現今，數據成為提升營銷效果的新的關鍵要素。營銷數據分析作為企業一項非常重要的活動，是通過特定技術獲取和分析有關市場的所有可用信息，以幫助設計或優化特定的營銷方案，提高營銷效果的一系列活動。本書由入選首批國家級一流本科專業建設點的安徽財經大學市場營銷專業李永發教授團隊歷經近兩年時間打磨，深入利用多個技術工具，挖掘營銷數據背后的市場規律與營銷邏輯，從而幫助學習者掌握數字經濟時代需要的高級營銷技能。本書展示了當前實踐中營銷數據分析的主要內容、常用方法、算法與實操演示，每章都以一個實際問題作為切入點，引出相關理論與算法，最終通過一個案例演示詳細的軟件解決過程。
李永發，安徽財經大學市場營銷系主任、教授、博士、碩士生導師。主要研究方向為：商業模式創新的理論與策略。主持完成國家社會科學基金項目1項，完成省級課題多項，在核心期刊上發表論文20余篇，出版專著2部。曾獲安徽省教學成果獎一等獎、安徽省教師教學創新大賽三等獎。已開發教學案例20余篇，其中，2018—2021年連續4次入選“全國百篇優秀管理案例（微案例）”名單；榮獲清華大學“卓越開發者”案例大獎賽一等獎1項，二等獎1項，三等獎6項。
第1 章 緒論········································1
1.1 營銷數據分析的相關概念··············2
1.1.1 數據分析與數據挖掘···········2
1.1.2 營銷數據與數據營銷···········3
1.2 營銷數據分析的應用領域··············3
1.3 營銷數據分析的方法····················5
1.3.1 基本方法··························5
1.3.2 高級方法··························6
1.4 營銷數據分析的流程····················7
1.5 營銷數據分析的影響····················9
本章小結······································.11
實訓目的······································.11
思考與練習···································.11
參考資料······································.12
第2 章 基于聚類算法的價格帶分析··.13
2.1 問題的提出·····························.14
2.1.1 價格帶分析····················.14
2.1.2 問題設計·······················.14
2.1.3 問題解決思路·················.15
2.2 聚類算法································.15
2.2.1 聚類算法簡介·················.15
2.2.2 K 均值算法原理··············.16
2.2.3 聚類算法的分類··············.17
2.2.4 聚類算法的應用··············.18
2.3 價格帶分析案例·······················.18
本章小結······································.24
實訓目的······································.25
思考與練習···································.25
參考資料······································.25
第3 章 用戶畫像分析·······················.27
3.1 問題的提出·····························.28
3.1.1 用戶畫像·······················.28
3.1.2 問題設計·······················.30
3.1.3 問題解決思路·················.30
3.2 用戶畫像構建過程····················.31
3.2.1 明確營銷需求·················.31
3.2.2 確定用戶畫像的維度和度量
指標·····························.32
3.3 用戶畫像案例··························.35
本章小結······································.46
實訓目的······································.47
思考與練習···································.47
參考資料······································.47
第4 章 基于ARIMA 模型的產品生命
周期預測······························.48
4.1 問題的提出·····························.49
4.1.1 產品生命周期理論···········.49
4.1.2 問題設計·······················.49
4.1.3 問題解決思路·················.50
4.2 時間序列法與ARIMA 模型·········.50
4.2.1 時間序列法····················.50
4.2.2 ARIMA 模型··················.51
4.3 產品生命周期預測案例··············.52
本章小結······································.62
實訓目的······································.64
思考與練習···································.64
參考資料······································.65
第5 章 基于關聯規則的購物籃分析··.66
5.1 問題的提出·····························.67
5.1.1 購物籃分析····················.67
5.1.2 問題設計·······················.67
5.1.3 問題解決思路·················.68
5.2 關聯分析································.68
5.2.1 關聯分析步驟與關聯強度··.68
5.2.2 關聯分析的核心算法········.69
5.2.3 關聯分析在營銷中的應用··.71
5.3 購物籃分析案例·······················.71
本章小結······································.79
實訓目的······································.80
思考與練習···································.80
參考資料······································.80
第6 章 基于文本挖掘的消費者情感
分析····································.81
6.1 問題的提出·····························.82
6.1.1 商品評價中的情感···········.82
6.1.2 問題設計·······················.82
6.1.3 問題解決思路·················.82
6.2 文本分析法·····························.83
6.2.1 文本分析原理·················.83
