How to Build Audiences in the FanCRM

The FanCRM is the brain for your fan data.

It's our customer data platform that lets you search, segment, create filters, and view fan profiles in one place. FanCRM gives you a complete fan history - from first engagement to purchase - so you can personalize messaging and experiences across the fan lifecycle.

What the FanCRM is (and what it's not)

The FanCRM is:

• A central system for fan profiles and history
• A flexible audience builder for marketing, sponsorship and retention
• A way to turn fan activity into actionable segments

The FanCRM is not:

• A one-click audience generator
• A replacement for strategy or messaging decisions
• A static database

Think of the FanCRM as a decision engine: the better your question, the better your audience.

This guide will help you build targeted audiences by teaching you how to think about FanCRM queries, not just which filters exist.

1. Start with the Goal (not the filters)

Before selecting any parameters, ask yourself: What am I trying to do?

Most FanCRM audiences fall into one of these categories:

• Re-engage inactive fans
• Reward or recognize loyal fans
• Activate sponsor-ready segments
• Exclude recent winners or buyers
• Understand who is most likely to convert again

Once you have a clear goal, the filters become much easier to choose.

2. The FanCRM Audience Formula

Most FanCRM queries can be broken down into 4 parts:

Audience = WHO + BEHAVIOUR + TIME + EXCLUSIONS

You don't need all four every time, but this framework will help keep your queries focused and intentional:

WHO are you targeting?

These filters define who belongs in the audience. Common examples:

• Location (city, region, radius)
• Age or gender
• Fan rating
• Fan source (how they entered your FanCRM)
• Tags or snapshots

If you're structuring or organizing fan data, see: Custom fields (link) & Tagging best practices (link)

WHAT have they done (or not done)?

These filters define fan behaviour. Common examples:

• Participated in a campaign
• Purchased tickets or merchandise
• Attended an event
• Clicked on an email or SMS
• Scanned into a venue

If you're working with campaign engagement, purchases or attendance data, you can see the FanCRM Playbook (Link)

WHEN did it happen?

Time adds meaning to behaviour, and in fact, the more timely, the more impactful. Common examples:

• Actively participated in the last 30 days
• Added tothe FanCRM within a specific date range
• Inactive (no participation) for 90+ days
• Purchased within a specific date range
• Attended an event this season

Time-based filters help you distinguish recent intent from historical interest.

WHO should be excluded?

Exclusions keep your messaging and targeting relevant. Common exclusions:

• Fans who already purchased
• Fans missing required consent or data

Good exclusions prevent fatigue and improve performance.

Common Audience Filters/Recipes (Start Here)

If you’re not sure where to begin, these audience “recipes” are a great way to start. Each one uses the same FanCRM logic, just applied to a different goal.

Each “recipe” includes:

• The goal
• Suggested filters
• Why it works
• Where to learn more

Recipe 1: Recently Inactive Fans (Re-Engagement)

Goal: Re-engage fans who haven’t interacted with you recently

Filters to use:

• Campaign Activity —> Days Recently Inactive (e.g. 60 - 90 days)

Optional refinements:

• Location (local relevance)
• Fan Rating (prioritize higher-value fans)

Why it works: Target fans who already know you without spamming your most active audience.

 

Recipe 2: High-Value Fans (Loyalty & Rewards)

Goal: Identify your most engaged or valuable fans

Filters to use:

• Minimum Fan Rating
• Purchase —> Sales Amount Minimum
• OR Campaigns Participated In (Multiple campaigns)

Optional Refinements:

• Purchased/Participated within the last season

Why it works: Combines value + engagement to find fans worth rewarding or studying.

 

Recipe 3: First-Time Engagers (Nurture)

Goal: Welcome and nurture new fans

Filters to use:

• Created Between (recent dates)
• Campaigns Participated in = 1
• Exclude fans with purchases

Optional refinements:

• Fan Source = campaign
• Location-based messaging

Why it works: First impressions matter, and this audience is early in their lifecycle

 

Recipe 4: Sponsor-Ready Audience

Goal: Build a clean, defensible audience for sponsor activations.

Filters to use:

• Limit Values Positive (e.g. email subscribed = true)
• Location or event attendance
• Age or demographic constraints (if required)

Exclusions:

• Missing consent fields
• Recent winners (if applicable)

Why it works: Ensures the audience is compliant, relevant and measurable.

 

Recipe 5: Exclude Recent Buyers (save Ad Money)

Goal: Prevent messaging/ads to fans who have already converted.

Filters to use:

• Purchased X within the last X days

Applied as:

• Exclusion filter on any campaign audience

Why it works: Improves relevance and avoids over-messaging