Growing Application of Artificial Intelligence in Retail industry

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September 19, 2022

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AI / Retail

WhatNext

Growing Application of Artificial Intelligence in Retail industry

The retail industry is a good example of how artificial intelligence can be used to improve the efficiency and profitability of an existing business. The most obvious way to do this would be to automate the repetitive tasks that are currently done by humans, such as stocking shelves or checking out customers. Another possibility is to use AI to help with customer service.

The first option is a bit more difficult to implement but can have a much bigger impact in the long term. It would reduce costs for the business as fewer employees are needed and should also increase profitability. The second option would be to use AI as a way to help employees provide better customer service. This might include using voice user assistants or chatbots to help customers with queries. By focusing on the needs of the customer, businesses can improve their conversion rates and decrease costs by not losing potential customers due to service delays.

Inventory Management Using AI

AI can also focus on inventory management. Currently, many businesses keep track of what they have in stock using a system that uses manual input. As you might expect, this can be a time-consuming process. AI might be able to manage inventory using a more advanced version of this algorithm: if you can define a set of criteria that can be used to determine whether an item has to be added to or removed from the inventory, then a computer program could check if the store has enough of an item without needing to contact the supplier.

Conversely, AI can be used to improve the efficiency of the supply chain. One of the main causes of inefficiency in the supply chain is at the warehouse level. Many businesses do not have the most up to date information on what they have in stock and how much it is worth.

Peak AI Ltd. is a company that is working on a solution to this problem. Using artificial intelligence, they are developing software that can scan product packages to determine their contents with 97% accuracy. This information could be used by businesses to better manage their inventory. For example, if the product package contains a bottle of wine, then the package can be scanned and the AI system can determine if the contents are more valuable as a wine bottle or an empty glass bottle. AI can help in increasing forecast and rebuying accuracy to drive profitability, avoid stock-outs, optimize inventory sell-through, and reduce wastage.

Sales Forecasting and Customer Engagement

Another area in that AI can make a difference in the retail business is the accuracy of forecasting sales. This can be done in a number of ways, the most obvious being to use AI to automatically generate sales forecasts. These forecasts could be used in a few different ways. The first would be to use them by themselves.

New York based Saggie uses AI and Big Data to forecast sales. Another startup Neuralytics provides AI-powered sales software that adds external data such as weather, traffic, and sports into the sales forecast.

AI-enabled chatbots can be used to interact with social media users to find out what they would like to see from your brand. Based on these requests, the chatbot can send you questions to ask your customers to better understand their needs and suggest products that customers may like.

Aigo.ai is a startup that is working on this exact solution. Aigo uses a chatbot to interact with customers on Facebook Messenger and Instagram. It uses customer conversations as the basis for product recommendations. By collecting reviews, you can improve product recommendations for your customers.

AI-enabled Sales Assistants

The AI-enabled sales assistant is another use case for AI. The sales assistant could be tasked with answering customer questions and providing personalized assistance. These assistants could also be used for support and to increase your overall conversion rates.

Pepper is a robot developed by SoftBank, which can be similarly used by businesses. Pepper can ask questions to customers and understand their needs. It can also browse products and answer questions about them.

Pepper is currently used in around 140 of SoftBank’s Japanese stores and has also been trailed in American stores. A small team of AI engineers from Amazon has also been experimenting with using Pepper to enhance the customer experience in Amazon stores.

Peapod is an online grocery delivery service, which uses AI to ensure their orders are correct. The company uses AI to identify the items ordered and also uses machine learning to recommend items that can be ordered together. Peapod is part of an online retail trend that uses cutting edge technology to disrupt the industry.

Conversica is a tech company that allows businesses to connect with their customers in a more personal way. Using AI and human experts, the company reviews customer messages and social media posts to determine the state of customer happiness.

AI in Warehouse and Logistics

As warehouses become more automated, they can also involve more use of AI. Imagine a warehouse with self-driving forklifts and a system that detects and routes around damaged unnecessary or dangerous items. Through the use of sensors and AI, items will no longer be piled on top of each other and packages will not be stacked too high.

Companies such as Amazon are already using technologies like AI and Robotics to manage their logistics infrastructure. Traditionally, for a package to be delivered, it has to pass through several human hands. With AI-powered logistic platforms, a package can be routed automatically, based on factors such as expected delivery date, current traffic conditions, or even a package’s temperature.

Using machine learning, Amazon’s technology can detect when items need to be picked, sorted, or packed and then assigns that job to a human or automaton.

Future of AI in retail

We are still in the early stages of AI being implemented into the world of retail. There are a few use cases in place and a few startups that are working on smaller-scale projects. The growth in AI and ML technologies will continue to boom in the coming years and you can be sure that we will start seeing this implement itself into the everyday world of online and offline retail.

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