CASE STUDIES

Sephora Case Study

Sephora started employing data collected through V-Count devices to gain more visibility into their operations and business cycles. Taking quick actions based on this data, the company has significantly increased conversion rates.

Samsung Case Study

Since the installment of the 3D Alpha+ Devices in January 2017 in-store conversion rates have increased more than 5% in Samsung Electronics stores.

TUMI Case Study

By identifying each store’s peak hours, Tumi has been able to optimize staffing, leading to a direct increase in conversion rate.

BENU Case Study

BENU managed to increase sales over 15% in several pharmacies in just one month.

Crocs Case Study

Crocs increased conversion rates by two points after reorganizing staff schedules using traffic data.

Samsonite Case Study

The company utilized footfall data combined with the rent paid per location and actionable insights provided via V-Count Business Intelligence Platform, to make critical business decisions.

ATU Case Study

V-Count assisted ATU in optimizing the staff according to occupancy rates enabled Istanbul Duty Free Shop to increase its conversion rate by 18.2% in the first year.

Türk Telekom Case Study

Türk Telekom is able to monitor 1000+ of their store operations and conversion rates on a single medium, V-Count Business Intelligence Platform.

Arçelik Case Study

Arçelik’s conversion rate has increased significantly since 2013, with V-Count’s retail analytics solutions, along with a boost in the sales volume and customer satisfaction.

DeFacto Case Study

Since the installment of V-Count solutions in January 2011 DeFacto’s in-store conversion rate has increased significantly.

Hatemoğlu Case Study

V-Count People Counting and Heatmap in-store analysis helped Hatemoglu, increase conversion rates, optimize personnel shifts and merchandising decisions.

JackRabbit Case Study

By leveraging V-Count’s suite of retail technologies, JackRabbit was able to monitor customer traffic more effectively. Data from people counters were analyzed to gain more in-depth insight into the sales potential of each store and, subsequently, evaluate performance at individual locations.

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