RetailNext

Description

RetailNext is a leading AI retail analytics platform designed to deliver comprehensive in-store intelligence to retailers worldwide. With a presence in over 100 countries and trusted by more than 600 retailers, RetailNext provides a robust suite of tools to analyze shopper behavior, optimize store operations, and enhance customer experiences.

The platform offers traffic analytics that accurately counts shoppers, connects traffic data to transactions for true conversion insights, and provides AI-driven staffing recommendations. RetailNext's asset protection features help reduce shrinkage and protect margins by identifying anomalous shopper behavior patterns and linking video data to events.

RetailNext's Pulse AI delivers actionable insights tailored to various roles within a retail organization, from store managers to executives. It offers proactive coaching and advice based on store data, ensuring teams focus on the most impactful areas.

RetailNext integrates seamlessly with existing POS, workforce management, and BI tools, allowing traffic and conversion data to flow into systems already used for scheduling and reporting. The platform is built on the Aurora® sensor, which provides 95-99% accurate people counting and is manually audited for accuracy.

RetailNext's pricing model includes full platform access, software licensing, and updates, with additional costs for installation and professional services. The platform supports GDPR compliance and ensures customer privacy by measuring shoppers anonymously.

RetailNext is ideal for retailers looking to make data-driven decisions, optimize staffing, and improve conversion rates. Its comprehensive analytics capabilities provide valuable insights that drive operational excellence and enhance the overall shopping experience.

RetailNext's Core Features

• AI-powered foot traffic analytics

• 95-99% accurate people counting

• AI-driven staffing recommendations

• POS and BI tool integration

• GDPR compliance and privacy controls

• Real-time dashboards and predictions

• Video-linked event data for asset protection

• Cross-store benchmarking

How to use RetailNext?

1. 1

   Configure: Set up Aurora sensors and integrate with POS

2. 2

   Analyze: Use real-time dashboards for insights

3. 3

   Optimize: Implement AI-driven staffing recommendations

4. 4

   Improve: Track conversion rates and operational bottlenecks

RetailNext's Use Cases

• Traffic Analytics
• Asset Protection
• Conversion Rate Optimization
• Staffing Efficiency
• Department-Level Insights

FAQ from RetailNext

• How accurate is RetailNext's people counting?

  RetailNext delivers 95-99% accurate people counting using the AI-powered Aurora® sensor, verified through manual audits and HD video validation.

• How does RetailNext integrate with existing systems?

  RetailNext integrates with POS, workforce management, and BI tools through standard APIs, allowing seamless data flow for scheduling and reporting.

• What is Pulse AI in RetailNext?

  Pulse AI provides actionable insights for various roles, offering proactive coaching based on store data to improve focus and decision-making.

• How does RetailNext ensure customer privacy?

  RetailNext measures shoppers anonymously, storing no personally identifiable data, and supports GDPR compliance with configurable privacy controls.

• What kind of ROI can retailers expect from RetailNext?

  Retailers can expect ROI from small, compounding gains in conversion, labor efficiency, and shopper yield, with examples of significant sales increases.

• How does RetailNext help with staffing optimization?

  RetailNext forecasts traffic and recommends staffing matched to predicted demand, reducing labor costs without sacrificing customer experience.

• What additional costs may apply with RetailNext?

  Additional costs may include installation, site surveys, professional services, hardware shipping, sales tax, and import duties.

• How does RetailNext handle department-level analytics?

  RetailNext provides traffic, conversion, and engagement data for each department independently, allowing benchmarking and optimization.