地区
- Europe
国家
- Germany
产品
- IBM PureFlex System
- IBM Storwize V5000
- IBM Watson Content Analytics with Enterprise Search
技术栈
- Social Media Analytics
- Content Analytics
- Enterprise Search
实施规模
- Enterprise-wide Deployment
影响指标
- Revenue Growth
- Productivity Improvements
- Waste Reduction
技术
- 分析与建模 - 预测分析
- 分析与建模 - 实时分析
适用功能
- 销售与市场营销
- 商业运营
用例
- 需求计划与预测
- 补货预测
服务
- 数据科学服务
关于客户
media control GmbH 总部位于德国巴登巴登,专门为客户提供媒体信息,例如电视收视率、图书销售、影院访问量和音乐排行榜数据。该公司希望通过帮助出版业公司找到更明智的经营方式来吸引更多公司的业务。出版商实现更高盈利的关键方法之一是将印刷量与销售额相匹配。
挑战
出版商面临着严峻的挑战。如果他们印刷的书籍数量超过人们购买的数量,他们就会浪费金钱,库存过剩。但如果印刷的书籍数量太少,他们就会错失收入。为了避免书籍数量过多或过少,媒体控制开发了一种最先进的社交媒体监听工具,帮助出版商准确预测每种图书的需求。
解决方案
通过与 IBM 顶级业务合作伙伴 PROFI Engineering Systems AG 合作,media control 开发了一款先进的社交媒体分析工具,该工具基于先进的 IBM Watson Content Analytics 和 Enterprise Search 软件。为了支持该解决方案,PROFI Engineering Systems 还帮助 media control 部署了连接到 IBM Storwize V5000 存储设备的 IBM PureFlex System。该社交媒体分析工具持续扫描超过 100,000 个网站,在在线论坛、博客和新闻网站上搜索有关书籍、作者和出版公司的相关用户评论和信息。
运营影响
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
Gexa Energy and AutoGrid's Innovative Demand Response Programs in ERCOT
Gexa Energy, a leading retail electricity provider in Texas, was seeking to introduce new demand response programs for its commercial and industrial customers in the Electric Reliability Council of Texas (ERCOT) market. The challenge was to provide a platform that would allow these customers to lower their energy bills by adjusting their energy consumption during peak energy demand or high wholesale electricity prices. The solution needed to be intelligent, scalable, and offer both manual and automated options for adjusting energy consumption. The demand response programs needed to include Emergency Response Service (ERS), Real-Time Price Response (RTPR), and 4 Coincident Peak (4CP).
Case Study
ZettaNet's Agile Juniper Network Meets Booming Digital Demand in Australia
ZettaNet, a privately-held company based in Perth, Australia, was facing a significant challenge due to the exponential demand for enterprise network, data center, and cloud services in the region. The company's business growth necessitated an upgrade of their core network to meet the increasing bandwidth requirements of their customers. The customers, which primarily include managed service providers, were demanding 1 Gbps connectivity between locations. These service providers then deliver network, data center, cloud, and voice services to a diverse range of customers including local businesses, schools, hospitals, residential communities, and government offices in Western and Southern Australia. The challenge for ZettaNet was to meet this high-capacity network services demand while maintaining profitability.
Case Study
Edge AI: Deploying AI Flexibility in a Virtualized LV/ MV Substation
Cuerva a Spanish Grip Operator, was seeking to enhance grid knowledge through the implementation of the AI Energy Forecasting Model to obtain precise forecasts of user demand and energy generation.Cuerva’s grid encompasses over 16,000 diverse supply points, making cloud-based operations intricate and susceptible to issues such as connectivity loss, delays in information transmission, and reliance on centralized infrastructure, which can result in the loss of critical data.To tackle these challenges, the Edge technology has proven to be the sole alternative capable of addressing these issues effectively. It ensures real-time data access and operates in a decentralized manner, minimizing the impact of device failures on the overall functionality of the network.In this successful case, we illustrate how with Barbara DSOs can implement AI directly in substations to accurately predict the demand and production values of consumers linked to the transformation center where an Edge node run by Barbara has been deployed.
Case Study
MISA's Success in Achieving 50% Query Deflection Rate with Freshdesk
MISA, an online fashion retailer, faced a significant challenge in managing customer support and communication during the COVID-19 pandemic. The shift in consumer behavior towards online shopping led to an explosive growth in digital footfall, increasing MISA’s average number of orders from 30-50 a day to about 70-100 a day. This surge in orders resulted in higher support volumes, with customers frequently enquiring about their orders and delivery status. The team struggled to prioritize issues as their existing email systems ordered conversations based on the latest response rather than the urgency of the queries. Additionally, the shift to remote work due to the pandemic raised concerns about effective team collaboration and communication. MISA also faced the challenge of dealing with repetitive customer queries, which were time-consuming and redundant.
Case Study
Designing an intuitive UI for effective product demand forecasting in retail
The client, a leading luxury store chain operating in over 100 countries, was facing challenges with their product demand forecasting process. The process involved a significant amount of manual work, with all sales-related data being kept in Excel tables and calculated manually. The client's merchandising and planning experts used a demand forecasting web application to make estimations of customer demand over a specific period of time. The solution calculated historical data and other analytical information to produce the most accurate predictions. However, the client wanted to improve the efficiency and effectiveness of this process, making it faster, more accurate, and less complicated for their employees. They sought to unify all processes under an intuitive UI.
Case Study
Book Creator: Transforming Education through Digital Book Creation
Book Creator, a self-publishing tool, aimed to shift its focus towards serving the K-12 market and enhance student engagement by unlocking their creativity. The company wanted to provide a platform where students and teachers could collaboratively create and publish ebooks and learning materials. However, with a small team of 13, they faced the challenge of reaching millions of students and handling high-variability workloads. Additionally, they needed to comply with strict data access management requirements including GDPR in the European Union and FERPA/COPPA in the U.S. The company also wanted to rapidly develop new features while reducing the complexities of storing data and scaling access to it.