From salt to satellite, products and services today have moved online. Most basic needs such as food, shelter and clothing have transformed into a click away on a smartphone screen. Businesses seek the help of new-age tools and techniques to cater to the global and larger audience base which came along with the internet era. Here, AI steps in and train machines to help e-commerce businesses handle most of the mundane and repetitive tasks and add value to both the organization as well as the customer.
NATURAL LANGUAGE PROCESSING
Product Recommendation
AI can make the process of searching for products and services on an e-commerce site easier for a user. Most of the time, this convenience is what customers look for in an online retailer as a differentiating factor. AI can recommend us products and help us to get this done by training algorithms to associate products with keywords. It turns the buying process efficient for the customer and drives sales for the business.
NATURAL LANGUAGE PROCESSING
Product Categorization
Ecommerce businesses thrive on the element of a wide variety of product and service options to choose from, which a traditional brick and mortar shop can’t provide. The business, at the same time, should make it easier for the consumer to find the product with minimal effort. Ever growing product portfolios make it very difficult to do this categorization manually. AI can categorize products automatically into predefined topics and help to automate this process as and when new products and categories get added.
NATURAL LANGUAGE PROCESSING
Product Review Moderation
Ecommerce sites use product review pages as a tool for customers to engage with the platform and provide feedback. The website has no control over the way customers can respond to good or bad products, but it can choose which reviews to be displayed on site. It is important to make sure that no inappropriate language or content is posted on the product review page. This can be ensured and screened by the Natural Language Processing capabilities of AI.
COMPUTER VISION
Image-Product Tagging
Visual representation is the most efficient way to attract the consumer’s attention. Especially in e-commerce since it lacks the advantage of touch and feels provided by physical stores. The images and product description should match to avoid customer confusion and the quality of images should match the standards set by the website. You can train the system through ML to tag specific descriptions and keywords with images and to verify the quality of those images simultaneously.
COMPUTER VISION
Personalized Discovery
Customers spend a lot of time in ineffective keyword searches for products that they wish to purchase, leading to reduced product discovery. E-commerce platforms implementing a visual search function, powered by Computer Vision, enables shoppers to take a photo or upload an image of an item of interest. AI analyzes the attributes of the item and can recommend similar products in their online and offline stores. This recommendation engine can be further enhanced using options to narrow down the search results by personal preference. AI ensures customers find exactly what they are looking for each time they visit the platform, greatly increasing sales revenue and opportunities to provide further product recommendations.
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