Classifications in Adobe Analytics

What is Classification?

In Adobe Analytics, Classifications are a powerful feature that allows you to enrich your data by adding descriptive attributes to your existing variables. This enhancement enables more detailed analysis and reporting, providing deeper insights into your digital strategies.

In other words, A classification is a way of categorizing Analytics variable data, then displaying the data in different ways when you generate reports. You establish a relationship between a variable value and metadata related to that value. Classifications can be used on most custom dimensions, such as Tracking code, props, and eVars.

What are some of the ways to classify data in Adobe?

• Classification sets: Create and manage classifications and their rules in a single, simplified interface.
• Classification rules: Create rules that assign a given dimension item to a classification dimension item. This method to classify data is best when a dimension frequently encounters new unique values or where manual classifications would be frequent and burdensome.
• Classification importer: Export a template spreadsheet with dimension items in each row. Columns represent each classification for a dimension. This method to classify data is best when all dimension items are known and does not require frequent updating.

Can you explain Classification using a real-world scenario?

Why, yes! Consider the following two scenarios to illustrate how classifications can be applied:

Product Catalog Enhancement

• Scenario: An online retailer tracks product interactions using unique product IDs (e.g., P12345).
• Challenge: While the product ID is useful for internal tracking, it doesn't convey meaningful information in reports.
• Solution: By classifying the product ID, you can add attributes such as Product Name, Category, Color, and Size.
• Implementation: Create classifications for the product ID: (Product Name: Red Nike Air Jordan Sneakers, Category: Footwear, Color: Red, Size: Varies)
• Benefit: Reports now display meaningful product information, allowing for analysis by category, color, or size, providing insights into product performance.

Marketing Campaign Analysis

• Scenario: A company uses tracking codes in their URLs to monitor marketing campaign performance (e.g., em:Summer:2025:Sale).
• Challenge: The raw tracking code is not easily interpretable in reports.
• Solution: Classify the tracking code into components like Channel, Campaign Name, and Year.
• Implementation: Set up classifications for the tracking code: (Channel: Email, Campaign Name: Summer Sale, Year: 2025)
• Benefit: This breakdown allows for detailed analysis of campaign performance across different channels and time periods.

What is SAINT Classification? Is it different from the normal classification we are talking about?

SAINT (SiteCatalyst Attribute Importing and Naming Tool) classifications are a method used to enrich data by adding descriptive attributes to existing variables. This process allows for more detailed analysis and reporting by categorizing data into meaningful segments.

Difference Between SAINT Classifications and Standard Classifications

While both SAINT classifications and standard classifications aim to enhance data analysis, they differ in their implementation:

• SAINT Classifications: Traditionally, SAINT classifications involve manually uploading data files to Adobe Analytics. This method is suitable for predefined data sets that don't change frequently.
• Standard Classifications: Adobe now offers more streamlined methods, such as the Classification Rule Builder and Classification Importer, which provide automated and user-friendly interfaces for categorizing data. These tools are designed to handle dynamic data and reduce manual effort.

As of 2025, Adobe has introduced enhanced classification tools that offer more flexibility and automation compared to the traditional SAINT method. While SAINT classifications are still supported, many organizations have transitioned to using the newer Classification Rule Builder and Importer for their improved efficiency and ease of use. Therefore, while SAINT classifications remain relevant, leveraging the latest tools is recommended for optimal data management and analysis.

What are the benefits of Classification in Adobe?

Following are the key benefits:

• Enhanced Reporting: Transform raw data into meaningful information, making reports more insightful.
• Improved Data Analysis: Facilitate deeper analysis by grouping related data points.
• Operational Efficiency: Reduce the need for complex data processing by enriching data within Adobe Analytics.

By effectively utilizing classifications, you can gain a more comprehensive understanding of your digital data, leading to informed decision-making and optimized strategies.

Additional article links:

1. Classification Overview
2. Classification Use Cases

Hope this article on Classification brings you one step closer to understanding data organization and correlation in Adobe Analytics. Stay tuned for more #AdobeAnalytics posts and don't forget to continue #DecodingDigital