> ## Documentation Index
> Fetch the complete documentation index at: https://docs.permutive.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Understanding Identity Overlap

> How to interpret the Slicer tab pivot table, including how to read overlap percentages and identify relationships between identifiers

## Overview

The Slicer tab in Identity Insights displays identity overlap in a pivot table format, showing how different identifiers relate to each other. Understanding how to read this table helps you assess identifier relationships, identify gaps in your identity graph, and evaluate vendor performance.

<Info>
  **Prerequisites:**

  * Access to Identity Insights dashboard
  * At least two identifiers configured and collecting data
  * Identity overlap data is updated daily
</Info>

## Steps

<Steps>
  <Step title="Open the Slicer tab">
    Navigate to **Identity > Identity Insights** and ensure you're on the **Slicer** tab (this is the default view).
  </Step>

  <Step title="Understand table orientation">
    The pivot table reads **top-to-bottom** rather than left-to-right. Start with the identifier in the top row, then read down the column to see overlap percentages.
  </Step>

  <Step title="Read overlap percentages">
    For each identifier in the top row, read down its column to see what percentage of users with each identifier also have the top-row identifier. For example, if AppNexus is in the top row, reading down shows what percentage of users with each identifier also have AppNexus.
  </Step>

  <Step title="Switch to absolute values">
    Use the view toggle to switch between percentage overlap and absolute values (sum view). Absolute values show the actual number of users who have both identifiers.
  </Step>

  <Step title="Identify relationships">
    High overlap percentages indicate strong relationships between identifiers - these identifiers are commonly found together. Low overlap may indicate gaps in identity collection or resolution.
  </Step>

  <Step title="Assess identifier scale">
    Use the table to understand the relative scale of each identifier and how they compare to each other. This helps identify which identifiers provide the most coverage in your identity graph.
  </Step>
</Steps>

### Reading the Pivot Table

**Example interpretation:**

* If `email_sha256` is in the top row and `appnexus` shows 45% in its column, this means 45% of users with AppNexus also have a hashed email
* If `appnexus` is in the top row and `email_sha256` shows 30% in its column, this means 30% of users with hashed emails also have AppNexus
* The percentages are not symmetric - they represent different perspectives of the same relationship

<Tip>
  **Tips for interpreting overlap:**

  * High overlap (70%+) between two identifiers indicates they're commonly found together and may have similar user coverage
  * Low overlap (under 20%) may indicate the identifiers target different user segments or there are gaps in collection
  * Use absolute values to understand the actual scale of overlapping users
  * Compare overlap percentages across different identifier pairs to identify the strongest relationships
  * Overlap data helps assess which identity vendors are performing well relative to each other
</Tip>

<Warning>
  **Important:**

  * The pivot table orientation (top-to-bottom) can be counter-intuitive - always start with the top-row identifier
  * Overlap percentages are directional - the percentage depends on which identifier is in the top row
  * Identity overlap data reflects the Past 7 Days and Past 30 Days - recent changes may take time to appear
  * Identifiers that have been removed from your allow-list may still appear if data was collected in the reporting time range
</Warning>

## Next Steps

<CardGroup cols={2}>
  <Card title="Accessing Identity Insights" icon="sign-in" href="/guides/signals/identity/accessing-identity-insights">
    Learn how to navigate the Identity Insights dashboard
  </Card>

  <Card title="Monitoring Data Ingestion" icon="chart-bar" href="/guides/signals/identity/monitoring-data-ingestion">
    Track daily data collection patterns
  </Card>

  <Card title="Back to Identity Insights" icon="arrow-left" href="/products/signals/identity/identity-insights">
    Return to Identity Insights overview
  </Card>
</CardGroup>