Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Trax empowers brands and retailers to successfully navigate the evolving landscape of retail, where the integration of physical and digital experiences enhances shopper satisfaction at the shelf. By offering a comprehensive and precise method for consumer packaged goods (CPG) manufacturers and retailers to observe, measure, and assess shelf activity, Trax stands out as a leader in the field. The platform’s real-time monitoring and analytical capabilities provide insights into aisle dynamics, allowing for improved operational efficiency. When shelves are not well managed, it can lead to dissatisfied customers and lost revenue; however, retailers often lack the workforce to identify every issue immediately. With Trax, shelves are automatically scanned, conditions are analyzed, and necessary adjustments are prioritized to fully realize the potential of each aisle. This ensures that every product is optimally positioned in every store consistently. Furthermore, Trax Retail Execution leverages cutting-edge image-recognition technology and advanced deep-learning algorithms to digitize shelf data, ultimately driving sales growth and enhancing the shopping experience. By harnessing these innovative tools, retailers can create a seamless integration of their physical presence and digital strategy, leading to better overall performance.
Description
Veras Extend is an innovative Customer Experience Application designed to create a cohesive and integrated strategy for customer interaction. It features mPOS CheckOut Anywhere, which effectively serves as an additional register by leveraging CheckOut’s ERP, CRM, and payment systems. The platform is versatile, compatible with iOS, Android, and Windows devices, ensuring that associates have access to consistent pricing and promotions for streamlined operations. Users can conduct complete POS transactions or pause and resume them at a traditional register as needed. This system is ideal for use at offsite events or for easily adding another register in-store to accommodate customer demand. Veras Affinity Clienteling distinguishes itself with an ultra-responsive engine, allowing for real-time associate input that enhances data accuracy and trains the AI to generate more intelligent sales recommendations. The Endless Aisle feature opens up a world of possibilities by enabling associates to explore the entire global inventory, including numerous vendor catalogs, providing customers with information on product availability, relevant promotions, and suggestions for similar items while they shop. This comprehensive approach not only improves customer satisfaction but also significantly boosts sales potential.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Trax Retail
Founded
2010
Country
Singapore
Website
traxretail.com
Vendor Details
Company Name
Veras Retail
Founded
2008
Country
United States
Website
www.verasretail.com
Product Features
Retail Execution
AI / Image Recognition
Collaboration Tools
Data Collection
Inspection
Pricing / Placement Optimization
Product Education
Product Promotion Strategy
Retail Site Audit
Workforce Management
Product Features
Customer Experience
Action Management
Analytics
Customer Segmentation
Dashboard
Feedback Management
Knowledge Management
Multi-Channel Collection
Sentiment Analysis
Survey Management
Text Analysis
Trend Analysis