Adobe Analytics uses AI to automatically scan hundreds or thousands of business metrics and flag unexpected changes — like a sudden drop in website sales or a spike in customer complaints — before an analyst might notice. It also identifies which factors most likely caused the change and sends automated alerts. This capability has been part of Adobe Analytics since 2016.

Anomaly detection uses statistical modeling to establish expected ranges for any metric, accounting for day-of-week patterns, seasonality, and long-term trends, then flags results that fall outside those ranges. Contribution Analysis then scans thousands of data dimensions to identify which factors — such as geography, device type, or marketing campaign — most likely explain the anomaly. Attribution modeling uses machine learning to assign credit for customer conversions to the correct touchpoints in a customer's journey, rather than simply attributing everything to the last click.