Published on
November 29, 2021
Fashion retailers are increasingly confronted with the changing nature of commerce, especially in the pandemic era, when e-commerce shopping is rising. They must do more than just provide a place for people to make purchases if they want to be competitive.
Naturally, they focus on improving the layout of their website and enhancing the shopping experience. However, in order to achieve this, they need to look at the entire customer journey, which usually starts somewhere on the internet and leads customers to their e-commerce store. This means they also need to think about SEO (Search Engine Optimization) and SEM (Search Engine Marketing). Moreover, they also need to optimize on-site search to make product discovery easier.
This optimization process can be quite challenging, especially during the process of optimization of large amounts of data. This article will talk about how data can be an obstacle with both on-site and off-site searches. Then, we’ll suggest a way to overcome this by leveraging AI algorithms and automatic tagging.
When it comes to on-site search, the retailer has a lot of flexibility in fine-tuning their search algorithms to ensure that when a consumer starts typing to find items on their site, they get exactly what they're searching for.
Let’s say a visitor comes to your website and types in the term “skirt” in the search bar. Because they haven't specifically supplied any helpful information, there is still work to be done in order to assist them in finding their ideal shirt. That’s why you need to personalize results and guide the visitor to the perfect product.
However, not all visitors will go through the same journey. Some of them will have a better idea of what they want. Instead of just searching for a “skirt,” they might search for a “long pleated skirt.” You have a good chance of converting this visitor if you can accurately deliver matched results. To make a fantastic digital experience for this consumer, you don't need to restructure your search experience or employ any complicated customization tactics. All you need to do is provide relevant and thorough information.
With SEO, things are different. You can’t control the results search engines show for a specific keyword. The only thing in your power is data and how you show it. If you provide search engines with relevant data, you will help them to show the correct information to your customers who may be using them.
And, this is very important. In fact, according to Statista, 40% of online shoppers start their product search on search engines. So, it’s essential that you generate rich product data to boost your SEO and SEM efforts. As a solution, we suggest automatic tagging.
Product discovery can become much easier with an AI-based automated product tagging system. Automated product tagging is a technique that can tag numerous features on any image or media source automatically. It considerably reduces the time it takes to tag catalogs and improves the accuracy of both website descriptions and search engine performance.
Automatic tagging organizes and tags photos in the product catalog depending on their properties using powerful Artificial Intelligence algorithms. Deep Learning is used in these algorithms to make the fashion tagging process more effortless and eliminate the need for human interaction. This is a mechanism for generating comprehensive information for objects in a product catalog. It works by scanning a picture for properties associated with particular keywords.
The automatic tagging method gives any image a logical taxonomy with various attribute labels. Automatically recognizing visual features gives far more than just conventional tags; it also delivers deep, nuanced insights about product items. In addition to catalog data, fashion tags accumulate information on their usage, who is using them, and their connections to other tags after a while.
Suggested read: The Complete Guide for Automatic Product Tagging in E-Commerce
Search engines regularly crawl your website. During the crawl process, they collect information from your website, which they will later show in search results when someone is searching for relevant keywords. The more consistent your data is, the higher you will rank when a customer uses a related search phrase to show their buying intentions.
The use of automatic tagging software increases the appearance of items in relevant search results. It allocates them to specific categories and assigns labels to improve product suggestions. Image recognition and machine learning, for example, can extract color, type, and subcategory from an image of a skirt in a retail catalog. These attributions could include “brown,” “mid-length,” “pleaded,” “high-waist,” etc. You can review and approve these tags with a single click.
Automatic tagging can also help you personalize the shopping experience and, therefore, boost conversions. The more thoughtful and precise the product description is, the more customized the customer buying experience will be. Consumers tend to convert when they are exposed to tailored, dynamic information. What is more, they are less likely to abandon their shopping cart or return a product after they get it because they will get exactly what they searched for.
Suggested read: How Intelligent Product Tagging Helps You Understand and Capitalize on Your Shoppers’ Intent
Product tags, names, and accurate and SEO-friendly descriptions may significantly improve product discoverability on search engines. They enhance the accuracy of the information provided on each product by enriching the catalog's metadata. When combined with customer testimonials, these characteristics can send a product to the top of search results. Consequently, this will result in a significant increase in sales.
Product tags are usually overlooked. Yet, without them, the entire e-commerce system comes apart. A catalog with well-labeled tags benefits the whole retail value chain, from lowering costs by automating complete human-centric activities to assisting product discovery by improving product indexing and resulting in more accurate site searches. Moreover, it can also help lower bounce rates on search result pages and give hyper-personalization to users depending on their preferences for certain characteristics.
Try Pixyle’s automatic tagging tool to start generating rich product data and improve your SEO and SEM activities.
How to develop solutions that help shoppers find what they are looking for.
How to develop solutions that help shoppers find what they are looking for.
How to develop solutions that help shoppers find what they are looking for.
How to develop solutions that help shoppers find what they are looking for.
Pixyle AI generates e-commerce product data that enables brands, retailers and marketplaces to deliver exceptional product discovery experiences.
