A theory of predictive sales analytics adoption

Q1 Business, Management and Accounting

AMS Review Pub Date : 2023-02-13 DOI:10.1007/s13162-022-00252-0

Johannes Habel, Sascha Alavi, Nicolas Heinitz

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引用次数: 5

Abstract

Given the pervasive ubiquity of data, sales practice is moving rapidly into an era of predictive analytics, using quantitative methods, including machine learning algorithms, to reveal unknown information, such as customers’ personality, value, or churn probabilities. However, many sales organizations face difficulties when implementing predictive analytics applications. This article elucidates these difficulties by developing the PSAA model—a conceptual framework that explains how predictive sales analytics (PSA) applications support sales employees’ job performance. In particular, the PSAA model conceptualizes the key contingencies governing how the availability of PSA applications translates into adoption of these applications and, ultimately, job performance. These contingencies determine the extent to which sales employees adopt these applications to revise their decision-making and the extent to which these updates improve the decision outcome. To build the PSAA model, we integrate literature on predictive analytics and machine learning, technology adoption, and marketing capabilities. In doing so, this research provides a theoretical frame for future studies on salesperson adoption and effective utilization of PSA.

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预测销售分析采用理论

摘要由于数据无处不在，销售实践正迅速进入预测分析时代，使用定量方法，包括机器学习算法，来揭示未知信息，如客户的个性、价值或流失概率。然而，许多销售组织在实现预测分析应用程序时面临困难。本文通过开发PSAA模型(一个解释预测性销售分析(PSA)应用程序如何支持销售员工工作绩效的概念框架)来阐明这些困难。特别是，PSAA模型概念化了控制PSA应用程序的可用性如何转化为这些应用程序的采用以及最终的工作性能的关键偶然性。这些偶然性决定了销售员工在多大程度上采用这些应用程序来修改他们的决策，以及这些更新在多大程度上改善决策结果。为了构建PSAA模型，我们整合了预测分析和机器学习、技术采用和营销能力方面的文献。在此基础上，本研究为未来销售人员采用和有效利用PSA的研究提供了理论框架。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

AMS Review Business, Management and Accounting-Marketing

CiteScore

14.60

自引率

0.00%

发文量

期刊介绍： The AMS Review is positioned to be the premier journal in marketing that focuses exclusively on conceptual contributions across all sub-disciplines of marketing. It publishes articles that advance the development of market and marketing theory.The AMS Review is receptive to different philosophical perspectives and levels of analysis that range from micro to macro. Especially welcome are manuscripts that integrate research and theory from non-marketing disciplines such as management, sociology, economics, psychology, geography, anthropology, or other social sciences. Examples of suitable manuscripts include those incorporating conceptual and organizing frameworks or models, those extending, comparing, or critically evaluating existing theories, and those suggesting new or innovative theories. Comprehensive and integrative syntheses of research literatures (including quantitative and qualitative meta-analyses) are encouraged, as are paradigm-shifting manuscripts.Manuscripts that focus on purely descriptive literature reviews, proselytize research methods or techniques, or report empirical research findings will not be considered for publication. The AMS Review does not publish manuscripts focusing on practitioner advice or marketing education.