---
title: How Do I Interpret Fan CRM Stats?
description: The Stats section in Fan CRM is your ticket to understanding the demographic and psychographic behaviours of your fanbase, complete with easy-to-understand visualizations and filters to dig deeper.
---
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# How Do I Interpret Fan CRM Stats?
## The Stats section in Fan CRM is your ticket to understanding the demographic and psychographic behaviours of your fanbase, complete with easy-to-understand visualizations and filters to dig deeper.
**All this data is great, now tell me what it means!**
**Before we dive in, let's go over some quick disclaimers about the information presented in this section:**
- Age ranges are determined by birthday fields pulled from social login or ticketing data
- Gender is either determined through social login or name matching
- Education and income psychographics are determined by mapping postal/ZIP code against publicly available census data
- Ethnicity psychographics are estimated using AI, based on fan first and last names across global regions (APAC, LATAM, PANAM, etc.)
- Results are most accurate when based on a large sample. These results are meant as a guideline for further investigation, and may not be 100% accurate as a result of the data sources being utilized for stats. Consider the results with a pinch of salt, especially if you have small sample sizes
- Consider the Sample Size provided against each well
**Now, let's chat about all the fancy options and stats that are presented on the "Stats" page:**
- **Refine Results:** Allows you to drill a little deeper into your pre-built segments and understand the demographics of the chosen segments. You can refine and analyze the fans that are present within a filter, a snapshot (a filter at a particular point in time), participants of a particular campaign or based on tags applied to fans. **If no elements are chosen, stats are displayed for all the fans in your CRM.** If you choose any parameter, click "Apply" once chosen to have the stats reflect the chosen segment.
- **Share Report:** Generates a link to share the report with sponsors or colleagues that do not have access to your Tradable Bits account. Please note that anyone with the link will be able to see your report, so keep it private. You can delete the link and thus revoke access at any time. You can set a name for the report and a brief description of the report.
- **Fans:** Displays the number of fans in the chosen segment.
- **First Fan Created:** The date when the first fan was added to the segment.
- **Last Fan Created:** The date when the last fan was added to the segment.
- **Fan Source Breakdown**: Shows how many fans in the database are connected through certain sources (Click *'**Load Additional Summary Stats'*** to view)
- **Top Fan Network Breakdown:** Shows how many fans in the database are connected to certain networks (Click *'**Load Additional Summary Stats'*** to view)
- **Age Breakdown:** A breakdown of the count of fans in various age ranges, further segmented by gender. Age ranges are determined by birthday fields pulled from social login or ticketing data.
- **Gender Breakdown:** A breakdown of the genders of your fans within the segment.
- **Ethnicity/Education/Household Income/Family Breakdown:** These charts and numbers reflect the breakdown of the corresponding demographics within your segment. The data is determined by mapping postal/ZIP code against publicly available census data. Ethnicity data is estimated using AI, based on fan first and last names across global regions.
- **Locations Breakdown:** Provides a variety of visualizations related to the locations where your fans are engaging with you from.
- **Load Idols Affinity Stats:** The Idol Affinity section builds Clusters of Idols that large sections your fans have shown a common interest in. Artists within a cluster are artists that fans have shown a common interest in. For example, if Billie Eilish and Taylor Swift are in the same cluster, then fans that have displayed an affinity towards Billie Eilish are also very likely to display an affinity towards Taylor Swift. This information can be used to advise your marketing communication and advertising strategy. For example, if you've got a show that Billie Eilish is headlining, then you could target fans that have shown an interest in Taylor Swift as well. If you want really concrete common interests, you can increase the number of clusters created and hit "Re-Cluster".
- **Top Artists:** Displays the top artists that your fans have shown an affinity for, alongside the percentage of fans within the segment that have shown an interest in the artist.
- **Top Interest Stats:** Displays the top areas of interest for your fans across a variety of categories. These can serve as thought starters for partnerships or possible advertising channels.
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