What is D2C?September 19, 2023
Fashion SearchOctober 19, 2023
What is an E-commerce search engine? What are the challenges to constructing a great one?
In the fashion e-commerce industry, a search engine is a pivotal tool designed to enhance product discoverability on digital storefronts. A robust fashion e-commerce search engine is capable of effectively deciphering customer search queries. Users engaging with search engines are often high-intent, making them a critical segment for any e-commerce platform. However, the modern shopper expects personalized experiences, steering away from overwhelming product listings.
Together with anonymous shopping preferences and data privacy concerns present a unique challenge, where brands and websites are expected to provide tailored experiences without intrusive data collection. Many search engines exhibit limitations, underscoring the need for innovation.
Beyond the Fashion Search Engine:
For any brand or e-commerce platform, optimizing product discoverability is paramount. This necessitates meticulous tagging and categorization of each item in the catalog. Precision in the tagging system is a primary challenge for search engines. Leveraging a visual AI-based tagging system
What are Tags and Metadata?
Tags represent a specific type of content metadata. It’s important to note that there are various types of metadata, and not all metadata are tags. Tags serve the purpose of identifying the content’s subject matter based on a predefined set of standardized descriptive keywords. This distinguishes content tags from social media hashtags, which are typically user-generated and not standardized.
What is Auto-tagging
Tagging is the process of describing and labeling content, which can be executed manually or automated, using standardized taxonomy terms. Auto-tagging, on the other hand, pertains to the automated application of tags for content description. It’s important to distinguish auto-tagging for content description from the campaign tags used by Google for ad tracking, also referred to as auto-tags by Google.
To streamline the content tagging process and enhance its effectiveness, developers have explored various strategies, including AI-based tagging solutions These employ artificial intelligence to automatically assign tags based on the content’s context and characteristics. AI-based tagging not only ensures consistency and precision but also accelerates the process, playing a pivotal role in enabling personalized recommendations.
Data privacy concerns:
Data privacy concerns are on the rise, requiring businesses to safeguard customer data rigorously. Proposals for limiting targeted advertising are gaining momentum, emphasizing the need for privacy-conscious approaches.
“The practice of targeted advertising is increasingly under fire. New rules now under consideration in the EU could put limits on how tech companies make money… And it’s not just a European issue. Some Democrats in Washington have proposed a bill that seeks to nearly ban targeted advertising altogether.” (Jillian Deutsch, Bloomberg Technology Newsletter, 02.18.2022).
The AI Key
One way to avoid some of the privacy issues is by utilizing, a highly precise AI tagging system. By adding this incredible tool to the e-commerce arsenal the brand enables personalization. This solution does not rely on intrusive data collection methods, it fosters trust from the moment a shopper’s journey begins.
Evidently, More and more people are becoming more aware of their data and privacy and are less willing to share this information “Today’s businesses have a fragile social contract with their customers. They have a responsibility not only to protect customers’ data to the highest standards….businesses must deliver on both fronts in an increasingly complicated regulatory environment.” (Adobe Digital Trends, 2022).
Personalized Recommendations In most cases, after a search engine leads a shopper to a product page, further exploration is desired. Highly accurate “Shop Similar” product recommendations, driven by a visual AI recommendation engine, strategically positioned on the product page, cater to these needs. This image recognition-powered site search aligns with the customer’s visual style preferences, delivering relevant search results and ensuring seamless product discovery.