SCHAFFHAUSEN, Switzerland — April 2, 2013 —Tyco Retail Solutions (www.tycoretailsolutions.com), a leading global provider of retail performance and security solutions, and Planet Retail, a leading provider of intelligence on the global retail and foodservice industries, today announced details of a new webcast, “Science of Shopper Conversion” to be held on Wednesday, 17 April 2013. The complimentary, one hour webcast will highlight the findings of a new Tyco Retail Solutions’ sponsored trend report, and detail how brick and mortar retailers can gain valuable in-store shopper behavior intelligence by deploying a new generation of traffic intelligence solutions.
To register, please click one of the following buttons:
10 a.m. BST (5 a.m. EDT)
4 p.m. BST (11 a.m. EDT)
While in-store shoppers deliver valuable insights in the form of POS or loyalty card data, store operators feel an increasing need to better understand what happens before the purchase decision. Traffic intelligence solutions can close this information gap. Traffic intelligence solutions not only measure the conversion rate of visitors into actual buyers, but also are integrated with already existing in-store systems such as queue management and loss prevention, thus boosting efficiencies. This new research will also highlight how shoppers’ smartphones will play an increasingly important role in traffic intelligence in the future.
WHAT: Tyco Retail Solutions Sponsors “Science of Shopper Conversion” Webcast Hosted by Planet Retail
WHEN: Wednesday, April 17th at 10:00 a.m. and 4:00 p.m. British Summer Time (5:00 a.m. and 11:00 a.m. Eastern Daylight Time)
WHY: Attendees will gain greater understanding of the value of traffic intelligence and how retailers around the world rely on the technology to:
- Calculate conversion rates and better measure the success of promotions or new store layouts
- Integrate with incumbent in-store technologies to boost efficiency
- Consolidate information from multiple input sources to lay the foundation for sophisticated data analysis
Filed under Keywords Store Execution; Store Performance
Published on 3/28/2013 Permalink