Artificial intelligence (AI) Trends in Retail

Artificial intelligence (AI) is being increasingly used in the Canadian retail industry to improve various aspects of the business, such as customer service, inventory management, and marketing.

Key Drivers of AI in retail

Some examples of how AI is being used in retail include:

  • Personalized product recommendations: AI-powered systems can analyze customer data, such as browsing and purchase history, to make personalized product recommendations to customers.
  • Chatbots: Retailers are using chatbots to provide customers with immediate assistance and support, such as answering product questions or providing information on store hours and location.
  • Inventory management: AI systems can analyze sales data and predict future demand to optimize inventory levels and prevent stockouts.
  • Predictive maintenance: AI-enabled systems can monitor and analyze data from equipment and machinery to predict when maintenance is needed, preventing costly breakdowns and downtime.
  • Fraud detection: AI-powered systems can analyze data to detect fraudulent activities such as identity theft, credit card fraud, and more.

Overall, AI is helping retailers improve efficiency, increase sales, and enhance customer service.


Services

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Service coverage

The variety, breadth, and depth of the projects where Arcus can be a resource are made unique by each client’s specific needs. By providing a very small sample of projects we’ve completed, we can help you understand how and when to use our services. Visit the links below to find out more about a specific problem or opportunity you would like to address.

Below is a sample of the range of services that Arcus has provided to clients.

  • A survey of 2,350 consumers and 1,320 business leaders for feedback on sustainability trends
  • Architecting a multi-year change strategy for a Fortune 500 company
  • Mentoring a CEO on organizational change
  • Excellence transformation of a leading B2B services company
  • Creating a new sales deployment model for a healthcare company
  • Developing a position evaluation and compensation model for a professional medical association   
  • Improving services to customer segments by deepening their understanding of customer attitudes


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