Knowledge Graphs (KGs) have become crucial in various domains, particularly e-commerce, where they are utilized for product search, recommendations, question-answering systems, and chatbots. However, e-commerce must continually cover new domains to meet evolving user needs, necessitating rigorous analysis and adding new knowledge to existing KGs. This study introduces UpKG, a framework designed to insert new domains into existing KGs within an e-commerce context. Our approach relies on collected questions and answers, applied in the real-world scenario of GoBots, an e-commerce solutions company in Latin America. Through a case study, we expanded an existing KG, initially dominated by the Automobile domain, by adding triples related to the Appliances domain, resulting in a KG that supports both domains. The final KG included 3,382 new instances derived from 1,338 real-world questions and answers from the GoBots database. We conducted two types of evaluations: the first focused on evaluating the ontology-based KG using tools such as Reasoner Pellet, OOPS!, and OntoDebug to ensure consistency and coherence of the generated KG; the second evaluated the alignment of the achieved KG with the application through 30 Competency Questions. The evaluation confirmed the viability and applicability of UpKG in expanding KGs into new e-commerce domains, offering a significant contribution to KG expansion.