For any B2C ecommerce buyer, the ability to browse or search for products “on their own terms” is essential for an engaging customer experience. To be discovered, catalog items must be “tagged” with essential information about the products to distinguish them from others in their category.
Catalog management is the foundation on which the entire retail industry was built. Today’s buyer doesn’t have time to click through several pages to find the product that meets their taste and interest. They want an intuitive information architecture that can help them find what they want quickly and let them get on with their day.
Automated product tagging is the process of analyzing and labeling a product item in an ecommerce catalog with descriptive meta tags. It automatically detects visual attributes from product images, like colors or patterns, through deep learning and computer vision. These AI-authored labels enable website visitors to discover items through a variety of search terms, enabling a more personalized online experience.
We all like to buy from companies that understand us, are credible, and earn our trust. Delivering search results that resonate with a buyer and speak to them in their context helps to build that credibility and trust.
Automated tagging can capture visual attributes of products from still images as well as video. Tags can be applied during content ingestion as part of the digital workflow.
When successful ecommerce websites scale up on product volume and out across product categories, manual tagging can become a tedious, time-consuming, and error-prone process. Especially in ecommerce niches like fashion, where buyer tastes and product trends change rapidly, manually creating and maintaining product tags is a serious hassle.
Brands need to get their products into the minds, hands, and hearts of their customers quickly, or risk missing their window of opportunity. Ensuring an item gets found and stands out among competing products requires a deep understanding of shopper preferences and being able to go to market faster than the competition.
Quality images, authentic reviews, and competitive pricing are all effective at converting browsers to buyers, once they narrow their search. Yet descriptive tags are the crucial ingredient that act as beacons to finding the products on their shopping list. These tags are important to attract attention from search engines.
Ecommerce websites catering to domestic and international audiences can reap many benefits from automatic product tagging as far as search engine optimization (SEO) is concerned.
Retailers and wholesalers are highly motivated to optimize their inventory turnover and product mix. Understanding which products are sitting on shelves for a long time, and which move quickly off the shelves is critical. Product tags are valuable for internal reporting and trend analysis, helping inventory and marketing managers make data-driven decisions about:
Building a high-caliber online store with thousands, tens of thousands, or more product SKUs requires structure, such as classifying products into use case categories. Over the past few years, automated tagging technology has increased in popularity as online catalogs have regained prominence as the driving force that empowers online buyers. This enables buyers to find not only the products they visited your ecommerce store for, but also some they never knew they needed.
For omnichannel retailers, the intelligence from tag data can be used throughout the organization. This technology has become the backbone of the retail industry. It enhances customer experience, leads to higher sales, and helps create a holistic persona for the kinds of shoppers visiting your digital and physical stores.
Like many AI-powered digital workflows, automated tagging is an invisible technology—yet has become indispensable for many retailers. A catalog with well-labeled tags creates efficiencies all along the retail value chain–from decreasing costs by automating entire human-centric workflows to aiding product discovery by helping to index products more effectively. This leads to more accurate searches on search engines and a better understanding of search intent. It also has extra benefits like reducing bounce rates.
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Simion began his career at OSF in 2007 when he entered the internship program as a software developer and quickly ascended within the company holding roles as a team leader and project manager. From 2013 to 2018, Simion established and optimized the company's commerce division, growing the group to over 400 people who delivered over 200 projects, making OSF Digital one of Salesforce’s top ecommerce partners. He has created new local structures designed to support the company's rapid growth in APAC and LATAM while at the same time, worked on innovation of the company's processes, best practices, and products including the creation of the OSF Product Labs program.