Design of an Intelligent System for Automated Personalization in B2B Sales Processes

Abstract

This paper explores the design of a semi-automated system for personalization in B2B sales, with a focus on the role of Sales Development Representatives (SDRs). The main issue addressed is the trade-off between quality and volume in the initial outreach to potential clients. Manual personalization produces relevant messages but is too slow and difficult to sustain at scale. Through detailed documentation of the practical SDR process at Semos Cloud, the paper identifies the key steps and data sources that lead to effective personalization. Based on these insights, a conceptual system design is proposed that integrates data collection, data enrichment, and automated message generation using language models. The system features a modular architecture, a user interface with human oversight, and ethical mechanisms ensuring transparency and privacy. The evaluation was conducted through a manual simulation of the future process. The results show significant improvements: a 3.46-fold increase in outreach volume, more than an 11-fold increase in response rate, and a reduction in message preparation time from 15 to 5 minutes. These findings confirm the practical value of the proposed system and justify its further implementation.