iMerit delivers product categorization services by classifying and labeling all forms of user-generated content such as text, video and images. Product categorization involves using training data to train a model to predict the category of a given product. The amount of data required is highly dependent on the number of products that must be categorized and the diversity of the product catalog.
Product categorization, also called product classification, is the classification of products into different categories using natural language processing (NLP). Product categorization is both critical and challenging for the e-commerce industry. With the development of AI, companies are trying to apply machine learning to product categorization problems. To improve the user’s experience it is necessary to categorize products into product categories so that customers are able to find their desired products quickly and easily. Categorization typically requires knowledge of product data and product attributes to integrate into the model. Descriptive and comprehensive product titles, product information, and product descriptions are essential for getting a product classification model working correctly.
Product categorization is extremely important for the e-commerce sector. Through relevant new product suggestions, personalized recommendations, and query-understanding algorithms, companies can improve their user experience and increase their conversion rates and profitability. The key to solving the product classification system is obtaining a highly representative, labeled dataset.
Product categorization allows customers to find what they are looking for easily and in no time. Most users will not make a purchase on their first interaction with the website, they search for the best price or the highest quality offering. After comparing, they choose the site with the best price and most seamless shopping experience.
Search engine is the first element where users will interact with online shopping sites and well-organized sites have a significant impact on SEO ranking. Product categorization maps the site which leads shoppers to know where to find what they are looking for. It makes it easy for both people browsing on the store website and people searching on Google or other search engines to find the product.
Product categorization naturally leads to higher sales. When a customer can easily find what they are searching for and can navigate through the e-commerce site easily, it’s more likely that there will be potential conversion.
iMerit provides various product categorization services that cater to a client’s project needs. Common workflows include style categorization, gender categorization, and object categorization. iMerit’s team works with the client to calibrate their quality and throughput requirements and builds custom processes to support client needs. More refined classification into product subcategories or hierarchical classification are also possible. All ecommerce platforms stand to benefit from integrating product categorization into their backend systems, and industry giants such as eBay and Amazon use it extensively to help customers to locate the products they’re searching for.
Taxonomy categorization involves training a model to perform product classification in a hierarchical manner, i.e. one producing a taxonomy structure or tree with a root, middle nodes, and leaf nodes. For example, one might have the goal of categorizing cookware into increasingly refined categories such as Cookware -> (Pots, Pans) -> (Stew Pot, Sauce Pan), etc. Many types of products can be categorized into a taxonomy.
In machine learning, product categorization is a method of classifying products based on predefined parameters, making them easier to recognize for the users and improving search results.
To provide more efficient buying and selling experiences on online shopping sites, it is important for machine learning systems to understand relevant products for genders. Experts train the ML algorithm to predict gender.
Object categorization from image search is a challenging task where machine learning models are trained to recognize and assign specific objects to a certain category. This process is sometimes called generic object categorization.
iMerit subject matter experts will guide you through the process to develop a customized end-to-end workflow.
Transformative, solution-based approach. Interdisciplinary product categorization problem solving. Agility and responsiveness, Time-To-Value enhancers.
Targeted resources. Custom skilling. Focused and deep microlearning curriculum. Domain expertise. Rostering tools.
Alignment of product categorization tools and processes. Structured Development Milestones. Two-step production and QA annotation workflows.
Transparency via analytics. Real Time Monitoring and Service Delivery Insights. Edge case Insights. Dynamic Model Improvement.
Assessment of deliverable. Appraisal of key metrics, quality control processes. Model reconsideration. Analysis of business outcome.
Client Profile : Large E-commerce company
Client data type: Product Taxonomies
Challenge: Product paths were inaccurate and as a result end-users were not finding the right results based on a search query and sellers were unhappy due to reduction in sales on the portal.
Volume: Over 3 million product paths were rectified in 1 year
Outcome: The company was able to enhance search relevance that led to improved user experience. We surpassed the client’s expressed expectations when a 60-member team trained for the task completed the project using an in-house platform. 16×7 coverage was provided with a 24-hour turnaround for each batch.
Client Profile: Large home improvement online retailer
Client data type: Gender categorization
Challenge: Users were facing difficulty finding appropriate products for children on the platform.
Volume: ~5k tasks were completed in 2 weeks,
Outcome: For this task, a five-member team was trained. Gender was selected depending on the style of the product mentioned in the title, description, or interpreted by the image. Data quality was above 95%.
The need for speed in high-quality product categorization has never been greater. iMerit combines the best predictive and automated transcription technology with world-class data annotation and subject matter experts to deliver the data you need to get to production, fast.
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