These are, by-far, the more interesting anomalies – they represent an expected and unknown change in performance, which the human had not anticipated – and generate an “Aha!” moment when revealed. These are generally not well understood by the audience – an example of this could be a sudden drop in orders from a retailer’s website, or a spike in the number of customer complaints for a video streaming platform. Importantly – they do not generate an “Aha!” moment when they are revealed to a human, as a change in performance is already expected These are generally well understood by those reviewing the results of Anomaly Detection – great examples of these include a spike in sales due to Black Friday, or a fall in footfall at a shopping centre on Christmas Day. An anomaly is a data point that falls outside of the range of usual behaviour.
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