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Smart Pricing in Retail
技术
- 分析与建模 - 预测分析
适用行业
- 零售
适用功能
- 销售与市场营销
服务
- 数据科学服务
挑战
欧洲一家领先的零售商拥有 3,500 多家门店和电子商务部门,由于价格被竞争对手压低而亏损。他们还发现,他们的客户群倾向于等到季节结束时才进行大幅降价,而且只会购买某些季节性产品,这扭曲了他们对未来如何进货的预测,并延续了定价问题。此外,他们很难有效地调整价格并保持门店和线上的一致 - 通常,这会导致定价不一致,尤其是当各个门店经理自行决定销售时。该零售商希望通过了解客户购买特定产品的决策因素以及哪种价格最能引起共鸣、轻松实时了解所有竞争对手提供的价格以及在门店和线上一致更新定价来改进他们的定价策略。
关于客户
客户是欧洲一家领先的零售商,拥有 3,500 多家门店以及提供送货上门服务的电子商务部门。这家零售商拥有数十万名员工和遍布多个国家的客户,始终走在大数据技术的前沿,以在不断增长的市场中保持竞争力。
解决方案
该零售商将 Dataiku 数据科学工作室 (DSS) 引入其数据团队的流程,以大规模整合预测分析。他们与 Dataiku 合作制作了一个最终数据项目,该项目考虑了竞争对手的定价,并将其用于预测模型中,以确定对于特定产品,整体业务是否可以支持该产品的激烈价格竞争。该解决方案利用 Dataiku 的 REST API 根据一组特定的预定义功能自动调整生产中的定价。它使用生产中的模型的实时监控来确保定价模型性能不会漂移,并且生产中的价格变化随时间推移都有充分的记录。该解决方案还包括一个基于预测定价模型的强大定价仪表板,可提醒并允许实体店对建议的价格变化或在线价格变化做出反应。
运营影响
数量效益
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.