Your MRR dashboard says one thing. Your finance team says another.

SaaS and subscription businesses run on recurring revenue metrics: MRR, ARR, net revenue retention, churn, LTV. These numbers determine fundraising, board decisions, and company valuation. The problem is that most subscription companies cannot produce them reliably.

Billing data sits in one system. Product usage lives in an event stream or analytics tool. CRM holds the customer relationship timeline. Marketing has attribution data from ad platforms. Each system reports its own version of the customer, and none of them agree on revenue. The subscription data model — with its upgrades, downgrades, pauses, credits, and multi-plan structures — makes reconciliation genuinely difficult without a proper data layer.

CorrDyn works with multiple subscription-based businesses across commerce, education, and services. The patterns repeat: connect billing to product to marketing, build a single governed layer, and produce the metrics that leadership trusts.

Revenue reporting that finance trusts. We build data pipelines that reconcile billing data — whether from Stripe, Recharge, Chargebee, or a custom system — with your general ledger, then transform it into MRR, ARR, and cohort-level revenue metrics. At a subscription commerce client, we unified data from multiple sales channels and marketing platforms into dashboards that replaced a patchwork of disconnected reports and manual pulls.

Churn and retention analytics. Cohort retention curves, voluntary vs. involuntary churn separation, and leading indicators that flag at-risk accounts before they cancel. The goal is not just reporting what happened, but identifying the usage patterns and engagement signals that predict what will happen next. At an online university, this approach supported 87% annual revenue growth by giving leadership visibility into the full student lifecycle.

Marketing attribution through the full funnel. Most SaaS companies can tell you which campaigns generated leads. Few can trace a dollar of marketing spend through to LTV, renewal rate, or expansion revenue at the cohort level. We connect ad platform spend to billing system revenue so you can see true customer acquisition cost by channel. For a DTC subscription brand, this enabled the product team to cut their portfolio by a third, eliminating spend on products that did not generate profitable subscriptions.

Cost-effective data infrastructure. SaaS companies at growth stage often inherit data stacks that cost more than the insights justify. We have cut ELT costs by 80% for one subscription client, migrated another off an oversized warehouse, and helped multiple clients right-size their infrastructure spend. We evaluate actual data volumes and query patterns before recommending changes.

From our podcasts: [8 Ways to Survive the SaaSpocalypse](/podcasts/eventual-consistency/ep-16-saaspocalypse-survival).

Subscription metrics are harder to get right than they look. MRR calculation alone has edge cases around trials, credits, multi-currency, prorations, and plan changes that most dashboards get wrong. We have built these calculations for enough subscription businesses to know where the numbers break and how to fix them. We also stay engaged: our average client relationship is over 5 years, which matters for a SaaS company that needs its metrics to remain accurate as the billing model evolves.