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Show Notes
Data Mining Techniques (Gordon S. Linoff)
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#Directmarketingresponsemodeling #Customerdatapreparation #Associationrules #Collaborativefiltering #Survivalanalysis #DataMiningTechniques
Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management is a practical business analytics guide by Gordon S. Linoff and Michael J. A. Berry. Its third edition, published by Wiley in 2011, explains how organizations can turn customer, transaction, and interaction data into decisions that improve acquisition, retention, cross selling, service, and risk management. Rather than presenting data mining as an isolated technical discipline, the book frames it around recurring commercial questions: Which prospects are most likely to respond, which customers are likely to leave, what products tend to be purchased together, and how should limited marketing resources be allocated. The authors introduce a broad set of methods, from traditional statistical approaches to decision trees, neural networks, association rules, collaborative filtering, link analysis, and survival analysis. It is an introductory but applied work, emphasizing data preparation, evaluation, deployment, and organizational infrastructure alongside modeling. Its central purpose is to help business practitioners connect analytical techniques to measurable customer relationship management actions.
- Amazon USA Store: https://www.amazon.com/dp/B004UB2KE4?tag=9natree-20
- Amazon Worldwide Store: https://global.buys.trade/Data-Mining-Techniques-Gordon-S-Linoff.html
- Apple Books: https://books.apple.com/us/audiobook/data-mining-techniques-for-marketing-sales-and/id1643287418?itsct=books_box_link&itscg=30200&ls=1&at=1001l3bAw&ct=9natree
- eBay: https://www.ebay.com/sch/i.html?_nkw=Data+Mining+Techniques+Gordon+S+Linoff+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1
- Read more: https://english.9natree.com/read/B004UB2KE4/
#Directmarketingresponsemodeling #Customerdatapreparation #Associationrules #Collaborativefiltering #Survivalanalysis #DataMiningTechniques
Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management is a practical business analytics guide by Gordon S. Linoff and Michael J. A. Berry. Its third edition, published by Wiley in 2011, explains how organizations can turn customer, transaction, and interaction data into decisions that improve acquisition, retention, cross selling, service, and risk management. Rather than presenting data mining as an isolated technical discipline, the book frames it around recurring commercial questions: Which prospects are most likely to respond, which customers are likely to leave, what products tend to be purchased together, and how should limited marketing resources be allocated. The authors introduce a broad set of methods, from traditional statistical approaches to decision trees, neural networks, association rules, collaborative filtering, link analysis, and survival analysis. It is an introductory but applied work, emphasizing data preparation, evaluation, deployment, and organizational infrastructure alongside modeling. Its central purpose is to help business practitioners connect analytical techniques to measurable customer relationship management actions.
