We scrape vast datasets of over 60 million online sources, extracting and processing constantly. As we process this data, our system indexes and categorises content, looking for correlation: are any entities or organisations featuring highly, what common phrases can we recognise, what influencers are driving conversation and what is the sentiment of this conversation?
The picture builds up immediately – the constant stream of information and real-time processing meaning our outputs can be delivered quickly and at high frequency. We are able to automatically detect reputational risks arising from online discussion, in context and at pace, alerting senior stakeholders to issues.
Our system applies machine learning to the indexed, aggregated data, accessing ten years of analysed data. Our approach can be distinguished by the quality of patterns we can leverage; it has been trained to filter information based on constantly refined assumptions ensuring that appropriate intelligence is delivered.
A team of highly-skilled analysts pulls all of this information together and tailors the output to a client’s objectives. They overlay a consistent narrative and context, broaden the insight by researching additional critical conversation and sense check that content alights perfectly with the client’s mandate. They ensure that any data trends are genuine, experienced in investigating anomalous patterns and seeing past one-dimensional movements.