Published research at the intersection of network science and matrix computations formed the basis of algorithms used by the digital marketing company Bloom. In particular, their product Whisper analysed large scale social media data for commercial insight. Whisper provided results for a range of clients, and formed an essential part of Bloom’s offering when Bloom was acquired by Jaywing plc. The challenges raised by the application of network algorithms at scale on real data with stakeholder-defined objectives has opened up further research directions, notably with respect to nonbacktracking walks and higher-order interactions. Here, we introduce the classical Katz centrality measure at the heart of Whisper. We also discuss various recent extensions and emerging applications.