Statistical modelling and machine learning that automatically finds unexpected anomalies in your data. It combs through vast amounts of data to immediately identify factors that are affecting your business.
Stuff happens. And you’ll know it when it does.
Unexpected action in your data can be both good and bad. On the one hand, it may mean that a campaign is performing better than expected. But on the other, it can mean that something’s wrong — a bug that’s causing problem, a tagging error, even corporate espionage. Whether the cause of the anomaly is good or bad, identifying it quickly is always good. But traditionally, this took time and resources, assuming you weren’t too busy simply cleansing data and preparing reports.
The anomaly detection feature of Adobe Analytics lets you automatically detect statistically significant data anomalies during specified periods. Then we show you these unexpected traffic spikes or dips with clear visualisations. And with our Contribution Analysis feature inside Analysis Workspace, you can see not only when anomalies happen, but understand why.
Analyse anomalies over time.
Broaden your analysis from hourly, daily or weekly views to monthly views to get a long-term vision of your campaigns and where anomalies occur over time.
Account for holidays or special events.
When used in Analysis Workspace, anomaly detection can account for seasonal events, such as Black Friday, spring break and holiday periods.
Let your AI do the driving.
Anomaly detection uses the unique machine-learning and automation algorithms of Adobe Sensei to drive better insights faster.
Be in the know — now.
With our intelligent alerts, you can know immediately via email or text about significant changes in your key metrics and segments.
Find the why behind the anomaly.
With contribution analysis, you can discover what caused the anomaly with literally the click of a button.
Learn more about anomaly detection in Adobe Analytics.
Know the unknowns in your marketing data.
Learn more about anomaly detection by viewing how a sample analyst for an ecommerce website can build out specific views in Analysis Workspace.