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Future of E-Commerce – Visual Search, See It Search It

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    Is your e-commerce business in need of a feature that can breathe new life into it? Perhaps you are searching for a way to take your product visibility to the next level and reach uncharted territories. In either case,  visual search is the solution. 

    From a regular stream of visitors to new customers, visual search helps everyone and can do wonders for your business. It streamlines product discovery for users, boosting your sales. 

    Here’s some comprehensive data about visual search suggesting that it is the future of e-commerce. The market value of visual search is set to exceed $30,000 million by 2028. Let’s understand how visual search sets the pace for e-commerce business.

    Is your e-commerce business in need of a feature that can breathe new life into it? Perhaps you are searching for a way to take your product visibility to the next level and reach uncharted territories. In either case,  visual search is the solution. 

    From a regular stream of visitors to new customers, visual search helps everyone and can do wonders for your business. It streamlines product discovery for users, boosting your sales. 

    Here’s some comprehensive data about visual search suggesting that it is the future of e-commerce. The market value of visual search is set to exceed $30,000 million by 2028. Let’s understand how visual search sets the pace for e-commerce business.

    Visual Search in E-Commerce

    Visual search is changing how users search for products and services online. With advanced algorithms and artificial intelligence (AI), visual search analyzes and interprets the physical attributes of a product to identify relevant results.

    Visual search allows the end-users to search for specific shapes, colors, or patterns by uploading a picture. Google Lens, for example, lets shoppers search for more than 2.5 billion products visually.

    There are numerous advantages to using visual search. Streamlining the search process allows users to find more products faster, improving their overall experience.

    How Does Visual Search Work?

    Powered by machine learning and computer vision technologies, visual search analyzes and understands images and provides search results corresponding to those images’ visual characteristics. Here is a brief explanation of how visual search works:

    • Recognizing images: A visual search starts with the analysis of an image’s shape, color, texture, pattern, and other visual characteristics. Deep learning algorithms are used for image recognition to identify the objects in an image and their characteristics.
    • Extracting features: To extract the features from an image, you must first identify the objects and their features. Feature extraction can numerically represent an object’s visual properties, which converts images into numerical values.
    • Matching and indexing: After extracting the features, they are compared with a database of product images to find similar or matching products. A process of indexing and matching is employed, which involves matching product visual characteristics with query image attributes.
    • Rank and present results: At the end, the user is presented with a ranked list of results based on the visual search. As a result of a mixture of search relevance algorithms and popularity algorithms, products may be deemed relevant depending on the search query, which takes popularity and similarity into account.

    Visual search can provide accurate and relevant results by leveraging multiple layers of analysis and processing.

    Improving Customer Experience With Visual Search

    Visual search appeals to users as it offers next-level personalization, ease of use, and speed. Research shows that 69% of shoppers frequently use the search function online, and more than 80% leave it due to poor experience. Visual search is poised as the right option to improve the search experience. 

    As a business owner, you must strive to make easy navigation and product discovery possible for your customers. This is where implementing visual search can offer a better experience to your customers.

    Finding a product is very easy with visual search. It is a truly seamless experience for the customer. Users can buy anything they see in the real world online in seconds. The Gen-Z is particularly eager for such speed and personalization.

    Moreover, searching for text information is not always convenient as users might not use the correct words or know a product name. Using artificial intelligence, visual search can provide better results in matching and finding products that match.

    The visual search feature also suggests to users other relevant products that may pique their interest. It enables customers to find various items, compare prices, or find similar products if their favorite has sold out.

    What Are the Most Promising Ways to Use Visual Search in E-Commerce?

    Know ahead that implementing visual search is not a piece of cake. It demands some effort from the business to embrace it completely. With visual search, you offer customers the convenience of shopping comfortably without having to scroll through endless product listings. 

    Here are some of the ways to integrate visual search into your e-commerce business.

    1. M-Commerce Integration

    As an e-commerce business, you must constantly link the online and offline worlds to boost e-store conversions in the omnichannel era. Visual search engines with mobile commerce capabilities are not fully streamlined yet, but they’re worth noting. They improve the conversion rate as the buyer journey is simplified. Rather than typing in keywords or scrolling down the page, your customers can upload images and instantly see matching results.

    1. Chatbot Integration

    A chatbot and a visual search engine can be a powerful combination. Implementing both can do wonders for your business if you aim to achieve swift and natural customer communications. Chatbots, coupled with image search capability, can make it easier for users to look up different products and services. 

    1. New-age Influencer Marketing

    Influencers post about different items they use, the places they visit, etc., and subtly encourage their audiences to purchase them at retail stores. However, the concept is often misused despite social media platforms developing tools that permit direct purchases from apps. Sometimes, it seems more like teleshopping than a natural way to motivate people. This can change with visual search; brands can make entire outfits shoppable at once, and users can browse similar options if inspired. Hard-sell tactics are less prevalent.

    What Can Visual Search Do for E-Commerce Businesses and Their Customers?

    There are numerous benefits to using visual search for e-commerce businesses, such as increased sales, higher customer engagement, and better user experience. Here are the key benefits of visual search!

