AI for Retail: Game-Changing AI technologies that are transforming Retail sector
AI is enabling retail systems to work together to optimize customer experiences, forecasting, inventory management, and more. AI technologies like computer vision bring near-real-time intelligence to brick-and-mortar stores.
By using computer vision in retail businesses can change their customer experiences. Computer vision can enable retailers to accelerate many business operations such as shelf management, payments, data gathering, and compliance. This technology can also use connected cameras for monitoring retail stores, spotting suspicious behavior, and deterring theft. This framework will help retailers enhance security in their stores. Retailers may use these technologies along with these applications for promotions and sales in-store. For certain business processes, therefore, retailers should consider using computer vision.
1. Product Recommendation systems:-
One of the key differentiators for Amazon is its AI-powered recommendation engine that suggests products that customers may want to buy based on previously purchased products and their demographic information. Recommendation engines usually run on predictive analytics technology, which forecasts a historical data-based outcome. The predictive analytics algorithm forecasts in the case of recommendation engines that a customer may like a product based on historical data, demographic data, time of day, internet search data, and more.
2. Targeting consumers with Email Campaigns:-
Predictive analytics software could determine which email template to send to certain email subscribers based on data about their past opens and clicks, as well as demographic data the company may have on the customer through surveys and website activity. This could automate the process of manually creating segments of email subscribers and manually scheduling different emails for them to be sent. Instead, this could be taken care of by the AI software, sending the appropriate email template only to subscribers who meet certain data criteria.
3. Fraud detection:
To use anomaly detection software to prevent fraud, a company would have to install the software and allow it to run in the background to generate an idea of the falseness of the payment processor within the company. Then, if a payment goes through the payment processor of a company, an anomaly detection software could automatically flag that payment as potential fraud if it deviates from the average customer's purchasing behavior or similar deviations from the norm.
4. Chatbots
By way of natural language processing, AI could reduce customer service costs in the retail sector, a form of machine learning program capable of discerning the meaning behind the written or spoken word. Chatbots are the most popular customer service AI application but most of them are currently only able to handle very rudimentary questions. Site visitors can type their questions into a chat window, and with pre-written templates, the chatbot will indeed address that.
5. Security:
Brick-and-mortar retailers could leverage computer vision, a type of machine learning capable of analyzing images and video. Some retailers use computer vision for security purposes, pointing cameras to checkout lanes that can identify when store employees intentionally forget to scan items that they ring up; this is typically done by employees for people they know. Such AI-enabled cameras can also detect when customers fail to scan objects on self-checkout counters, or when they take products from shelves and conceal them on their bodies.
Conclusion:
There has been plenty of talk among retailers since the start of e-commerce about the benefits of experiential retail, providing consumers with an experience rather than just a product or service as a way to compete more efficiently. This has always been easier said than done – but retailers today do not need to make significant capital investments to build such new and unique shopping experiences.
