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Fashion brands are facing immense pressure in today's fast-paced world to quickly and accurately upload their product data onto their e-commerce platforms, as consumers demand instant gratification when it comes to online shopping.

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Google reports that 85% of shoppers surveyed consider product information and pictures important when deciding which brand or retailer to buy from.

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However, manually entering product data is a time-consuming and error-prone task that leaves room for mistakes and delays. Research indicates that 22% of an employee's time is spent on repetitive tasks, which could be automated, resulting in significant savings over time.

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And, a report from McKinsey Global Institute found that over 40% of workers surveyed spend at least a quarter of their work week on manual, repetitive tasks, with email, data collection, and data entry taking the majority of their time.

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This is where AI-powered tagging comes in, revolutionizing the way fashion brands enter their product data.

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What is tagging in fashion? 

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Fashion tagging is the process of assigning labels to product attributes shown in an image, including design style, pattern, color, and material type.

And, AI-powered tagging uses machine learning algorithms to automatically tag and categorize product images based on these attributes, as well as other important features such as clothing type, material, and purpose, resulting in a more efficient and accurate way of categorizing products, saving fashion brands significant time on manual data entry.

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‍Suggested read: The Complete Guide for Automatic Product Tagging in E-Commerce

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How is product tagging done and what are product tags?

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Product tags, also known as object metadata, are descriptors that identify a product's unique features, characteristics, and categories. These tags include color, height, style, brand, use, and price, among others. 

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By implementing product tagging, search functions, product ratings, and inventory management are improved.

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Traditional methods of product tagging involve manual labeling, which is labor-intensive, time-consuming, superficial, and prone to human bias. Fortunately, AI and technology have revolutionized the product tagging process.

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AI image tagging involves assigning multiple attribute labels automatically to each product in the catalog, utilizing neural networks trained on continuously updated datasets such as category prediction and subcategory prediction networks. These networks calculate high-level and more detailed categories for each product and locate the relevant item in the image. Additionally, a separate neural network predicts the relevant attributes from a taxonomy that may apply to the specific item, allowing for images that may contain multiple potential products.

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Manual product tagging is inefficient and can result in poor catalog management, leading to supply chain confusion, time-consuming digitization, and irrelevant search results. As a viable alternative, AI automation of retail processes, including product tagging, has emerged as a solution. By implementing automatic tagging, retailers can effectively organize product catalogs, saving significant amounts of time and energy.

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Suggested read: 2024: Manual Product Tagging Vs. AI-Driven Product Tagging

Advancements in AI technology have paved the way for more efficient workflows in fashion brands. 

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Advantages of AI-powered tagging for fashion brands

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Here are some of the ways AI is making a difference:

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1. Enabling more time for high-value work‍

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According to Smartsheet, almost 60% of workers surveyed believe they could save six or more hours a week by automating repetitive tasks.
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2. Reducing errors and increasing accuracy‍

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AI-powered tagging reduces the chances of human error in categorizing images, leading to a more efficient and effective data entry process.

3. Increasing employee productivity

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By automating repetitive tasks, your employees can focus on higher-value work, leading to improved productivity and job satisfaction. In fact, studies show that 74% of employees in the most automated companies say automation improves job satisfaction, compared to just 53% in highly manual companies.

Instead of paying a full-time employee to manually input data into a spreadsheet, why not let AI-powered automation take care of it? This can help you complete the task more quickly and at a lower cost than your competitors who are still relying on manual labor.

4. Handling large amounts of data

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For fashion brands with a vast product catalog, AI-powered tagging significantly reduces the time needed for manual data entry, allowing them to upload their products faster and stay ahead of competitors.

5. Offering a high level of consistency

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By using algorithms to categorize products, AI-powered tagging ensures a more consistent and organized product catalog. Consistency ensures that customers can easily find what they are looking for, which can increase sales and customer satisfaction.

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Overall, AI technology has the potential to revolutionize the fashion industry, providing more accurate and efficient processes, saving time and money, and ultimately increasing customer satisfaction.

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Wrapping up

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To recap, 

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• AI-powered tagging is revolutionizing the way fashion brands enter their product data;
  
  
• With its ability to save time, reduce errors, handle large amounts of data, and provide consistency, fashion brands can stay ahead of the competition by quickly and accurately uploading their products onto their e-commerce platforms;
  
  
• As technology continues to advance, we can expect to see AI-powered tagging becoming even more prevalent in the fashion industry, transforming the way we shop online;
  
  

Interested in seeing the benefits of AI-powered tagging for your fashion brand? Give our demo a try!

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