Live chat in customer service platforms is critical for serving clients online. For multi-turn question-answering live chat, typical Question Answering systems are single-turn and focus on factoid questions; alternatively, modeling as goal-oriented dialogue limits us to narrower domains. Motivated by these challenges, we develop a new approach based on a framework from a different discipline: Community Question Answering. Specifically, we opt to divide and conquer the task into two sub-tasks: (1) Question-Question Similarity, where we gain more than 9% absolute improvement in F1 over baseline; and (2) Answer Utterances Extraction, where we achieve a high F1 score of 87% for this new sub-task. Further, our user engagement metrics reveal how the enterprise support representatives benefit from the 2-step approach we deployed to production.