January 10, 2020
The number of companies that can profit from their own e-commerce platform is huge—from startups and small businesses to big corporations. An e-commerce website is a perfect place where they can market their own products or services.
The shoppers of today are looking for comfort. They don’t want to go to the crowded shopping streets to shop anymore. Instead, they want to shop from their own homes, in just a few minutes, which makes e-commerce the perfect solution.
The e-commerce sector is proliferating due to an imminent growth and the arrival of the 2020 impact on trade. More stores make the switch to online purchases every day, while startups get their start with e-commerce projects. E-commerce sales are expected to rise to $6.54 trillion by 2023, up from $3.53 trillion in 2019.
E-commerce, though, is an ever-changing market. Several new trends pop up every year that can help your company expand and outperform your rivals, and 2021 is no different. As most shopping goes online, a vast number of orders and products are required to be managed at a high level by retailers. This is a difficult challenge, especially for shops selling goods from multiple brands.
Product tagging is one of the responses to this concern. It strengthens the whole product catalog organization. In addition, it makes goods more important because they have the right keywords as their tags.
In 2021, we anticipate more emerging innovations, including catalog management and product tagging, take over retail processes. In this post, we'll talk about automatic product tagging as a way to boost the success of your e-commerce store.
Tagging products is one of the solutions to this problem. It improves the complete organization of the product catalog and makes products more relevant when they have the correct keywords as their tags.
Manual tagging is the conventional way of product tagging. This suggests that the e-commerce shop manager or an employee spends weeks physically applying product tags to the photos in the product catalog, sometimes even months. This is a rather wasteful way of doing stuff, especially when there is a large number of items in the shop. The results are mixed supply chains, a long digitization process of new products, and irrelevant search results that lead to poor customer experience.
The catalog information must be clean and organized, with accurate product details, to avoid these problems. If you manually conduct the retail tagging process, it will be almost impossible to achieve this. However, there’s a much less time-consuming alternative.
Automatic product tagging is an alternative to manual product tagging. Automatic product tagging is a method that uses AI algorithms to organize and tag photos of the product based on their details. The advanced image recognition algorithms that leverage deep learning make the tagging process automated and performed efficiently without the need for human intervention.
The automatic product tagging process automatically generates metadata for catalog assets. It scans the image and identifies patterns within that are linked to particular keywords.
As their use gets more frequent, tags created this way can collect data not only about the catalog data, but also about how and where they’re being used, who is searching for them, and how they correlate to other tags.
One product image can have various tags. For example, if an online retail store has an image of a red skirt, the machine learning technology will attach tags like “midi”, “A-line”, “streetwear”, “red skirt”, etc. This way, people who are looking for both a midi-length skirt and a red skirt could find this image. At the same time, this eliminates a considerable amount of effort and store managers only need to accept these automatically generated tags through one click.
Among various AI-driven products in the retail market, the automated tagging technology has become one of the most important technologies. This technology can recognize items in moving images, videos or to say any kind of visual content.
The visually-intelligent system of auto-tagging engines can extract multidimensional attributes. This takes the customer experience on a higher level and increases sales volumes. At the same time, it can help the creation of a shopper persona for every customer, which enables online retail managers to get a better insight into who their shoppers really are.
Automatic product tagging makes the e-commerce website more personalized. Every click on a tag makes the system aware of the different expectations of shoppers, which, paired with the data-driven historical behavior, gives the right answer to the question: “What does the shopper really want to see?” It allows the customization engine to be much more efficient and precise when reading the purpose of the shoppers.
Automatic tagging is crucial in generating better personalized recommendations. The technology gives more content to the products, giving the personalization system information about what kind of products the users like. This info comes from the combination of the shopper’s search history and the tags. This is valuable data that isn’t available when the products aren’t tagged.
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Product tagging is essential for an efficient e-commerce store. A properly tagged catalog is very important for the value chain of the store. Thanks to the automated workflows, store owners profit from the decreased costs. It also allows consumers to properly get a better overview of the products they want, leading to more precise searches.
Pixyle.ai’s automatic product tagging engine can help you get a clean catalog, improve your SEO ranking, and increase your sales volumes by scanning your entire product catalog in just a few seconds.