以顾客为中心的销售预测模型:RFM-ARIMA方法

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Sanket Londhe, Sushila Palwe
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引用次数: 2

摘要

背景:决策者通过处理、分析和解释数据来获得洞察力,从而确定最佳行动方案的过程被称为商业智能。一些决策支持系统使用销售数据来预测未来的扩张,但很少考虑客户数据的影响。目的:本研究的主要目的是建立一个模型,该模型将使用一些以客户为中心的特征,根据微调的销售数字给出预测。方法/方法:我们首先使用RFM模型根据客户购买特征将客户划分为不同的细分市场,然后丢弃与业务无关的细分市场。然后我们使用ARIMA模型对剩余的数据进行销售预测。结果:使用该模型,我们能够更好地拟合预测模型的数据,并在RFM分析后使用时获得更好的准确性。结论:我们试图合并两种不同的概念来做一个跨功能的分析,以更好的决策。我们能够将RFM-ARIMA模型作为一种更好的度量或方法来微调销售分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Customer-Centric Sales Forecasting Model: RFM-ARIMA Approach
Abstract Background: Decision makers use the process of determining the best course of action by processing, analysing & interpreting the data to gain insights, known as Business Intelligence. Some decision support systems use sales figures to predict future expansion, but few consider the effect of customer data. Objectives: The main objective of this study is to build a model that will give a forecast based on fine-tuned sales numbers using some customer-centric features. Methods/Approach: We first use the RFM model to segment the customers into distinct segments based on customer buying characteristics and then discard the segments that are irrelevant to the business. Then we use the ARIMA model to do the sales forecasting for the remainder of the data. Results: Using this model, we were able to achieve a better fitment of the data for the prediction model and achieved a better accuracy when used after RFM analysis. Conclusions: We tried to merge two different concepts to do a cross-functional analysis for better decision-making. We were able to present the RFM-ARIMA model as a better metric or approach to fine-tune the sales analysis.
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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