---
title: "Correspondence analysis"
url: "https://helpdesk.telmarhelixa.com/en/article/correspondence-analysis"
language: "en"
last_updated: "2026-10-27T15:24:16.399Z"
---

# Correspondence analysis

Condenses multi-variable categorical relationships onto a two-dimensional perceptual grid (CA).

## **Setup and display**

-   Plots **Factor 1** (horizontal) against **Factor 2** (vertical), aiming for at least **70%** combined variance explained.
-   Metrics: Percent Influence (% INF), Absolute Contribution (ABS), Relative Contribution (REL).
-   **Entity delineation:** row variables and column variables are shown with distinct symbols and color markers, separating profiled entities (such as brands) from descriptive attributes (such as lifestyle indicators).
-   **Custom axis labels:** rename Factor 1 and Factor 2 (for example "Value vs. Premium" and "Traditional vs. Modern") for presentation-ready maps.
-   **Annotation styling:** Annotation Mode supports custom line and text annotation colors (shared with Explore - P-Maps).

## **Use cases and benefits**

-   **Segmentation and targeting:** identify audience segments and their preferences, for example from media consumption habits, to fine-tune targeting.
-   **Media channel optimization:** see how media platforms relate to consumer responses or brand metrics to allocate budget.
-   **Competitor analysis:** like Cluster Analysis, cluster brands and products into competitive sets; brands sharing a factor compete more with each other.
-   **Identifying psychographic drivers:** run **before** a Cluster Analysis to find which psychographic variables have the strongest associations with audience segments and products.

## **Interpreting the map**

-   **Factors:** typically Factor 1 on the X axis (left to right) and Factor 2 on the Y axis (top to bottom).
-   **Proximity:** items close together are very similar (for example brands or age groups).
-   **Relationships between items:** to relate active rows and columns (for example a brand and a demographic), draw lines to the origin (zero). **Obtuse angles** indicate a negative correlation.
-   **Distance from center:** the closer an item is to the center, the less the map says about it; the further from the middle, the more strongly it relates to something else on the map.
-   **Variance explained:** a robust analysis reaches 70% or more across Factor 1 and Factor 2 combined.

## **Key metrics in the results table**

| Metric | Definition |
| --- | --- |
| % INF (Percent Influence) | Contribution each variable makes to the overall analysis; higher means more relevant to market differences. Often sorted by % INF before a Cluster Analysis to find the most influential variables. |
| ABS (Absolute Contribution) | The "value" of each statement or brand within the factor. Higher ABS means the factor explains that variable better. Can be read like %Col in Crosstab. |
| REL (Relative Contribution) | Decides which side of the graph a brand or lifestyle statement appears on. For Factor 1, "-" is on the left and "+" on the right. Shows which factor best explains the brand or demographic. Can be read like %Row in Explore. |