چکیده مقاله
This research examines artificial intelligence transformation of traditional sales processes into automated revenue systems within B2B SaaS environments Through systematic literature analysis of contemporary publications 2023 2024 and comprehensive case study of HubSpot implementation, we investigate AI architectural foundations for lead to cash automation Our mixed methods approach reveals machine learning ensembles achieve 94% accuracy in lead qualification while AI CRM integration reduces sales cycles by 41% The HubSpot case demonstrates 35% increase in qualified leads and 27% improvement in deal closure rates through strategic human AI collaboration Quantitative analysis shows significant improvements in marketing efficiency and sales productivity AI driven systems substantially enhance revenue predictability and operational performance, though data quality management and ethical implementation challenges require continued attention This study provides validated architectural guidance for organizations pursuing AI powered revenue transformation in competitive digital markets
کلیدواژهها
نویسندگان
Mahsa Yaghoubzadeh
MSc in Business Management, E Commerce, Arak,Iran
شیوه ارجاع
Yaghoubzadeh, Mahsa,1404,Architecting Intelligent Revenue Systems: AI-Driven Transformation in B2B SaaS Platforms,3rd International Conference on Industrial Marketing,Tehran
ارائهشده در
مجموعه مقالات سومین کنفرانس بین المللی بازاریابی صنعتی21 آبان 1404 · تهران