors, inconsistencies and outdated catalog content.
Time Drain
Teams spent too much time updating product details across platforms instead of working on strategic projects.
Data Discrepancies
Inconsistent product details across systems confused customers, hurt sales and affected the brand’s reputation.
Slow Response to Market Changes
Delays in updating product information meant missed opportunities and reduced competitiveness.
Inefficient Inventory Management
Without real-time stock information, the business risked stockouts or overstocking.
Poor Customer Experience
Inaccurate or incomplete product information led to customer dissatisfaction and more returns.
Limited Product Insights
Without centralized data, it was hard to analyze product performance and make informed decisions.
The Solution
LST Consultancy built an Icecat NetSuite integration that brings product content management directly into the client’s ERP.
Icecat
Product content
- Laptop42 specs · 6 imagesImported
- MonitorNew descriptionUpdated
- PrinterMissing specsFlagged
- Headset18 specs · 3 imagesImported
Icecat API + scheduled import
- Field mapping
- Validation checks
- Discrepancy alerts
- Scheduled sync
Oracle NetSuite
One accurate catalog
- Item recordsDescriptions and specifications
- Item imagesAttached automatically
- Stock levelsUpdated in NetSuite
- AlertsDiscrepancies flagged for review
Automated Data Syncing
Product descriptions, specifications and images sync from Icecat into NetSuite on a regular schedule, so product details stay current.
Centralized Product Information
Icecat serves as the central source of product data, reducing duplication and discrepancies across platforms.
Inventory Updates
Stock level information is updated in NetSuite, improving inventory accuracy and responsiveness to demand.
Automated Data Entry
APIs and data import tools handle product information entry, minimizing manual work and errors.
Better Reporting and Analytics
Integrated data supports reporting on product performance, sales trends and inventory levels.
Accurate Product Listings
Complete, accurate listings improve the shopping experience and reduce returns caused by wrong information.
Regular Audits with Alerts
Routine data audits, plus automated alerts for discrepancies, keep product content accurate over time.
Training and Support
Staff were trained on the new integration and tools so they could manage product data confidently.
How We Delivered It
We used an Agile approach across eight phases.
Initiation
We defined objectives and scope, identified stakeholders and set up communication channels.
Planning
We built the project plan and analyzed requirements for data fields and integration needs.
Design
We designed the integration architecture, data mapping between Icecat and NetSuite, and user workflows.
Development
We built the APIs, data synchronization, and automated import and update processes.
Testing
We ran unit and integration testing, followed by user acceptance testing (UAT) with key stakeholders.
Deployment
We rolled out the integration to production and monitored early performance.
Training
We ran training sessions and created user documentation and support materials.
Maintenance and Support
We set up ongoing support and continue to optimize the integration based on feedback and business needs.
The project team included a project manager, business analyst, technical lead/developer, QA tester, IT support specialist and training coordinator.
Obstacles We Overcame
Importing third-party product content raised four issues. Here’s how we handled each one.
Data quality issues
Challenge- Icecat product data was sometimes inconsistent or incomplete.
How we solved it- Validation checks during import to ensure accuracy and completeness.
Integration complexity
- Challenge
- Mapping data fields and managing API connections was technically complex.
- How we solved it
- A thorough requirements analysis and a robust integration architecture.
Change management
- Challenge
- Some users were hesitant to adopt new processes.
- How we solved it
- Comprehensive training and support, highlighting the benefits of the integration.
System downtime
- Challenge
- Deployment could have disrupted operations.
- How we solved it
- Deployment during off-peak hours, with a rollback plan ready.
The Results
The integration paid off in efficiency, sales, accuracy and adoption.
Efficiency- 85%
- reduction in manual data entry thanks to automation
- 70%
- time savings in data management, freeing teams for strategic work
- 60%
- faster response to market changes, with quicker product updates
Customers and Sales- 15%
- increase in sales after the integration, attributed to better product information and customer experience
- 85%
- improvement in customer satisfaction, with fewer returns
- 80%
- improvement in customer feedback on product accuracy and availability
Accuracy- 95%
- reduction in product data errors after integration
- 80%
- improvement in inventory management efficiency, with more accurate stock levels and fewer stockouts
Project Delivery- On time
- delivered within the planned timeline
- 90%
- user adoption within the first three months
Key Takeaways
Rich product content sells
Complete descriptions, specifications and images contributed to a 15% sales increase.
Validate on the way in
Checking third-party product data during import stops bad content from reaching your catalog.
Automate the boring parts
Removing manual entry saved 70% of data management time.
Train for adoption
Training and documentation helped reach 90% user adoption within three months.
