Icecat Release Notes 200: Major Enhancements and Technical Improvements

In Icecat release notes 200, we are marking a milestone in our continuous effort to improve and innovate our systems. This release encompasses significant advancements across various components, including user registration, data health, compliance with EU energy labeling, as well as numerous enhancements aimed at optimizing our tools and processes. Each development is designed to enhance the user experience, streamline workflows, and ensure robust performance and compliance. For additional details, please refer to the previous Icecat Release Notes.

The key highlights of this release include the transition to SSR for the Registration Page, introducing Data Health Score Version 2, integration of EPREL ID for EU Energy Label compliance, improvements to the Export Tool for better product matching, as well as a new notification for cropped images in the product gallery, and crucial technical debt developments. These updates reflect our commitment to providing useful features and maintaining the highest standards of quality and efficiency.

Transition to SSR for Registration Page

In this sprint, we successfully transitioned the Registration page to Server-Side Rendering (SSR). This strategic shift aims to enhance the overall user experience and improve critical web performance metrics as assessed by Google’s Lighthouse tool.

SSR is a method of rendering web pages on the server instead of the client’s browser. This technique is known to deliver faster initial page loads and improve the overall user experience, especially for users with slower internet connections or less powerful devices.

Before the transition to SSR, the Lighthouse metrics for the Registration page were as follows:

• Performance: 88
• Accessibility: 75
• Best Practices: 100
• SEO: 69

After the implementation of SSR, we re-evaluated the Registration page using Lighthouse. Here are the updated metrics:

• Performance: 98
• Accessibility: 96
• Best Practices: 100
• SEO: 100

Analysis of Metrics:

• Performance (98): The performance score saw a significant improvement from 88 to 98. This dramatic increase indicates that SSR has significantly reduced the time it takes for the page to load, providing a much faster and more efficient user experience.
• Accessibility (96): The accessibility score improved from 75 to 96. This enhancement shows our commitment to making the Registration page more usable for people with various disabilities, ensuring a more inclusive experience for all users.
• Best Practices (100): The perfect score for best practices was maintained at 100. This reflects our ongoing adherence to the latest web development standards and practices, ensuring our site remains secure and reliable.
• SEO (100): The SEO score improved from 69 to a perfect 100. This significant enhancement demonstrates that SSR has helped our Registration page become more search engine-friendly, improving its visibility and potential ranking in search results.

The transition to SSR offers several underlying benefits:

1. Improved User Experience: Faster initial load times lead to a better user experience, reducing bounce rates and keeping users engaged.
2. Enhanced SEO Potential: SSR improves how search engines index our pages, leading to better search rankings.
3. Scalability: SSR can better handle high traffic volumes, ensuring consistent performance under load.

The transition to SSR for the Registration page is a significant step forward in our commitment to delivering a high-quality web experience. Especially, the substantial improvements in Lighthouse metrics—particularly in performance, accessibility, and SEO—highlight the effectiveness of this strategy.

We look forward to the positive impact these changes will bring and will continue to work on optimizing our web pages for the best possible user experience.

Data Health Score Version 2: Enhancing Data Quality and Consistency

We are excited to announce the release of the second part of the Data Health Score settings. This enhancement aims to provide a more comprehensive and granular approach to managing and evaluating product data. The new settings encompass various elements such as Family, Series, Images, Description block, Reasons to buy, Multimedia objects, and Specs. Additionally, we have introduced quantity and quality-dependent characteristics, offering a more robust framework for data management.

The updated Data Health Score settings include the following components:

• Family
• Series
• Images: All, Main, Resolution
• Description block: Full product name, Description, Bullet points
• Reasons to buy
• Multimedia objects: Leaflet, Manual PDF, Video, 360, Product story 1.0, Product Story 2.0
• Specs: All, Searchable, Mandatory, Optional

Quantity Dependent Settings

A significant addition to this update is the introduction of quantity-dependent characteristics. This feature allows for the regulation of the asset quantity added to a product. Consequently, this ensures that editors focus on comprehensive data entry, tailored to the complexity and richness of each product.