    1. Increase in Sales

    Visual search technology for e-commerce businesses can increase customer engagement and sales by providing a simple and intuitive way to browse and discover items. This is because customers can discover products with a visual search that they wouldn’t have found with a text-based search alone. Moreover, customers can spend less time looking for products with this technology, improving their shopping experience and increasing their sales.

    1. Enhancing Customer Engagement

    Visual search can create a more engaging and personalized shopping experience for e-commerce businesses. The visual search feature helps customers find products based on their reference pictures, creating a more personalized and engaging shopping experience.

    1. An Improved User Experience 

    E-commerce websites and apps can benefit from visual search features by providing a smoother and more intuitive way to browse for products. An exhausted user does not want to spend hours searching for the right keyword at the end of the day. Visual search can make product browsing more enjoyable and seamless by reducing the effort needed.

    1. A Higher Conversion Rate

    Providing more relevant and accurate search results can improve conversion rates for e-commerce businesses. Using state-of-the-art search algorithms and image recognition produces highly relevant and accurate results.

    Examples of Visual Search in E-Commerce

    Let’s check out the key visual search examples that we find ourselves using quite often.

    Amazon

    In partnership with Snapchat, Amazon introduced a visual search feature in 2018. With Snapchat’s camera, you could scan objects in the real world and see similar items on Amazon. They launched a fashion-focused feature on its platform called StyleSnap a year later. With this StyleSnap functionality, users can take photos of styles (shoes, hats, clothing) and receive Amazon recommendations. So, you can essentially “Shop the Look,” as they call it.

    Pinterest

    Pinterest Lens allows people to develop ideas based on everyday life experiences. Google Lens and Pinterest Lens both offer a variety of benefits. The Pinterest search engine can identify over 3 billion objects in the fashion and home categories. The E-commerce search game was changed when Pinterest introduced a shopping tab on Lens. When users upload images of items, shoppable Pins will appear, displaying products in stock that match the image.

    Google

    Google launched Lens in October 2017, making it the world’s leading visual search technology company. Today Google Lens gets 3 billion searches every month. Google Lens is a reverse image search powered by artificial intelligence. Lens utilizes Google’s highly refined search intent algorithms to provide the most relevant answers. With AI advances such as the Multitask unified model or MUM, Google searches have become more complex and require even greater SEO knowledge and implementation.

    Bing Visual Search

    There is no doubt that Microsoft has followed the lead of its competitors in rolling out visual search. The Microsoft site allows you to scan an item, get a detailed description, and see where it can be purchased near you. There is no limitation on what can be used, such as clothing, flowers, brand names, logos, etc.

    Snap a picture, and AI will suggest relevant items based on your outfit that day, and you can move up from there.

    Best Practices for Effective Visual Search Integration

    The following are the best practices you can use to integrate visual search functionality into your e-commerce business effectively. 

    • Enhance the image quality: By using a high-resolution image, businesses can allow customers to recognize and match objects accurately. Using the visual search feature, a user can, for example, take a high-resolution picture of an item on the website similar to a red dress.
    • Implement clear product tagging: The tags businesses assign to each product must be relevant and comprehensive for precise search results. It is essential to use descriptive product tags, including “blue,” “shirt,” “men’s clothing,” etc., for products like blue shirts. Visual search can quickly identify the product if tagged correctly. 
    • Work on top-class User Experience (UX): Adding visual search functionality and accessibility to your platform’s UI encourages better engagement. The visual search button can be easy to use, or straightforward instructions can be provided on how to use it.
    • Utilize AI and machine learning: Machine learning and artificial intelligence algorithms enhance the relevance and accuracy of visual search results. Visual search features, for example, can improve the accuracy and relevance of search results. Techniques such as pattern recognition, color analysis, and object recognition can be included.
    • Perform optimization and A/B testing: Configuration rules can be set up, and tracking can be implemented for each placement. As a result of the data collected, retailers can adapt accordingly to achieve the desired results.
    • Practice, adjust, and observe: Your visual search feature can continuously improve by monitoring user feedback and tracking usage data. This information helps adjust the search results per the preferences and needs of its users.

    The Future of Visual Search for E-Commerce

    As visual search technology develops, the possibilities for e-commerce businesses are endless. There have been significant changes in visual search algorithms, which can recognize more sophisticated images and provide more accurate results.

    Virtual try-on and augmented reality (AR) are other trends in visual search. E-commerce businesses can enhance their customers’ shopping experience by providing immersive and personalized shopping experiences through augmented reality and virtual try-on technology. 

    The popularity of voice search technology is also increasing. As voice search improves in accuracy and popularity, retailers can optimize their stores to better respond to voice search queries, increasing their search ranking and making online shopping easier for customers.

    The following are a few key takeaways from visual search to understand its power better:

    A business that optimizes visual search will survive in the long run. By embracing this revolution, businesses can communicate their unique voice to the world and improve conversion rates.

    Verdict: Visual search Engine to Transform E-Commerce 

    Customers now have the opportunity to purchase anything they see on the streets or at home without having to type a single word or spend hours searching for the best deal or offer that may be relevant to their situation.

    Rubick.ai can help make your business visual-search-ready. We help brands improve their marketing strategies and strive for organic growth via our suite of AI-powered tools catered to e-commerce businesses. We streamline product data management and deploy SEO strategies to maximize your online visibility organically.

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