Imagine you are a data analyst for a travel company. You know there are anomalous behaviours that don’t match your forecasting expectations, such as spikes or dips in bookings, but it’s like searching for patterns in static: you simply don’t have the tools to identify these anomalies.
More importantly, you have no way of knowing why these anomalies take place, or how they affect your business results.
Combining the Anomaly Detection and the Contribution Analysis capabilities of Adobe Analytics enables companies to intelligently identify the hidden patterns and contributing factors for statistical anomalies in their raw data.
By quickly analysing analytics data, it can save countless hours searching for reasons why company metrics may have changed. Contribution Analysis leverages powerful machine learning designed to transform the analyst and marketer into a data scientist.
For trended data, Anomaly Detection identifies statistical anomalies—separating “true” signals from “noise” as data changes over time—so analysts can uncover anomalous behaviors or patterns that would have otherwise gone unnoticed.
Anomaly Detection greatly simplifies the analysis of data by surfacing the most relevant trends, freeing up valuable time to find actionable insights.
The next step after Anomaly Detection, Contribution Analysis doesn’t just tell a company what is out of the ordinary; it helps them understand why the anomaly occurred.
Contribution Analysis intelligently identifies potential causes or contributing factors for significant changes in trended data and anomalies, so companies can save countless hours in searching terabytes of data by analysing all Adobe Analytics data at once.
The true power of Adobe Analytics is in the combination of its capabilities. By combining Anomaly Detection with Contribution Analysis, organisations don’t just know the what—they also know the why.
Adobe Analytics automatically searches all of an organisation’s raw data—more than any human could ever hope to analyse—to determine the relevance of anomalous activities so organisations can better optimise their digital properties.
Adobe Analytics combines data from online and offline channels to give organisations real-time insights into campaign and website performance and customer behaviour across channels.
The Anomaly Detection & Contribution Analysis capabilities come with all implementations of Adobe Analytics, full integration with the other capabilities of the solution, and integration with other solutions of Adobe Marketing Cloud.
By combining Anomaly Detection and Contribution Analysis, companies can intelligently identify the hidden patterns and contributing factors for statistical anomalies in their raw data.
Goji provides consulting, training, support and implementation services to Australian and New Zealand organisations in Adobe Analytics, as well as other platforms in the Adobe Experience Cloud and Google Analytics. If you would like to discuss our services, use our contact form and tell us your story.
View More Adobe Analytics Features
- What is Adobe Analytics?
- Adobe Analytics Reports
- Dynamic Tag Manager (DTM)
- Adobe Analytics Workspace
- Adobe Analytics Ad Hoc Analysis
- Adobe Mobile Services (Adobe App Tracking)
- Adobe Analytics Data Connectors
- Adobe Analytics Data Workbench
- Adobe Analytics Report Builder
- Contribution Analysis and Anomaly Detection
- Adobe Segment IQ
- Adobe Analytics Activity Map (Heat Map and Click Map)