You can slice and dice your customer data in powerful ways using filters in Baremetrics. Whether you're analyzing churn, segmenting high-value accounts, or targeting trial users, filters help you zoom in on exactly the group you care about.
This guide breaks down all available filters, pulled from Stripe, your billing behavior, and enrichment tools like Clearbit, so you can create precise segments and gain the insights you need quickly.
Related Guides
How to segment your metrics - A guide to building and saving segments
Customer augmentation - Enrich your customers with external company and person data
This guide covers all default filters available in Baremetrics. If you're passing in custom attributes, don’t worry - we’ll automatically create a filter for every one of those too.
Let’s dig in 👇
👤 Customer Info
Email Address: Filter by full or partial (e.g.,
@acme.com
)Provider / Source: Identify payment provider/billing source (e.g., Stripe or multiple Stripe instances)
Signup Date: Track cohorts or churn over time
Unsubscribed from Emails: See who’s opted out (Messaging, Recover, etc.)
Customer ID: Payment Provider's unique identifier for a customer
Notes: Search internal notes saved to a customer's profile
💳 Payment Activity
Total Charges Count: Count of all charges, ever
Recurring Charges Count / Value: Subscription-only payments
One-Time Charges Count / Value: Non-subscription purchases
→ Spot high spenders, upsells, or freemium upgrades
💰 Revenue & Subscription
Current MRR: Today’s monthly recurring revenue
LTV: Total customer spend
Plan / Plan Months / Canceled Plan: What they signed up for, and how long
Cancellation Reason: Stripe-provided feedback
Current Stripe Products: Active product identifiers
Last Known MRR / Plan / Products: For analyzing current and churned customers
→ Useful for churn analysis and cohort comparisons
📉 Lifecycle Status
Canceled?: True if the account is canceled
Active Subscription? / Count: Who’s still subscribed, and how many subscriptions
Is Trialing?: In trial phase
Is Delinquent?: Payment failed but not canceled
Cancellation / Conversion / Delinquent Date: Key lifecycle milestones
🏢 Enrichment Data (via Clearbit)
Company
Name / Description / Tags
Location: Country, state, city
Industry / Sector / Sub-industry
Tech Stack: e.g., “uses HubSpot”
Employees / Revenue / Founded Year
Twitter Followers / Amount Raised
Person
Full Name / Email
Country / Gender
Role / Seniority: e.g., “CEO”, “Director”
Twitter Followers: Social reach proxy
💡 Example Use Cases
Here are some common ways you can combine filters to answer key questions or take action on specific segments.
Goal | Filters to Use | Why It’s Useful |
Find churn risks before they cancel |
| Identify valuable customers with failed payments before they churn |
Compare churn rates for monthly vs. annual plans |
| Include churned accounts to compare how plan intervals impact retention. |
Spot lost revenue from big accounts |
| Focus on enterprise churn with high revenue impact |
Re-engage trial users who ghosted |
| Find users who finished the trial but never converted |
Identify usage-based churn |
| Spot users who churn quickly after light usage |
Find happy customers to ask for reviews |
| Target long-time, paying, engaged customers for advocacy |
Upsell Opportunities |
| Find engaged customers with a history of spending
|
Measure campaign success by source |
| Analyze ROI of recent paid acquisition campaigns |
Compare ARPU by customer size | - Bucket 1: | Understand where the most revenue comes from, even if customers have churned. This avoids excluding $0 Current MRR users who paid substantially in the past. |