{"title":"Artificial intelligence in business-to-business (B2B) sales process: a conceptual framework","authors":"Michael Rodriguez, Robert Peterson","doi":"10.1057/s41270-023-00287-7","DOIUrl":null,"url":null,"abstract":"<p>The present study introduces a conceptual framework to explore sales professionals’ use of artificial intelligence (AI) in the sales process. The author explores AI’s impact and its relationships with specific outcomes within the sales process. The study first explores the embryonic artificial intelligence literature on sales to measure sales professionals’ perceptions of AI by conducting a content analysis. Based on the results, 79 studies were found on AI and sales, with only 13 specifically looking at the business-to-business sales process. Given the newness of AI, this is a dire need to dive deeper into the use of AI in the B2B sales process. A content analysis from the scant literature and data from 62 sales professionals was performed to conceptually develop a framework proposing AI’s impact on several outcomes: sales process effectiveness, administrative efficiency, and performance with customers.</p>","PeriodicalId":43041,"journal":{"name":"Journal of Marketing Analytics","volume":null,"pages":null},"PeriodicalIF":4.0000,"publicationDate":"2024-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Marketing Analytics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1057/s41270-023-00287-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
Abstract
The present study introduces a conceptual framework to explore sales professionals’ use of artificial intelligence (AI) in the sales process. The author explores AI’s impact and its relationships with specific outcomes within the sales process. The study first explores the embryonic artificial intelligence literature on sales to measure sales professionals’ perceptions of AI by conducting a content analysis. Based on the results, 79 studies were found on AI and sales, with only 13 specifically looking at the business-to-business sales process. Given the newness of AI, this is a dire need to dive deeper into the use of AI in the B2B sales process. A content analysis from the scant literature and data from 62 sales professionals was performed to conceptually develop a framework proposing AI’s impact on several outcomes: sales process effectiveness, administrative efficiency, and performance with customers.
期刊介绍:
Data has become the new ore in today’s knowledge economy. However, merely storing and reporting are not enough to thrive in today’s increasingly competitive markets. What is called for is the ability to make sense of all these oceans of data, and to apply those insights to the way companies approach their markets, adjust to changing market conditions, and respond to new competitors.
Marketing analytics lies at the heart of this contemporary wave of data driven decision-making. Companies can no longer survive when they rely on gut instinct to make decisions. Strategic leverage of data is one of the few remaining sources of sustainable competitive advantage. New products can be copied faster than ever before. Staff are becoming less loyal as well as more mobile, and business centers themselves are moving across the globe in a world that is getting flatter and flatter.
The Journal of Marketing Analytics brings together applied research and practice papers in this blossoming field. A unique blend of applied academic research, combined with insights from commercial best practices makes the Journal of Marketing Analytics a perfect companion for academics and practitioners alike. Academics can stay in touch with the latest developments in this field. Marketing analytics professionals can read about the latest trends, and cutting edge academic research in this discipline.
The Journal of Marketing Analytics will feature applied research papers on topics like targeting, segmentation, big data, customer loyalty and lifecycle management, cross-selling, CRM, data quality management, multi-channel marketing, and marketing strategy.
The Journal of Marketing Analytics aims to combine the rigor of carefully controlled scientific research methods with applicability of real world case studies. Our double blind review process ensures that papers are selected on their content and merits alone, selecting the best possible papers in this field.