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Optimize store activity with predictive foot traffic

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Important

This content is archived and is not being updated. For the latest documentation, go to What's new in Microsoft Cloud for Retail. For the latest release plans, go to Dynamics 365, Power Platform, and Cloud for Industry release plans.

Enabled for Public preview General availability
Users by admins, makers, or analysts Jul 1, 2023 Sep 1, 2023

Business value

Retailers can benefit from foot traffic analysis in physical stores to achieve more innovative workforce planning. Retailers can allocate and optimize in-store tasks such as daily product replenishment based on predicted customer activity throughout the day. This feature helps retailers to optimize operations, and in turn, provide excellent customer service.

Predictive foot traffic analysis and insights through AI models would enable retailers to be proactive and not just reactive regarding their business measures and objectives. This investment aims to bring predictive analytics around workforce allocation and product replenishment using foot traffic data from autonomous stores and signals from external sources like events, weather, etc.

Feature details

The predictive foot traffic capability can:

  • Extend retail data template on Microsoft Azure Synapse to support relevant entities and attributes.

  • Plug into Microsoft Cloud for Retail Smart Store Analytics to:

  • Use data from autonomous stores and external sources through AI models.

  • Get insights to the Smart Store Analytics service using AI models.

  • Provide insights to consumers in the Smart Store Analytics UI.

See also

Foot traffic forecast (docs)