How is Artificial Intelligence transforming the Future of Retail?
Retailers are increasingly leveraging Artificial Intelligence (AI) to enhance both customer and employee experience. AI is enabling them to have access to heaps of data that can enhance efficiency, speed, and business decisions.
The global annual spending on AI is expected to reach 7.3 billion by 2022.
Technologies including image classification, optical character recognition, object detection, human pose estimation and activity recognition are already helping retailers enhance retail experience.
Here are a few significant ways in which AI is helping the transformation of the retail industry:
Inventory Management
AI-enabled inventory management can help retailers optimize pricing, supply chain, promotions, and human resources. Computer vision systems can instantly scan the entire inventory to detect objects on the shelf. It can notify about any product shortage or sale in the future. It can also generate heat maps to help you do better product placement and forecast surge in product requirement during the peak hours. Inventory management can also forecast the amount of time a product may stay on the shelf.
Retailers can also leverage computer vision to develop autonomous robots that can help in stock replenishment.
Cashier less checkouts
Computer vision and big data analytics have helped retailers transform traditional shopping into smart shopping. A cashier less retail store leverages a combination of multiple cameras, loT sensors and computer vision-based systems.
A cashier less checkout enables shoppers to buy and pay for the product without any intervention from a human cashier. Retail outlets may use a smart shopping cart and a mobile app to ensure a seamless experience.
Cashier less checkout can help in reducing the waiting time and decrease the money spent on human resources. Retailers can also collect and analyze heaps of data to enhance customer experience and supply chain.
Suspicious Activity
AI-enabled systems can analyze CCTV footage and alert the retail staff of any suspicious activity happening within the retail store premises. Computer vision-based systems can help in theft detection by analyzing the movement and behavior of both staff and customers. It can also be used to identify physical assault and any other illegal activity. This can help to enhance the security and safety of the store.
Better product placement
Image recognition can help retailers efficiently track fast-moving goods and audit product placement through computer vision. It can also help to analyze the goods that are in demand and sold faster than other products in the retail store. This gives retailers enough information about when to re-stock and what products need to be placed as a priority.
AI-based image recognition can also instantly identify empty shelves and alert staff to replenish products with the exact location of the shelf and SKU (stock keeping unit). It saves a lot of time and ensures a better customer experience.
Dwell time and gaze time
Retailers are using AI technology to track the dwell time of customers. It can help in enhancing the overall customer experience and can help in boosting conversion rates of specific products.
Dwell and gaze time can help retail businesses understand how customers interact with different products. Actionable data insights can help businesses make data-driven decisions that can ensure more products are bought from the shelves. It can also help retailers deliver a more personalized experience based on age group, gender, and niches.
Crowd analysis
Crowd analysis leverages object detection, face mask detection, pressure mats, thermal and video counters to keep track of customers. However, retailers need to place high quality CCTV cameras with good lighting to ensure it works effectively.
Retailers can collect footfall data by detecting entering and exiting customers. It can help in analyzing why customers want to buy a particular product through reaction to a particular product and overall behavior inside the retail store.
It can also be leveraged to more efficiently manage queues, change staff, and generate analytical data to improve retail management.
Optical Character Recognition for retail
Optical Character Recognition (OCR) leverages computer vision to transform written receipts, text, and other manual documents into digital form. It helps machines to scan, read, and apply natural language processing (NLP) algorithms to meaningful data efficiently.
It enables easier storage, searching, and editing of data while streamlining the return and invoice process. OCR can also be used to create templates for invoices without having to interact with users. It can also help in accelerating services like “click and collect” by expediting collections and ensuring customers don’t have to wait unnecessarily.
The end-to-end automated process also generates a huge amount of data that can be analyzed to understand customer behavior and offer better products throughout the year.
How can Quality Engineering help the retail industry embrace AI?
With complex software embedded in every step of the business process, it is business-critical to ensure the reliability, security, and efficiency of AI-based systems in the real-world scenarios. Robust quality engineering (QE) can help businesses leverage AI-enabled systems and applications cost-efficiently and reliably.
Leveraging QE services from reliable and capable independent vendors can ensure end to end security, smoother scalability, and desired performance. QE can also help in enhancing the overall customer experience and enabling retailers to mitigate business risks cost-efficiently.
Wrapping Up
AI will transform the way retailers do research about products, pricing, and inventory management. It will also transform the shopping behavior of customers. Artificial intelligence has already become an integral part of big retailers to facilitate more engaging customer experience. Retail outlets are using cameras and sensors to learn more about customers through dwell and gaze analysis. Theft and other malpractices are being curbed through image detection and cashier less checkout have become a norm with some of the major retail brands including Amazon.
AI’s efficiency, accuracy, and predictive capabilities are poised to make retail stores smarter and more cost-efficient. With better shelf and inventory management along with lesser requirements of human resources, retail outlets can break even faster and generate more sales on a regular basis. AI can help retail stores become more self-sufficient, smart, and responsive towards customers.
