实例探究 > Improving Store Operations by Better Understanding Traffic

Improving Store Operations by Better Understanding Traffic

公司规模

1,000+

产品

RetailNext

技术栈

Advanced Analytics
Sensors

实施规模

Enterprise-wide Deployment

影响指标

Customer Satisfaction
Productivity Improvements
Revenue Growth

技术

分析与建模 - 预测分析
功能应用 - 远程监控系统
传感器 - 相机/视频系统

适用行业

服装
零售

适用功能

商业运营
销售与市场营销

用例

零售店自动化

服务

数据科学服务
系统集成

关于客户

One of the world’s largest apparel companies and a global leader in jeans, this iconic brand operates over 2,600 store locations and sells its products in over 100 countries around the world.

登录后查看完整内容

挑战

The brand was restricted in its efforts to optimize store operations and the shopper experience. Over 60 percent of its stores lacked any type of traffic counting solutions, even in the most fundamental form. What pre-existing traffic counting solutions the brand did have were inaccurate and unreliable. The solutions were standardized within regions, much less globally. The retailer wanted to improve its ability to calculate basic managerial metrics like conversion.

登录后查看完整内容

解决方案

First, RetailNext piloted advanced analytics in a newly relocated store. This delivered an accurate front door traffic counting solution to empower the calculation of conversion and other operational key performance indicators (KPIs). Secondly, RetailNext deployed sensors to include dwell zones and fitting room analytics, providing rich data on the effectiveness of product displays and the efficiencies of service areas at a very low incremental capital expenditure. RetailNext worked with the brand to establish baseline metrics on: Pass-by traffic, Pass-by capture rate, Store traffic, Average store traffic per day, Conversion, Average Transaction Value (ATV), Exposure (display traffic/store traffic), Dwell, Engagement (# of dwell/display).

登录后查看完整内容

运营影响

With the new metrics, the brand was able to identify clear opportunities to optimize store performance and shopper engagement.
Staff fitting rooms to align with traffic demand based on day of the week and hour of the day.
Focus on improving conversion on the three lowest-converting days (Sunday, Thursday, Saturday) from 7.2% to 8%, potentially resulting in a 5% increase in weekly sales.
Target an improvement in conversion during the three lowest hours of the day (1-2 p.m. and 6-8 p.m. during lunch and dinner), where a 0.3 point increase could lead to a 4.4% increase in sales during those hours.
Utilize effective signage and associate referrals to drive traffic and enhance engagement.

登录后查看完整内容

数量效益

Focus on improving conversion on the three lowest-converting days (Sunday, Thursday, Saturday) from 7.2% to 8%, potentially resulting in a 5% increase in weekly sales.
Target an improvement in conversion during the three lowest hours of the day (1-2 p.m. and 6-8 p.m. during lunch and dinner), where a 0.3 point increase could lead to a 4.4% increase in sales during those hours.

登录后查看完整内容