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|b eng
|e rda
|c DLC
|d YDX
|d BTCTA
|d BDX
|d OCLCF
|d OCLCQ
|d GSE
|d OCLCQ
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|a 658.800285/63
|2 23
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| 100 |
1 |
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|a Struhl, Steven M.,
|e author.
|0 http://id.loc.gov/authorities/names/no93036188
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| 245 |
1 |
0 |
|a Artificial intelligence marketing and predicting consumer choice :
|b an overview of tools and techniques /
|c Steven Struhl.
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| 264 |
|
1 |
|a London ;
|a New York, NY :
|b Kogan Page Limited,
|c 2017.
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| 264 |
|
4 |
|c ©2017
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| 300 |
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|a xiii, 254 pages :
|b illustrations ;
|c 24 cm
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| 336 |
|
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|a text
|b txt
|2 rdacontent
|
| 337 |
|
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|a unmediated
|b n
|2 rdamedia
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| 338 |
|
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|a volume
|b nc
|2 rdacarrier
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| 504 |
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|a Includes bibliographical references and index.
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| 505 |
0 |
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|a Who should read this book and why? -- Getting the project going -- Conjoint, discrete choice and other trade-offs: let's do an experiment -- Creating the best, newest thing: discrete choice modelling -- Conjoint analysis and its uses -- Predictive models: via classifications that grow on trees -- Remarkable predictive models with Bayes Nets -- Putting it together: what to use when.
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| 520 |
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|a The ability to predict consumer choice is a fundamental aspect to success for any business. In the context of artificial intelligence marketing, there is a wide array of predictive analytic techniques available to achieve this purpose, each with its own unique advantages and disadvantages. This book integrates these widely disparate approaches and shows the strengths, weaknesses, and best applications of each. It provides a bridge between the person who must apply or learn these problem-solving methods and the community of experts who do the actual analysis. It is also a practical and accessible guide to the many advances that have been recently made in this field.
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| 650 |
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0 |
|a Marketing research.
|0 http://id.loc.gov/authorities/subjects/sh85081350
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| 650 |
|
0 |
|a Consumer behavior.
|0 http://id.loc.gov/authorities/subjects/sh87006429
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| 650 |
|
0 |
|a Artificial intelligence.
|0 http://id.loc.gov/authorities/subjects/sh85008180
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| 650 |
|
7 |
|a Artificial intelligence.
|2 fast
|0 (OCoLC)fst00817247
|
| 650 |
|
7 |
|a Consumer behavior.
|2 fast
|0 (OCoLC)fst00876238
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| 650 |
|
7 |
|a Marketing research.
|2 fast
|0 (OCoLC)fst01010284
|
| 776 |
0 |
8 |
|i Online version:
|a Struhl, Steven M.
|t Artificial intelligence marketing and predicting consumer choice.
|b 1st Edition.
|d New York : Kogan Page Ltd, [2017]
|z 9780749479565
|w (DLC) 2017009070
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|t 0
|
| 952 |
f |
f |
|p Can Circulate
|a Michigan State University-Library of Michigan
|b Michigan State University
|c MSU Gast Business Library
|d MSU Gast Business Library
|t 0
|e HF5415.2 .S787 2017
|h Library of Congress classification
|i Printed Material
|m 31293033960877
|n 1
|
