Top 5 AI Retail Use Cases

From its inception Artificial Intelligence has made our lives smarter and easier. When it comes to Retail commerce, AI is backbone. It’s proved that every retail sector is surplus by applying AI to it. In retail industry NLP (Natural Language Processing) is an AI application that plays an outstanding role in imparting human language to machines. Our blog explains how dynamic retail industry is through AI.

Juniper Research says retail machine learning will grow 230% between 2019 and 2023.

AI Use Cases in Retail

Computer vision is a new era in Retail which is a path to smart mirrors, neural networks for image search, virtual assistants, data science behind subscriptions, predictive analytics are best-use cases for Retail AI.

Computer vision for smart mirrors

Source : trendhunter

In fashion commerce a smart mirror is a game-changer. It is developing way we shop for our costumes and apparel. A smart mirror is a gadget a full display connected to AI, that works with software and computer vision algorithms. It looks like a classic mirror but is furnished with two-way glass and a smart mirror with integrated cameras. From a market research study by allied market research, in 2025 Smart mirror market will reach $4,118.7 million.

The screen works with augmented reality, feature extraction, object recognition and detection, and distortion correction. Computer vision is that end-users can’t notice what is behind a mirror. 

As smart mirrors interface makes it more accessible for sharing videos and images tied up with products. This frames UI to trip on more items and boost deals.

Neural networks for image search

Source: today.duke.edu

Every retail business has its rank of images. From returning to end-user, every deal ends with images. Neural network is a math tool. Here computer vision is a trick applied to neural network to image data. By that Computer Vision can admit images. 

For instance in an image a woman is walking in heels. It knows what type of heels she was walking with and sends same data to machine learning algorithms. In this part computer vision can see data, and machine learning can verify data.

When a neural network is framed it should be trained in supervised and unsupervised learning. This craves large data sets to find allies between images. Moreover image tagging has to be applied to pursue pictures in a text format. For this neural networks are used to tag or label images.

Data science behind subscriptions

Customized UI trend in retail business. NLP data is fixed and used in designing great UI. Retail technology is more exposed with subscription services. With this user data is collected and applied to user experiences to discover more products that a user is looking for. US music subscription revenue grew by $1.5BN in 2021 compared to 2020.

Most subscriptions are sorted out for collecting data on which products are sold and returned. Few surveys were crafted in UI for users to rate returned products. Few questions on total experience. With this data corps end which products are mainly sold what is denied, and how they can perk up total sales.

Predictive analytics 

A blend of tricks from analytics to machine learning and is a project that works with actual user data to show him looming carnival events. Predictive analytics takes hints from past events and programs a sample. So that corps can predict events for present and next year. 

A predictive algorithm is made to process this and it works with actual data. For instance an ecommerce store sells apparel of many fits. Here predictive analytics is applied with a recommendation engine showing best fit. It helps users to find best fit. Then they use these fit insights like what other users with exact fit have shopped and Viewed.

AI stylist

Source : smartfashion

It’s a virtual assistant to lift our fashion styles with latest trends. AI stylist magnifies best apparels that meet intention and reality. It works with a software agent offering services to users like voice command prompts. The process starts by decoding human input. 

AI records human voice and makes text and whole process is automatic speech recognition. In another way it works by taking images processing them in an application. It accepts commands from computer vision, recommendation engines, and access to all products on website.

Conclusion:

Artificial Intelligence is making retail industry more accessible by its capabilities. Companies have to invest more in retail AI to grow their business. With AI Retail use cases like Predictive Analytics, Neural Networks, AI Stylists, and Smart Mirrors retails companies get more profits,users and can decrease their pain points.

Author Bio :

Suresh is working as a Sr. Technical Content Writer at Visionify has skills in writing on Artificial Intelligence and Machine Learning. Visionify has experience in building production-ready Computer Vision Solutions that help companies apply computer vision in manufacturing. We develop scalable solutions around your niche. Our engineers work with you to devise most effective solution for your pain point and then build it from end to end. Our solutions are also user-friendly so that you can use our solution with no further tech knowledge.