Example:

• Category A has 100 specs, while Category B has 10 specs.
• The quantity-dependent setting can be configured such that to achieve 100% of this parameter’s score, the editor must add 70% of the specs.
• For Category A, this means adding 70 out of 100 specs.
• For Category B, this means adding 7 out of 10 specs.
• This approach ensures proportional data completeness across different categories, enhancing the overall quality and usability of the product data.

Quality Dependent Settings

In addition to quantity, the new settings also incorporate quality-dependent characteristics. This allows for setting specific quality thresholds that must be met to achieve full scores for certain parameters.

Example:

• For images, we have added the capability to set a minimum resolution requirement.
• Products will receive a score for this parameter only if the images meet or exceed the specified resolution.
• This ensures that high-quality images are consistently used, improving the visual representation and reliability of the product data.

The introduction of these advanced settings offers several benefits:

• Improved Data Accuracy: Ensures that product data is not only complete but also meets specified quality standards.
• Consistent Data Entry: Encourages editors to maintain consistency in data entry.
• Enhanced User Experience: High-quality and comprehensive product data improves the overall user experience for customers, aiding in better decision-making.
• Scalable Framework: The flexible nature of quantity and quality-dependent settings allows for scalable application across diverse product categories and parameters.

The Data Health Score Version 2 represents a significant step forward in our commitment to maintaining high standards of product data quality. By incorporating both quantity and quality-dependent characteristics, we provide a more detailed and effective way to manage and score product information. These enhancements will help ensure that our product data remains accurate, comprehensive, and of the highest quality, ultimately benefiting both our internal processes and our customers.

EPREL ID for EU Energy Label: Enhancing Compliance and Data Integration

We have made a significant enhancement to our product data management system to better align with the EU Energy Label regulations. This update involves the integration of EPREL (European Product Database for Energy Labeling) IDs directly from the EPREL link into our product XML and JSON files. Furthermore, this development ensures that our products comply with the stringent requirements set forth by the EU and enhances the transparency and accuracy of our energy labeling data.

The EPREL ID is a unique identifier assigned to products registered in the European Product Database for Energy Labeling. This identifier is crucial for compliance with EU regulations, as it links the product to its detailed energy label information stored in the EPREL database. Including the EPREL ID in product data is mandatory for products sold in the European market, ensuring that consumers have access to accurate energy efficiency information.

In this sprint, we focused on extracting the EPREL ID from the provided EPREL link and integrating this information into our product data files. The changes include:

1. Product XML File:

• A new attribute named “EprelId” has been added to the “MultimediaObject” tag.
• This ensures that the EPREL ID is explicitly provided in the product XML, enhancing compliance and data clarity.

2. Product JSON File:

• A new key “EprelId” has been introduced in the “Multimedia” section of the JSON file.
• This addition ensures that the EPREL ID is readily available in the JSON format, facilitating easier data processing and integration.

This update ensures our product data is fully compliant with the EU Energy Label regulations. By providing the EPREL ID in the specified formats, we facilitate better regulatory compliance and make it easier for our partners and customers to access and utilize this critical information.

Export Tool Improvement: Streamlining Product Matching for Editors

Our team has made significant enhancements to the Export tool, a popular feature within our Product Information Management (PIM) system. This tool is widely used by our editors to export essential information about products stored in our database. In this sprint, we introduced a key improvement that allows editors to match products using Global Trade Item Numbers (GTINs). This new capability aims to save our editors time by streamlining the preliminary product matching process, previously handled by the “Coverage from file” tool.

The primary improvement in this sprint is the addition of GTIN-based product matching within the Export tool. This enhancement simplifies and accelerates the process of extracting product information, enabling editors to work more efficiently. Here’s an overview of the new matching capabilities and logic:

• Product ID Matching: If the file contains a product ID, the tool matches products solely based on the product ID, which is a unique identifier in the Icecat system.
• Product code + Brand Matching: If the product ID is not available, the tool searches for products using a combination of Product code and Brand.
• GTIN Matching: If no match is found with Product code + Brand, the tool matches products by GTINs.
• Fallback Handling: If no matches are found, the system leaves an empty line with placeholders for Product code + Brand or GTIN, indicating the unmatched entries.

