Customer segmentation and clustering using SAS Enterprise Miner
Understanding your customers is the key to your company’s success! Segmentation is one of the first and most basic machine learning methods. It can be used by companies to understand their customers better, boost relevance of marketing messaging, and increase efficacy of predictive models. In Cust...
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| Main Author: | |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
Cary, NC :
SAS Institute,
2017.
|
| Edition: | Third edition. |
| Subjects: | |
| ISBN: | 9781629605296 9781629605272 9781629605289 |
| Physical Description: | 1 online zdroj |
Cover
Table of contents
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| 100 | 1 | |a Collica, Randall S., |e author. | |
| 245 | 1 | 0 | |a Customer segmentation and clustering using SAS Enterprise Miner / |c Randall S. Collica. |
| 250 | |a Third edition. | ||
| 264 | 1 | |a Cary, NC : |b SAS Institute, |c 2017. | |
| 300 | |a 1 online zdroj | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 506 | |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty univerzity | ||
| 520 | |a Understanding your customers is the key to your company’s success! Segmentation is one of the first and most basic machine learning methods. It can be used by companies to understand their customers better, boost relevance of marketing messaging, and increase efficacy of predictive models. In Customer Segmentation and Clustering Using SAS Enterprise Miner, Third Edition, Randy Collica explains, in step-by-step fashion, the most commonly available techniques for segmentation using the powerful data mining software SAS Enterprise Miner. A working guide that uses real-world data, this new edition will show you how to segment customers more intelligently and achieve the one-to-one customer relationship that your business needs. Step-by-step examples and exercises, using a number of machine learning and data mining techniques, clearly illustrate the concepts of segmentation and clustering in the context of customer relationship management. The book includes four parts, each of which increases in complexity. Part 1 reviews the basics of segmentation and clustering at an introductory level, providing examples from a variety of industries. Part 2 offers an in-depth treatment of segmentation with practical topics, such as when and how to update your models. Part 3 goes beyond traditional segmentation practices to introduce recommended strategies for clustering product affinities, handling missing data, and incorporating textual records into your predictive model with SAS Text Miner. Finally, part 4 takes segmentation to a new level with advanced techniques, such as clustering of product associations, developing segmentation-scoring models from customer survey data, combining segmentations using ensemble segmentation, and segmentation of customer transactions. New to the third edition is a chapter that focuses on predictive models within microsegments and combined segments. - Resumé vydavatel | ||
| 588 | 0 | |a Online resource; title from PDF title page (EBSCO, viewed December 6, 2017) | |
| 590 | |a eBooks on EBSCOhost |b All EBSCO eBooks | ||
| 650 | 0 | 7 | |a řízení vztahů se zákazníky |7 ph118187 |2 czenas |
| 650 | 0 | 7 | |a dolování dat |7 ph165954 |2 czenas |
| 650 | 0 | 7 | |a SAS (software) |7 ph118060 |2 czenas |
| 650 | 0 | 7 | |a zpracování dat |7 ph127675 |2 czenas |
| 650 | 0 | 9 | |a customer services |2 eczenas |
| 650 | 0 | 9 | |a customer relationship management |2 eczenas |
| 650 | 0 | 9 | |a data mining |2 eczenas |
| 650 | 0 | 9 | |a SAS (computer file) |2 eczenas |
| 650 | 0 | 9 | |a data processing |2 eczenas |
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