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    How AI is changing retail


    Business people know that retail is changing at an extremely fast pace. Driven by the global pandemic, regional conflicts, and other disruptions, leaders in the retail industry are looking to AI for solutions more than at any time before. AI systems and software applications have practical uses across retail departments and business functions. From reducing errors, to improving inventory efficiency, to increasing customer engagement, and improving staff management. This blog is going to tell how AI is changing retail for the better!

    State of Retail Sector and AI: 2022 Outlook

    Deloitte interviewed 50 senior retail executives for its “2022 Retail Industry Outlook” report. Respondents appear optimistic about revenue growth this year: Fifty-four percent expect growth of up to 5%, and 32% expect growth of 5% or more. In Addition, Meticulous Research® found that AI in the retail market is expected to grow at a compound annual growth rate (CAGR) of 34.4% from 2020 to 2027 and reach$19.9 billion by 2027.

    Retail Sector Growth

    Much of the growth in the retail sector corresponds to an increased understanding of AI, big data, and integrating advanced digital technologies. As a result, customers expect a seamless online shopping experience that leads to quick checkout, simplified product searches, and an overall better customer experience. As AI becomes more commonplace, we’ll likely see even more changes in the retail industry moving forward. The foundation of the retail industry is dependent on stable and reliable supply chains.

    AI & Supply chain management: Stable, Efficient, Predictive, and Future-ready!

    According to Throughput Inc: “Artificial Intelligence and Machine Learning (ML) drive visibility into all aspects of the supply chain and with granularity and methodologies that humans simply can’t mimic at scale.” This includes making decisions faster, lowering cycle times, speeding up operations, and enhancing continuous improvement.

    Supply chains compromised!

    Mark Minevich of Forbes writes “The issue facing many industries today, and retail, in particular, is “The supply chain,” the problem is that nearly every single link in the supply chain is compromised.” Supply chain disruptions do not just create higher prices and shortages among high-end consumer products, such as cars. They also influence more basic products such as food, medicine, and raw materials, increasing the cost of living.

    According to an Accenture report, “supply-chain-dependent businesses should aim for an operational maturity model, meaning: Stable, Efficient, Predictable, and Future-ready.” Moreover, the Covid19 pandemic has highlighted persistent challenges with the production and movement of goods worldwide. Consequently, supply chain resiliency will likely require significant change across the board to reach “maturity.” However, retailers can’t afford to wait: Eighty percent of executives surveyed believe consumers will prioritize stock availability over retailer loyalty in 2022.

    Retail Industry: How AI Has Changed the Shopping Experience

    Artificial Intelligence and Machine Learning

    Purchasing data can be used by machine learning (ML) algorithms to retail companies’ advantage. These programs suggest products for customers to buy and what inventory retailers need to replenish. ML collects current and past data reflecting the day of the week, season, nearby events, social media information, and past customer behavior when providing product or inventory recommendations. The information is easily applied to brick and mortar stores, and through online retail business.

    AI and Predictive Analytics

    Predictive analytics charts a customer’s path and gives retailers valuable insights into how prospects and leads move through a store as customers. This demonstrates where and how retailers may need to change this system to optimize future customer journeys. What’s more, predictive analytics assist in ordering the correct amount of inventory reducing errors and preventing over or under-ordering inventory.

    AI Supports Product Placement

    AI software can help retail stores place products in the right location by analyzing customer data and behavior patterns. Using these patterns, AI can access customer selections and preferences while keeping track of visits to the physical stores. This knowledge of customer shopping behavior ensures that customers can find the products they want and that retailers are not wasting time and money placing products in the wrong places. This provides a more personalized shopping experience and increases customer retention.

    AI Supports Pricing Strategy

    AI has made it possible for retailers to make informed pricing strategy decisions. For example, AI can help retailers develop the best price for their products by taking into account similar products, promotional activities, sales figures, and related data. Retailers can use AI to analyze this data to see what pricing strategy would be the most successful.

    AI Chatbots

    Three ways AI chatbots and predictive data help companies deliver a seamless customer journey:

      • Reduce the time it takes to answer customer questions.
      • Automatically recognize and answer multiple forms of the same question.
      • Collect necessary information that agents need to solve a case quickly.

    An example of a chatbot, Lowe’s: Robotic customer service aka, Lowbot. Lowbot is an AI-driven automated robot that answers customer questions and helps them navigate through stores. More common examples include AI-driven interactive chatbots that provide website customer service for several companies.

    Online Shopping

    Artificial Intelligence has completely changed online shopping, Amazon, for example, has become a household name in many countries. AI has made it easier for customers to find what they need and make more informed decisions about their purchases. Machine Learning takes in countless lines of historical data and tries to find patterns and trends and make accurate predictions for customers.

    AI and Retail HR Management

    There are many different ways that AI assists retail businesses in managing staffing issues. For example, AI can automate the onboarding process of new employees. This can include everything from scanning their documents to inputting their information into the system. AI can also be used to manage employee leave and absences.

    A prime example is: TimeWellScheduled.com , a leader in providing retail companies with software to manage business scheduling needs. Our software:

      • Simplify the scheduling process
      • TimeWellScheduled makes building your schedules easier and faster.
      • Spend your valuable time on more important things
      • Optimize shift coverage during high and low business volumes

    AI is changing the retail industry for the better. Its ability to quickly and accurately make decisions allows retailers to streamline their operations and make more informed choices about inventory, pricing, and customer service. In addition, AI can also create a more personalized shopping experience for customers. By analyzing customer data, AI can figure out what products each individual is likely to want and recommend those products. This level of personalization is sure to improve customer engagement and encourage them to return again and again. Finally, AI supports store management, by reducing and automating administrative tasks and optimizing scheduling to meet business needs.

    Interested in learning more about Scheduling optimization. Visit us at: TimeWellScheduled.com

    Start using TimeWellScheduled today

    TimeWellScheduled is a team management solution for retail businesses. We provide a full suite of team and time tools designed to save you time and improve productivity.