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Size of wallet estimation: Application of K-nearest neighbour and quantile regression

机译:钱包估计的大小:K到最近邻和分位数回归的应用

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Size of wallet (SOW) estimation is an important problem to solve from a company's perspective. The total business volume conducted by the customer for a product category across firms is generally unobservable, while the volume of transactions conducted by the customer with the company is mostly accessible. This paper focuses on the estimation of SOW and the estimation of opportunity, which is the difference between the SOW and the actual transactional value of the business that a customer does with a company. K-nearest neighbour (KNN) and quantile regression (QR) are applied here to arrive at the estimations, and their performance is compared. Based on the SOW and opportunity estimates, a company can decide its target segment and design specific marketing strategies accordingly, thereby improving its profitability.
机译:钱包的大小(母猪)估计是从公司的角度解决的重要问题。 客户对公司的产品类别进行的总业务卷通常是不可观察的,而客户与公司的交易量大多是可访问的。 本文重点介绍播种的估计和机会的估计,这是客户与公司所做的业务的实际交易价值之间的差异。 k最近邻(knn)和定量回归(QR)在此处应用于估计,并比较它们的性能。 根据母猪和机会估计,公司可以相应地决定其目标细分和设计特定的营销策略,从而提高其盈利能力。

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