Resumo:
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.
