The Retail Technology Advancements strategies combine data with user experience principles to transform casual browsers into paying customers. It involves a mix of tactics including reminders to fill shopping carts, effective visual online merchandising and calls to action, and targeted promotions that encourage conversions or repeat purchases.

Increasingly, shoppers expect to be able to find products that fit their unique preferences and needs. To meet these expectations, retailers must focus on personalization – a strategic approach that requires the right tools and expertise to drive sales.

Intelligent merchandising uses emerging technologies like AI to automate routine tasks and improve the effectiveness of in-store and online product positioning, promotions and marketing.

The Future of Retail: How AI is Revolutionizing Merchandising

For example, AI can help retailers understand shoppers’ behavior and purchase histories to better anticipate their needs. It can also provide a deeper understanding of how products interact and are purchased together, enabling cross-sell and up-sell recommendations that are relevant to the consumer without annoying them (recommending things they don’t need) or losing them (not recommending anything at all).

AI also helps with demand forecasting by looking at huge datasets like historical sales, market trends, competitor pricing data, weather patterns and even Google search queries, to predict future trends and price fluctuations with remarkable accuracy. One American department store retailer used Pluto7’s Gen AI merchandising software to achieve 85% demand accuracy, which significantly reduced inventory holding costs and increased sales.

AI can also reduce the time spent preparing for and managing promotional campaigns by leveraging dynamic digital shelf images to deliver immediate, real-time guidance to field reps. This process, called Best Shelf Action, improves compliance and reduces out-of-stock issues. To be successful, however, AI merchandising tools need high-quality labeled data to perform these functions. To solve this problem, companies like Taskmonk offer solutions that leverage the power of AI to improve the speed and quality of data labeling.

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