¥ 4,504
通常配送無料 詳細
残り1点(入荷予定あり) 在庫状況について
この商品は、Amazon.co.jp が販売、発送します。
Introduction to Algorithm... がカートに入りました
この商品をお持ちですか? マーケットプレイスに出品する
裏表紙を表示 表紙を表示
サンプルを聴く 再生中... 一時停止   Audible オーディオエディションのサンプルをお聴きいただいています。
2点すべてのイメージを見る

著者をフォローする

何か問題が発生しました。後で再度リクエストしてください。


Introduction to Algorithmic Marketing: Artificial Intelligence for Marketing Operations (英語) ハードカバー – 2017/12/2


その他(2)の形式およびエディションを表示する 他のフォーマットおよびエディションを非表示にする
価格
新品 中古品
ハードカバー
¥ 4,504
¥ 4,504 ¥ 5,748

booksPMP

【2冊で最大4%、3冊以上で最大8%、10冊以上で最大10%】ポイント還元

2冊を購入する際クーポンコード「2BOOKS」を、3冊以上は「MATOME」を入力すると最大8~10%ポイント還元!今すぐチェック

click to open popover

キャンペーンおよび追加情報


よく一緒に購入されている商品

  • Introduction to Algorithmic Marketing: Artificial Intelligence for Marketing Operations
  • +
  • 前処理大全[データ分析のためのSQL/R/Python実践テクニック]
総額: ¥7,744
ポイントの合計: 96pt (1%)
選択された商品をまとめて購入

Kindle 端末は必要ありません。無料 Kindle アプリのいずれかをダウンロードすると、スマートフォン、タブレットPCで Kindle 本をお読みいただけます。

  • iOSアプリのダウンロードはこちらをクリック
    Apple
  • Androidアプリのダウンロードはこちらをクリック
    Android
  • Amazonアプリストアへはこちらをクリック
    Android

無料アプリを入手するには、Eメールアドレスを入力してください。

kcpAppSendButton

商品の説明

内容紹介

Introduction to Algorithmic Marketing is a comprehensive guide to advanced marketing automation for marketing strategists, data scientists, product managers, and software engineers. It summarizes various techniques tested by major technology, advertising, and retail companies, and it glues these methods together with economic theory and machine learning. The book covers the main areas of marketing that require programmatic micro-decisioning - targeted promotions and advertisements, eCommerce search, recommendations, pricing, and assortment optimization.

"A comprehensive and indispensable reference for anyone undertaking the transformational journey towards algorithmic marketing."

―Ali Bouhouch, CTO, Sephora Americas

"It is a must-read for both data scientists and marketing officerseven better if they read it together."

―Andrey Sebrant, Director of Strategic Marketing, Yandex

"The book gives the executives, middle managers, and data scientists in your organization a set of concrete, actionable, and incremental recommendations on how to build better insights and decisions, starting today, one step at a time."

―Victoria Livschitz, founder and CTO, Grid Dynamics

Table of Contents

Chapter 1 - Introduction

  1. The Subject of Algorithmic Marketing
  2. The Definition of Algorithmic Marketing
  3. Historical Backgrounds and Context
  4. Programmatic Services
  5. Who Should Read This Book?
  6. Summary

Chapter 2 - Review of Predictive Modeling

  1. Descriptive, Predictive, and Prescriptive Analytics
  2. Economic Optimization
  3. Machine Learning
  4. Supervised Learning
  5. Representation Learning
  6. More Specialized Models
  7. Summary

Chapter 3 - Promotions and Advertisements

  1. Environment
  2. Business Objectives
  3. Targeting Pipeline
  4. Response Modeling and Measurement
  5. Building Blocks: Targeting and LTV Models
  6. Designing and Running Campaigns
  7. Resource Allocation
  8. Online Advertisements
  9. Measuring the Effectiveness
  10. Architecture of Targeting Systems
  11. Summary

Chapter 4 - Search

  1. Environment
  2. Business Objectives
  3. Building Blocks: Matching and Ranking
  4. Mixing Relevance Signals
  5. Semantic Analysis
  6. Search Methods for Merchandising
  7. Relevance Tuning
  8. Architecture of Merchandising Search Services
  9. Summary

Chapter 5 - Recommendations

  1. Environment
  2. Business Objectives
  3. Quality Evaluation
  4. Overview of Recommendation Methods
  5. Content-based Filtering
  6. Introduction to Collaborative Filtering
  7. Neighborhood-based Collaborative Filtering
  8. Model-based Collaborative Filtering
  9. Hybrid Methods
  10. Contextual Recommendations
  11. Non-Personalized Recommendations
  12. Multiple Objective Optimization
  13. Architecture of Recommender Systems
  14. Summary

