David’s Bridal Enhances Inventory Management and Forecast Accuracy with First Insight
公司规模
1,000+
地区
- America
国家
- United States
产品
- First Insight Platform
技术栈
- Direct-from-consumer valuation data
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Productivity Improvements
- Revenue Growth
技术
- 分析与建模 - 预测分析
- 功能应用 - 库存管理系统
适用行业
- 零售
适用功能
- 销售与市场营销
- 仓库和库存管理
用例
- 库存管理
- 补货预测
服务
- 数据科学服务
- 系统集成
关于客户
David’s Bridal, a prominent name in the wedding gown industry since 1950, has established itself as a leader in delivering fashion, value, and unparalleled customer personalization. With over 60 years of experience and millions of brides served, the company has become a go-to destination for brides in North America. David’s Bridal operates more than 300 stores, catering to over 60% of brides in the region. The company’s commitment to providing a wide range of wedding gowns and accessories has made it a trusted brand for brides seeking quality and style for their special day.
挑战
When introducing new dresses, David’s Bridal faced a significant challenge with a low forecast accuracy rate of 48%. The primary issue was the difficulty in aligning customer demands with product selection, leading to heavy markdowns and slow-moving inventory, which negatively impacted margins. Previously, the company tested samples of new styles in 10 stores before a full rollout, a process that was both expensive and time-consuming, adding approximately three months to the launch timeline. Additionally, this method risked biased results as sales associates tended to push new dresses harder than usual, skewing sales forecasts optimistically.
解决方案
David’s Bridal adopted First Insight’s platform to address their inventory and forecasting challenges. The platform provides inventory investment guidance and price point recommendations for gowns that have not yet been introduced to the market. By leveraging direct-from-consumer valuation data, the platform enables merchants to make more accurate buying decisions. Additionally, David’s Bridal uses the First Insight solution to gather input from store associates and compare it with consumer feedback. This approach allows the company to gain a forward-looking view of the most profitable dresses to source and bring to market within just 72 hours. The implementation of this solution has significantly improved the company’s ability to select the right inventory, leading to higher full-price sales and reduced dependency on markdowns.
运营影响
数量效益
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
相关案例.
Case Study
Improving Production Line Efficiency with Ethernet Micro RTU Controller
Moxa was asked to provide a connectivity solution for one of the world's leading cosmetics companies. This multinational corporation, with retail presence in 130 countries, 23 global braches, and over 66,000 employees, sought to improve the efficiency of their production process by migrating from manual monitoring to an automatic productivity monitoring system. The production line was being monitored by ABB Real-TPI, a factory information system that offers data collection and analysis to improve plant efficiency. Due to software limitations, the customer needed an OPC server and a corresponding I/O solution to collect data from additional sensor devices for the Real-TPI system. The goal is to enable the factory information system to more thoroughly collect data from every corner of the production line. This will improve its ability to measure Overall Equipment Effectiveness (OEE) and translate into increased production efficiencies. System Requirements • Instant status updates while still consuming minimal bandwidth to relieve strain on limited factory networks • Interoperable with ABB Real-TPI • Small form factor appropriate for deployment where space is scarce • Remote software management and configuration to simplify operations
Case Study
How Sirqul’s IoT Platform is Crafting Carrefour’s New In-Store Experiences
Carrefour Taiwan’s goal is to be completely digital by end of 2018. Out-dated manual methods for analysis and assumptions limited Carrefour’s ability to change the customer experience and were void of real-time decision-making capabilities. Rather than relying solely on sales data, assumptions, and disparate systems, Carrefour Taiwan’s CEO led an initiative to find a connected IoT solution that could give the team the ability to make real-time changes and more informed decisions. Prior to implementing, Carrefour struggled to address their conversion rates and did not have the proper insights into the customer decision-making process nor how to make an immediate impact without losing customer confidence.
Case Study
Digital Retail Security Solutions
Sennco wanted to help its retail customers increase sales and profits by developing an innovative alarm system as opposed to conventional connected alarms that are permanently tethered to display products. These traditional security systems were cumbersome and intrusive to the customer shopping experience. Additionally, they provided no useful data or analytics.
Case Study
Ensures Cold Milk in Your Supermarket
As of 2014, AK-Centralen has over 1,500 Danish supermarkets equipped, and utilizes 16 operators, and is open 24 hours a day, 365 days a year. AK-Centralen needed the ability to monitor the cooling alarms from around the country, 24 hours a day, 365 days a year. Each and every time the door to a milk cooler or a freezer does not close properly, an alarm goes off on a computer screen in a control building in southwestern Odense. This type of alarm will go off approximately 140,000 times per year, equating to roughly 400 alarms in a 24-hour period. Should an alarm go off, then there is only a limited amount of time to act before dairy products or frozen pizza must be disposed of, and this type of waste can quickly start to cost a supermarket a great deal of money.
Case Study
Supermarket Energy Savings
The client had previously deployed a one-meter-per-store monitoring program. Given the manner in which energy consumption changes with external temperature, hour of the day, day of week and month of year, a single meter solution lacked the ability to detect the difference between a true problem and a changing store environment. Most importantly, a single meter solution could never identify root cause of energy consumption changes. This approach never reduced the number of truck-rolls or man-hours required to find and resolve issues.
