Business-to-business (B2B) social media efforts have largely focused on creating brand engagement through online content. We propose to analyse company social media texts (tweets) according to its two main dimensions, content and linguistic style, and to evaluate these in comparison to the overall content and style of the company's community of Twitter followers. We combine 15 million tweets originating from 254,884 followers of ten company profiles and link these to 10,589 B2B company tweets. Using advanced text analytics, we show that content similarity has positive effects on all engagement metrics, while linguistic style similarity mainly affects likes. Readability acts as a moderator for these effects. We also find a negative interaction effect between the similarity metrics, such that style similarity is most useful if content similarity is low. This research is the first to integrate content and linguistic style similarity and contributes to the brand engagement literature by providing practical message composition guidelines, informed by the social media community.