Predicting Customer Potential Values Using Customers' Behavior of Features in Shops
| Project/Area Number |
24730375
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Commerce
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| Research Institution | Senshu University (2014)
Kansai University (2012-2013) |
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Principal Investigator |
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| Project Period (FY) |
2012-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2014: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2013: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2012: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | データマイニング / マーケティング / 機械学習 / 潜在モデル / 顧客潜在価値 / 消費者行動 / データ研磨 / マイクロクラスタリング / 潜在価値 / マインド / 購買モデル / 顧客動線 / RFID |
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| Outline of Final Research Achievements |
In this study, I have proposed a customer potential values (CPV) index to conceptualize customers’ potential for purchasing products based on association rules. The customer potential value is calculated by extracting distinguishing features of customers’ movement in one supermarket. This method extracts potential purchases related to certain product items, and applies a novel technique to enhance the latent structure of relationships between products known as “graph polishing” to identify key clusters. This study was awarded top prize by Joint Association Study Group of Management Science at Data Analysis Competition in 2013.
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Report
(4 results)
Research Products
(22 results)
