下载PDF
BrewDog's Customer-Centric Approach in Times of Uncertainty
技术
- 网络安全和隐私 - 身份认证管理
- 传感器 - 自动驾驶传感器
适用行业
- 电子商务
- 零售
适用功能
- 销售与市场营销
用例
- 零售店自动化
- 时间敏感网络
挑战
由于越来越多的人呆在家里并在线订购啤酒,BrewDog 面临着客户服务活动的增加。他们还必须处理有关社区和企业社会责任项目的一般联系和问题。 COVID-19 大流行加速了客户服务流程变革和自动化的需求。
关于客户
BrewDog 是一家诞生于苏格兰的精酿啤酒公司,在全球拥有 100 家酒吧。他们有一个由股东、朋友和客户组成的社区,被称为“股权朋克”,他们对精酿啤酒充满热情。 BrewDog 旨在提供个性化服务,重视客户透明度和创新。
解决方案
BrewDog 采用 Freshdesk 来管理其客户服务运营。他们专注于自动化以节省时间和精力,使用 Freshdesk 的功能来消除重复和手动任务。他们还利用 Freshdesk 的分析来识别趋势并提供反馈以改进其电子商务流程。 BrewDog 通过更新知识库文章和常见问题解答来增强其自助服务能力。他们优先考虑客户体验,并将客户服务渠道扩展至社交媒体平台。
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.