What is ARR/MRR?
ARR/MRR is Annual Recurring Revenue (ARR) and Monthly Recurring Revenue (MRR) measure the predictable, recurring revenue from subscriptions.
Definition
MRR is the total predictable revenue normalized to a monthly figure. ARR is MRR multiplied by 12. These metrics exclude one-time fees, professional services, and usage overages. There are several flavors: New MRR (from new customers), Expansion MRR (upsells and add-ons), Contraction MRR (downgrades), and Churned MRR (cancellations). Net New MRR combines all four. Investors and boards care about Net Revenue Retention (NRR), which is the percentage of ARR retained from existing customers including expansion and contraction.
Why It Matters
ARR and MRR are the heartbeat metrics of any subscription business. They tell you whether your revenue engine is accelerating or stalling. A company growing ARR at 50% year-over-year with 120% NRR is in fundamentally different shape than one growing at 50% with 80% NRR. The first is expanding within its base; the second is churning and replacing.
Example
A company starts January with $1M MRR. During the month, they add $80K New MRR, $30K Expansion MRR, lose $15K to Contraction MRR, and $25K to Churned MRR. Their Net New MRR is $70K, ending January at $1.07M MRR ($12.84M ARR).
Best Practices for ARR/MRR
Start with Clear Requirements
Before adopting any arr/mrr tooling, document what specific problems you need to solve. Teams that skip this step end up with tools that don't match their actual workflow. Write down your current pain points, the volume of data you handle, and the outcomes you expect.
Evaluate Against Your Existing Stack
The best arr/mrr solution is one that connects to what you already use. Check integration support with your CRM, data warehouse, and other tools before committing. A standalone tool that doesn't sync with your existing systems creates more work than it saves.
Measure Before and After
Set baseline metrics before you implement any changes to your arr/mrr process. Track data quality, time spent on manual tasks, and downstream conversion rates. Without a baseline, you can't prove ROI or identify regressions.
Build Internal Documentation
Document how arr/mrr fits into your data operations. Include which fields are affected, which systems are involved, and who owns the process. When team members leave or tools change, this documentation prevents knowledge loss.
Common Mistakes with ARR/MRR
Treating It as a One-Time Project
ARR/MRR requires ongoing attention. Data decays, requirements shift, and tools update their capabilities. Teams that set up a arr/mrr process and never revisit it end up with stale or broken workflows within 6 to 12 months.
Ignoring Data Quality Upstream
No amount of arr/mrr tooling fixes bad data at the source. If your input data is full of duplicates, formatting errors, or outdated records, the output will carry those same problems forward. Clean your source data first.
Over-Investing in Tools Before Process
Buying an expensive platform before you have a defined process for arr/mrr wastes money. Start with a clear workflow, test it manually or with basic tools, and then invest in automation once you know exactly what you need.
Not Auditing Results Regularly
Automated arr/mrr processes can drift over time. Schedule quarterly audits to check accuracy rates, coverage gaps, and whether the output still matches your team's needs. Catching issues early prevents compounding errors.
How ARR/MRR Connects to Your Stack
ARR/MRR rarely operates in isolation. It sits within a broader data and sales technology stack, and understanding where it fits helps you choose the right tools and build effective workflows.
CRM Systems
Your CRM is the central repository where arr/mrr data gets stored and used. Whether you run Salesforce, HubSpot, or another platform, the arr/mrr tools you choose should write data directly into CRM records without manual import steps.
Data Warehouses
For teams with analytics infrastructure, arr/mrr data often needs to flow into a data warehouse like Snowflake or BigQuery. This lets analysts build reports that combine arr/mrr signals with revenue data, usage metrics, and other business intelligence.
Sales Engagement Platforms
Outreach tools like Salesloft and Outreach rely on accurate data to personalize sequences. ARR/MRR feeds these platforms with the information sales reps need to write relevant messages and target the right prospects at the right time.
Marketing Automation
Marketing platforms use arr/mrr data for segmentation, lead scoring, and campaign targeting. The more complete and accurate your data, the better your marketing automation performs across email, ads, and content personalization.
Tools for ARR/MRR
Find the Right ARR/MRR Tool
Not sure which tool fits your needs? Check out our curated recommendations: