Uncovering Factors Contributing to Inconsistent Conversion
Company Size
1,000+
Region
- America
- Europe
Country
- Brazil
Product
- RetailNext Traffic Sensors
- RetailNext POS Integration
Tech Stack
- Traffic Sensors
- POS System Integration
- Data Analytics
Implementation Scale
- Departmental Deployment
Impact Metrics
- Customer Satisfaction
- Productivity Improvements
Technology Category
- Analytics & Modeling - Predictive Analytics
- Functional Applications - Remote Monitoring & Control Systems
Applicable Industries
- Retail
Applicable Functions
- Business Operation
- Sales & Marketing
Services
- Data Science Services
- System Integration
About The Customer
A century-old luxury brand who sells products exclusively through an international network of authorized dealers, jewelers, and some 400 company-owned boutiques, this brand has become world-renowned as it shares its stories of preservation and opulence.
The Challenge
Consistent traffic, but also consistent lulls in conversion. In-store analytics showed consistent traffic at an international airport location, but revealed consistently low conversion at specific times and days of every week. The retailer was interested in using in-store analytics to better understand what factors were contributing to the consistently under-performing periods of time.
The Solution
RetailNext deployed traffic sensors at the front entrance of the retail location to measure traffic, and integrated the Point-of-Sale (POS) system to accurately calculate conversion. However, nothing in the correlated data pointed to an obvious cause-and-effect relationship. Then, RetailNext examined arriving and departing flights within the same time frame as the lower-than-normal conversion periods, and the deeper analysis revealed that the periods with lower conversion coincided with flights to and from Brazil. The retailer realized the store lacked a Portuguese-speaking sales associate at those critical times.
Operational Impact
Quantitative Benefit
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