Six Key Growth Strategies for Shopping Malls with the Help of AI
The pandemic has severely impacted physical retail foot traffic and caused supply chain issues. As the industry has emerged on a post-pandemic recovery path, other non-pandemic-related issues, such as rising gas prices and inflation fears are slowing the recovery process. Moreover, post-pandemic, consumers have changed and may never shop the way they once did. With many consumers shifting to e-commerce, shopping malls are looking to reinvent themselves and create new experiences and a modern, sustainable, multi-purpose environment.
With the help of customer behavior and shopping mall analytics, shopping malls can now access in-depth insights to gain a competitive edge and give the customers a better shopper experience.
Thanks to advancements in machine vision technology and the development of affordable sensors shopping centers can utilize some of the analytics methods previously only available to e-commerce stores.
AI-based sensors provide data that help to control and improve the customer journey and define popular places in the shopping mall to place, for example, new kiosks or advertisiment displays. AI analytics helps manage overcrowding, which gives a competitive edge to shopping malls as a safer place in the current post-pandemic normal.
With mall visitor analytics, mall owners can do better mall layout planning, gain targeted tenant mix, and market activities more accurately. The tenants – retail stores or restaurants, can increase visitors, conversions, and sales opportunities.
In this presentation, we discuss six key customer analytics metrics acquired with modern AI sensors and related growth strategies for each metric. Click below to access the presentation.
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