6.2.2 文本數據的分析類型與一般
流程·····························.84
6.2.3 文本情感分析的三種方法··.84
6.3 消費者情感分析案例·················.85
本章小結······································.94
實訓目的······································.96
思考與練習···································.96
參考資料······································.96
第7 章 基于PSM 的定價策略··········.97
7.1 問題的提出·····························.98
7.1.1 定價·····························.98
7.1.2 問題設計·······················.98
7.1.3 問題解決思路·················.99
7.2 PSM 的原理、流程與優缺點········.99
7.2.1 PSM 的原理···················.99
7.2.2 PSM 的流程···················100
7.2.3 PSM 的優缺點················100
7.3 定價案例································101
本章小結······································109
實訓目的······································110
思考與練習···································110
參考資料······································110
第8 章 基于決策樹的消費者響應
預測····································112
8.1 問題的提出·····························113
8.1.1 促銷與消費者響應···········113
8.1.2 問題設計·······················113
8.1.3 問題解決思路·················114
8.2 決策樹工作原理與算法··············114
8.2.1 決策樹的工作原理···········114
8.2.2 構建決策樹的多種算法·····115
8.3 消費者響應預測案例·················116
本章小結······································132
實訓目的······································133
思考與練習···································133
參考資料······································133
第9 章 品牌推廣策略優化················134
9.1 問題的提出·····························135
9.1.1 品牌營銷·······················135
9.1.2 問題設計·······················135
9.1.3 問題解決思路·················136
9.2 數據可視化·····························136
9.2.1 數據可視化的定義···········136
9.2.2 數據可視化的步驟···········137
9.2.3 數據可視化的呈現要點·····137
9.2.4 數據可視化的報告撰寫·····138
9.3 品牌營銷效果分析案例··············139
本章小結······································146
實訓目的······································147
思考與練習···································147
參考資料······································147
第10 章 客戶關系管理·····················148
10.1 問題的提出····························149
10.1.1 客戶關系管理···············149
10.1.2 問題設計·····················149
10.1.3 問題解決思路···············150
10.2 客戶購買預測·························151
10.2.1 邏輯回歸算法簡介·········151
10.2.2 基于邏輯回歸算法的潛在
客戶識別案例···············153
10.3 基于RFM 模型的客戶分類········164
10.3.1 RFM 模型····················164
10.3.2 客戶分類案例···············166
10.3.3 差異化營銷策略············173
10.4 客戶流失預測案例···················174
本章小結······································181
實訓目的······································182
思考與練習···································182
參考資料······································182
第11 章 營銷大數據倫理··················183
11.1 營銷大數據中的倫理道德問題····184
11.1.1 大數據收集中的倫理道德
問題···························184
11.1.2 大數據處理與分析中的倫
理道德問題··················185
11.1.3 大數據應用中的倫理道德
問題···························186
11.2 營銷大數據倫理道德問題的
危害·····································187
11.2.1 個人層面·····················187
11.2.2 企業層面·····················188
11.2.3 行業層面·····················189
11.2.4 社會層面·····················190
11.2.5 國家層面·····················191
11.3 營銷大數據倫理道德問題的
治理·····································192
11.3.1 完善法律規制················192
11.3.2 加強行業自律················193
11.3.3 加強技術監控和保護·······194
11.3.4 提高個人信息安全和信息
保護意識·····················195
本章小結······································195
實訓目的······································195
思考與練習···································196
參考資料······································196
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