赢得价格战
公司规模
1,000+
地区
- America
- Asia
- Europe
- Middle East
国家
- United States
- Worldwide
产品
- JDA Demand
- JDA Travel Price Optimization
技术栈
- Demand Forecasting
- Price Optimization
实施规模
- Enterprise-wide Deployment
影响指标
- 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
适用功能
- 商业运营
- 销售与市场营销
用例
- 需求计划与预测
- 补货预测
服务
- 系统集成
- 培训
关于客户
卡尔森酒店集团是一家全球性的酒店公司，在服务和质量方面享誉全球。该公司在竞争激烈、价格驱动的环境中运营，并不断寻求脱颖而出并最大化收入的方法。尽管卡尔森酒店集团拥有强大的市场地位，但它认识到需要一种更复杂的方法来将价格与实际需求相匹配，以优化其收入。该公司希望不仅根据入住率来衡量其成功，还希望根据个人预订产生的收入以及在低需求周期报出更高价格而导致的“错失机会”的价值来衡量其成功。
挑战
由于市场透明度和互联网预订的快速增长，酒店业正面临一场新的价格战。这给包括卡尔森酒店在内的酒店运营商带来了重大挑战，他们一直在寻找在这种竞争激烈、价格驱动的环境中脱颖而出并实现收入最大化的方法。传统的收益管理只有在市场条件导致售罄晚数减少时才会偶尔有效。卡尔森酒店发现需要一种更复杂的方法来将价格与实际需求相匹配，这样他们就可以不仅根据入住率来衡量他们的成功，还可以根据个人预订产生的收入以及在低需求周期报出更高价格而导致的“错失机会”的价值来衡量他们的成功。
解决方案
Carlson Hotels 向 JDA Software 寻求一种截然不同的方法。他们启动了一项名为 SNAP（住宿晚数自动定价）的新收入优化项目，使用 JDA Demand 和 JDA Travel Price Optimization 为酒店经营者带来更高的收入。Carlson Hotels 现在能够量化价格弹性并使用该输出来生成最优价格，将竞争对手的数据引入其收入管理系统并预测客户对价格变化的反应。JDA Demand 提供了强大的预测功能，使 Carlson Hotels 能够更快地对需求或竞争价格的变化做出反应。通过将 JDA Demand 与 JDA Travel Price Optimization 相结合，Carlson Hotels 能够从基于产品和对竞争影响的猜测定价转变为基于需求预测和与实时竞争对手价格相比的价格弹性定价。
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
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.