Benefits of the Enhancement

• Time Savings: By integrating GTIN-based matching into the Export tool, editors can bypass the preliminary matching step, saving considerable time and effort.
• Improved Accuracy: The comprehensive matching logic ensures that product information is accurately matched and extracted, reducing the risk of errors.
• Enhanced Workflow: This enhancement streamlines the editorial workflow, allowing editors to focus more on content quality and less on data matching.

We are confident that this development will greatly enhance the productivity of our editors and look forward to their feedback as they integrate this new capability into their workflows.

Cropped Image Notification in the Product Gallery

We are pleased to announce a small yet impactful development designed to significantly improve the workflow of our editors. In our continued effort to enhance the usability and efficiency of our PIM system, we have introduced a new feature in the product gallery that visually notifies editors if an image has been cropped. Furthermore, this new sign serves as an important indicator, informing editors that the image has been standardized according to Icecat’s rigorous standards.

A clear sign is now displayed on images within the product gallery that have been cropped. This sign confirms that the image meets Icecat’s standardization criteria, ensuring consistency and quality across all product images.

Benefits for Editors:

• Efficiency: Editors can quickly identify which images have been processed and standardized, reducing the time spent on manual verification.
• Quality Assurance: The visual notification helps maintain high standards of image quality, ensuring that all product visuals adhere to Icecat’s guidelines.
• Improved Workflow: By instantly knowing the status of an image, editors can streamline their tasks and focus on other important aspects of product information management.

We believe this improvement will greatly benefit our editorial workflow, making the process of managing product images faster, more accurate, and more reliable.

Addressing Technical Debt: Enhancements and Developments

In the latest sprint, our team focused on addressing various aspects of technical debt, as well as implementing several key improvements to enhance the efficiency, reliability, and performance of our systems. These developments span multiple areas, including the Reporting Engine, file storage migration, and the new Editor Journal. Here is a detailed overview of the progress made.

Reporting Engine Enhancements

• Disabling Unused Scripts: we identified and disabled several scripts within the Reporting Engine that were no longer in use. This cleanup reduces system clutter and potential maintenance overhead.
• Re-engineering Aggregate Product Count: the aggregate product count functionality was re-engineered to improve its performance and accuracy. This enhancement ensures more reliable and faster reporting metrics.
• Statistics Duplication to Cassandra: to bolster system resilience, we created a duplicate of statistics data in Cassandra which will keep statistics information for the last three months. This serves as a fallback mechanism to ensure continuity when Clickhouse experiences issues, thereby improving data availability and reliability.

File Storage Migration

• Removal of Unused Files:  as part of our ongoing effort to migrate files from mounted storage to S3 storage, we conducted a thorough review and removed several unused files. This cleanup helps streamline our storage infrastructure.
• Transition to S3 for File Reading: we successfully transitioned file reading operations from mounted storage to local S3 storage. This change enhances data retrieval efficiency and aligns with our goal of modernizing our storage solutions.
• Deprecation of Perl Files Creation: Perl file creation processes were deprecated in favor of file creation by PHP. This transition supports our move towards more contemporary and maintainable codebases.

New Editor Journal Development

• Completion of Product History RESTs: we completed the development of two new RESTful APIs for the product history. These APIs provide detailed historical data about product edits and changes, enhancing traceability and data integrity. The newly developed REST APIs are currently in the process of covering with autotests. This step ensures that the APIs are robust, reliable, and free from defects, contributing to higher software quality.
• Setting Editor Journal Data: we began setting editor journal data for Reasons to Buy and the product Gallery. This development allows editors to track and manage product information more effectively, improving overall data management and user experience.

The technical debt developments undertaken in this sprint are pivotal in enhancing the performance, reliability, and maintainability of our systems. These efforts not only streamline current operations but also lay a stronger foundation for future developments.

As we roll out these enhancements, we remain dedicated to refining our platform and delivering exceptional value to our users. We are confident that these improvements will significantly benefit our users, ensuring a smoother, more efficient, and more reliable experience.

Olena Vasylynenko