User reviews provide a significant source of information for companies to understand their market and audience. In order to discover broad trends in this source, researchers have typically used topic models such as Latent Dirichlet Allocation (LDA). However, it is not clear whether the resulting topics can also provide in-depth product analysis. Our paper aims to tackle this issue by examining user reviews from the Best Buy US website for smart speakers, to understand how people use them and what their main concerns are. We find that coherence scores are a good starting point to identify a good number of topics, but it still requires manual inspection. We use the resulting topics to gain insights into brand performance and difference, and find that brands sort into two distinct groups with different properties.