Chapter 6 - Pricing and Assortment

  1. Environment
  2. The Impact of Pricing
  3. Price and Value
  4. Price and Demand
  5. Basic Price Structures
  6. Demand Prediction
  7. Price Optimization
  8. Resource Allocation
  9. Assortment Optimization
  10. Architecture of Price Management Systems
  11. Summary

レビュー

"At a time when power is shifting to consumers, while brands and retailers are grasping for fleeting moments of attention, everyone is competing on data and the ability to leverage it at scale to target, acquire, and retain customers. This book is a manual for doing just that. Both marketing practitioners and technology providers will find this book very useful in guiding them through the marketing value chain and how to fully digitize it. A comprehensive and indispensable reference for anyone undertaking the transformational journey towards algorithmic marketing."

―Ali Bouhouch, CTO, Sephora Americas

"This book is a live portrait of digital transformation in marketing. It shows how data science becomes an essential part of every marketing activity. The book details how data-driven approaches and smart algorithms result in deep automation of traditionally labor-intensive marketing tasks. Decision-making is getting not only better but much faster, and this is crucial in our ever-accelerating competitive environment. It is a must-read for both data scientists and marketing officerseven better if they read it together."

―Andrey Sebrant, Director of Strategic Marketing, Yandex

"This books delivers a complete end-to-end blueprint on how to fully digitize your company's marketing operations. Starting from a conceptual architecture for the future of digital marketing, it then delves into detailed analysis of best practices in each individual area of marketing operations. The book gives the executives, middle managers, and data scientists in your organization a set of concrete, actionable, and incremental recommendations on how to build better insights and decisions, starting today, one step at a time."

―Victoria Livschitz, founder and CTO, Grid Dynamics

"This book provides a much-needed collection of recipes for marketing practitioners on how to use advanced methods of machine learning and data science to understand customer behavior, personalize product offerings, optimize the incentives, and control the engagement - thus creating a new generation of data-driven analytic platform for marketing systems."

―Kira Makagon, Chief Innovation Officer, RingCentral; serial entrepreneur, founder of RedAril and Octane

"While virtually every business manager today grasps the conceptual importance of data analytics and machine learning, the challenge of implementing actual competitive solutions rooted in data science remains quite daunting. The scarcity of data scientist talent, combined with the difficulty of adapting academic models, generic open-source software and algorithms to industry-specific contexts are among the difficulties confronting digital marketers around the world. This book by Ilya Katsov draws from the deep domain expertise he developed at Grid Dynamics in delivering innovative, yet practical digital marketing solutions to large organizations and helping them successfully compete, remain relevant, and adapt in the new age of data analytics."

―Eric Benhamou, Founder and General Partner, Benhamou Global Ventures; former CEO and Chairman of 3Com and Palm


登録情報

  • ハードカバー: 508ページ
  • 出版社: Ilia Katcov (2017/12/2)
  • 言語: 英語
  • ISBN-10: 0692989048
  • ISBN-13: 978-0692989043
  • 発売日: 2017/12/2
  • 商品パッケージの寸法: 15.2 x 3.8 x 22.9 cm
  • おすすめ度: この商品の最初のレビューを書き込んでください。
  • Amazon 売れ筋ランキング: 洋書 - 52,841位 (洋書の売れ筋ランキングを見る)
  • さらに安い価格について知らせる
    この商品を出品する場合、出品者サポートを通じて更新を提案したいですか?


まだカスタマーレビューはありません


この商品をレビュー

他のお客様にも意見を伝えましょう

Amazon.com で最も参考になったカスタマーレビュー

Amazon.com: 5つ星のうち4.3 11 件のカスタマーレビュー
Dmytro Sotnyk
5つ星のうち5.0Solid overview of the marketing from academical standpoint
2018年1月30日 - (Amazon.com)
Amazonで購入
12人のお客様がこれが役に立ったと考えています.
cloud21st
5つ星のうち1.0just a list of applied mathematical theories in marketing
2018年8月30日 - (Amazon.com)
Amazonで購入
10人のお客様がこれが役に立ったと考えています.
Ingrid Lee
5つ星のうち5.0A must-read for every data scientist in retail
2018年2月3日 - (Amazon.com)
Amazonで購入
6人のお客様がこれが役に立ったと考えています.
Dennis
5つ星のうち5.0Excellent book for readers with a mathematical background
2018年1月17日 - (Amazon.com)
Amazonで購入
3人のお客様がこれが役に立ったと考えています.
A Anand
5つ星のうち5.0Best marketing data science book !
2018年6月25日 - (Amazon.com)
Amazonで購入
1人のお客様がこれが役に立ったと考えています.