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AI In Retail - A Paradigm Shift

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Posted on Jul 07, 2021
by Karan Ahluwalia ( Business Development Executive)

AI In Retail - A Paradigm Shift

Retail business is growing at an astonishing pace keeping the customer at the heart, spoiling them with jaw-dropping deals and effective payment options. Customers have slowly begun narrowing down their choices to connect with brands that in turn connect with them and provide them with personalized shopping experiences. This new age of customers expects the best shopping experience, that involves minimal efforts, and at the lowest cost. They want their favorite brands to be familiar with their preferences so that they can save time on unnecessary data entry points and have a seamless checkout experience.

Why is there a need of Artificial Intelligence (AI) in Retail?

Artificial Intelligence (AI) and Machine Learning (ML) have introduced a whole new level of shopping experience for customers looking to connect with their favorite retail brands. Every area in the retail business can be automated with the help of AI thereby increasing efficiency, accuracy, and customer satisfaction. With the help of AI, retail businesses can formulate data models to extract meaningful insights. This would further help them in efficient forecasting and make better data-driven decisions.

According to International Data Corporation, the Global AI market is expected to break the $500 billion mark by 2024 with a five-year compound annual growth rate (CAGR) of 17.5% and total revenues reaching an impressive $554.3 billion.

Let us take a deeper dive into some of the top use cases of AI in Retail:

  • Cashier-free stores
    The AI-enabled automation of store counters have helped in reducing customer queues, lowering the staff, and hence saving on operational expenses. Major retail giants have already adopted AI-based systems to automate the shopping experience of their customers which has helped them overgrow their business.
  • Conversational Support
    AI-enabled chatbots use natural language processing (NLP) to provide an unmatched level of customer service. They play an important role in providing suitable recommendations, answer product-related queries, and even cross-sell products based on past purchases.
  • Visual Curation
    AI-powered visual search systems enable customers to upload images and search similar products based on various categories. This is achieved with the help of image recognition (IR) technology. Recently developed IR-based systems promise a minimum of 90% accuracy in helping customers find the product they need and even provide recommendations on additional products.
  • Voice search
    Major retail brands have adopted Google or Amazon AI technology to help their customers use voice command for their shopping experience. Amazon's Alexa is widely used by customers across the globe and helps them track their product orders with the help of voice search.
  • Stock Management
    AI can help retail businesses manage their inventory by calculating the demand for a specific product. This is mainly done by considering history of sales, trends, promotions, and other factors. Retailers can eliminate the cases of leftovers and out-of-stock scenarios to a great extent with the help of AI.
  • Demand Forecasting
    Extracting insights from marketplace, customer, and competitor data, AI-based business intelligence tools can help retailers forecast demand trends and eventually make proactive alterations to their marketing, production, and overall business strategies.

With the help of a team of industry-led experts, Aress can design, develop, and deploy Artificial Intelligence and Machine Learning-based products and solutions to help your retail business achieve greater heights along with giving your customers a revolutionary shopping experience. We have already developed some ready-to-deploy AI models, chatbots with the help of Optical Character Recognition (OCR) and NLP technologies to address specific business objectives. Feel free to get in touch with our experts for a free consultation or visit for more details.

Category: Data Analytics, RPA & AI

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