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  • Busra Demir

Karaca x Co-one Collaboration | Data Filtering in E-commerce


karaca

Overview


In a dynamic partnership, Co-one collaborated with Karaca, an e-commerce enterprise, with a shared goal - the refinement of their product filtering system. This collaborative endeavor aimed to improve the product search and categorization process, optimizing the user experience on Karaca’s e-commerce platform.


The Problem


At the heart of the challenge lay Karaca’s ambition to elevate its product filtering system. Their vision was clear: to empower customers with a seamless and efficient means of discovering the products nestled within the right categories. So, Karaca’s e-commerce site needed to enhance its product filtering system to help customers easily find the right products in the correct categories. The solution necessitated the meticulous annotation of vital product details, including object names such as Brand, Model Name, and Product Description.


The Solution


Step 1: Crafting a Comprehensive Guideline

To establish a solid foundation for data labeling, Co-one embarked on the meticulous creation of a comprehensive guideline. This document was the cornerstone of the entire project, outlining the rules, criteria, and standards to be rigorously followed throughout the annotation process. The guideline not only ensured uniformity but also acted as a reference point for the crowdsourced team, guaranteeing consistent and accurate data labeling.


Step 2: Efficient Data Transfer

Seamless communication and data transfer were pivotal to the success of this project. Karaca transmitted the necessary data to Co-one via a secure and efficient channel.


Step 3: Expert Annotation by the Crowdsource Team

With data in hand, Co-one’s skilled crowdsource team sprang into action. Their mission was to annotate the object names of the products, encompassing critical details like Brand, Model Name, and Product Description. This vital annotation process was crucial for achieving the project’s overarching goals.


Step 4: Quality Assurance Through Cross-Validation and Expert Review

Co-one maintained a steadfast commitment to data quality. To achieve this, a two-tier quality assurance process was implemented. First, a cross-validation system was employed to scrutinize the annotated data for any inconsistencies or inaccuracies. Flagged data was then subjected to a second round of review, conducted by expert annotators. This dual-layered approach ensured that the data met the highest standards of accuracy and consistency.


Step 5: Data Export and Analysis

Upon completion of the annotation process, the labeled data was prepared for delivery. The data was exported in the desired format (.xlsx), ensuring compatibility and accessibility. But the journey didn’t end there. Also, a comprehensive Dataset Analysis and Findings Report was created and delivered to Karaca. This phase unveiled valuable insights and trends, empowering Karaca with a deeper understanding of their product listings.


Each of these steps was a critical piece of the puzzle, contributing to the project’s overall success and the enhancement of Karaca’s e-commerce platform.


The Result


The fruits of this labor manifested in the meticulous annotation of approximately 8,000 products in a few days. Each product name and its associated information underwent thorough filtration and categorization, delivering precision and organization to Karaca’s product listings. As Co-one, we achieved a success rate of 99% at the end of the project, and then 100% with the arrangements made with feedback.


Customer Review


“Our partnership with Co-one was transformative. They displayed exceptional professionalism in enhancing our product filtering system. From their rigorous planning and precise annotation of 8,000 products to their thorough quality assurance, Co-one exceeded our expectations. Their in-depth Dataset Analysis provided valuable insights that have since improved our platform’s user experience. Thanks to Co-one, our customers now navigate our site with greater ease. We highly recommend Co-one for data annotation needs – a truly reliable and efficient partner!”

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