學門類別
哈佛
- General Management
- Marketing
- Entrepreneurship
- International Business
- Accounting
- Finance
- Operations Management
- Strategy
- Human Resource Management
- Social Enterprise
- Business Ethics
- Organizational Behavior
- Information Technology
- Negotiation
- Business & Government Relations
- Service Management
- Sales
- Economics
- Teaching & the Case Method
最新個案
- A practical guide to SEC ï¬nancial reporting and disclosures for successful regulatory crowdfunding
- Quality shareholders versus transient investors: The alarming case of product recalls
- The Health Equity Accelerator at Boston Medical Center
- Monosha Biotech: Growth Challenges of a Social Enterprise Brand
- Assessing the Value of Unifying and De-duplicating Customer Data, Spreadsheet Supplement
- Building an AI First Snack Company: A Hands-on Generative AI Exercise, Data Supplement
- Building an AI First Snack Company: A Hands-on Generative AI Exercise
- Board Director Dilemmas: The Tradeoffs of Board Selection
- Barbie: Reviving a Cultural Icon at Mattel (Abridged)
- Happiness Capital: A Hundred-Year-Old Family Business's Quest to Create Happiness
Machine Learning Algorithms to Drive CRM in the Online E-Commerce Site at VMWare
內容大綱
VMW is a leader in software virtualization with approximately USD 6.5 billion annual revenue. VMW sells Workstation that can be bought online (store.vmware.com) and is used for running Mac on Windows. Workstation forms a significant portion of store revenues and most of it is bought online. There is rich digital/clickstream data for the visitors which can be combined with their past purchase history and other offline features as well. The business would like to increase sales of the product by targeting the right customers and needs a propensity model to be built using machine learning that can target the right set of customers. Michael Butler, the WW head of the store wants to leverage Parag's data sciences team to help him target the right workstation prospects that visit the store. A business conversation between Michael and Parag is followed by a technical discussion between Ravi, the data scientist and Parag. The following are the key questions that Ravi seeks to answer: -Cross-validation and evaluation in the context of huge imbalance in the data -Feature selection techniques -Communicating internal results such as lift curves back to the business -Different modeling approaches that can be followed -Interpreting the results for business decision making