Pipeline de prospecção de leads: descoberta do cliente, qualificação com lead scoring (ICP) orientado a customer success com apoio de IA generativa e IAPAAS

Abstract

Client prospecting and lead qualification in website development projects often rely on informal processes, resulting in ambiguities in requirement elicitation, customer understanding, and decision-making. In this context, this research investigates how Generative Artificial Intelligence can support Customer Discovery and lead qualification activities aligned with Customer Success principles. A Design Science Research (DSR) approach combined with a Systematic Literature Review was adopted to support the design and evaluation of a technological artifact. As a result, an AI-supported prospecting pipeline was proposed and implemented, comprising Generative AI conversational agents, iPaaS integrations, and lead qualification mechanisms responsible for lead qualification, needs diagnosis, proposal generation, sales support, and follow-up activities. The pipeline was integrated through iPaaS platforms and evaluated with specialists and graduate students representing potential users. The results indicated positive perceptions regarding the pipeline's ability to support needs identification, structure relevant information for commercial processes, and improve understanding of customer objectives. The findings suggest that the proposed approach has the potential to assist web development professionals and small digital service businesses in conducting more structured customer discovery and lead qualification processes. The main contribution of this research is the demonstration of how Generative AI agents can be applied to early-stage customer interactions by integrating Customer Discovery, Lead Scoring, and Customer Success concepts into a unified prospecting pipeline.