Built for Modern Retail Teams Who Need Speed, Scale, and Accuracy
Dragonfruit's robust Foot Traffic & Dwell Time Analysis AI agent delivers powerful traffic and dwell analytics without the bloat:
- No extra hardware required. Works with your existing cameras and VMS
- Understand layout, window, and fixture performance
- Built for teams. Visual dashboards made for marketers, CX, and retail media
- Start simple and expand as your needs evolve
- Lowest TCO in the industry. More value than traditional counters or bulky AI platforms

Powering Smarter In-Store Decisions. See How
The Traffic & Dwell Time Analysis Agent delivers fast, actionable visibility — helping teams optimize merchandising and prove in-store promotion performance with confidence

Traffic Volume & Peak Time Trends
Know When and Where Shoppers Show Up
- Identify peak traffic hours by day, week, or campaign
- Compare entrances or storefronts to find top-performing zones
- Share high-level traffic reports with ops, and marketing teams—customized by week, month, or year

Dwell Time Insights
See Where Shoppers Stop and For How Long
- Measure how long shoppers linger at displays, windows, and key promos
- Identify what’s capturing attention and what isn’t
- Optimize merchandising using real shopper engagement data
- Visual summaries make it easy to spot what’s working

Flexible View & Setup
Customize What You Monitor, Down to the Display Window
- Set up views for entrances, walkways, and display windows
- Use built-in tools and spatial filters to define areas of interest, no extra hardware needed
- Adapt setup to fit any store layout

Engagement Reporting
Turn Shopper Behavior into Shareable Insights
- Summarize traffic and dwell trends in clear, visual reports
- Break down how window displays, signage, and promos are performing
- Share tailored insights with marketing, CX, and Retail Media customers.
- Compare performance by store, time period, or campaign
Built for Scale, Designed for Flexibility
Grow from foundational traffic insights to full-store intelligence—one modular layer at a time
