Revenue that compounds, cohort by cohort

It groups your customers by when they joined — by month, source, segment, or campaign — then tracks how each group retains and spends over time. MarkAge360 builds the full picture: a clean revenue data model, cohort and segmentation design, retention and churn analytics, LTV with CAC payback, revenue segmentation, and growth forecasting. The output is one operating view that shows which customers, channels, and campaigns create durable, profitable growth rather than one-off spikes.

Pricing depends on how many data sources we unify, the state of your event and revenue tracking, and whether you want a one-time analysis or living dashboards on a decision cadence. We usually scope an initial build — data model, cohort design, and the first retention and LTV views — then a lighter ongoing rate to maintain the model and run the weekly review. We share a fixed quote after a short discovery call so there are no surprises.

If your underlying data is reasonably clean, we can stand up the first cohort and retention views in a few weeks. Building a trustworthy revenue model with a single customer ID and join date is the part that takes the most care, since every metric downstream depends on it. LTV and forecasting curves get more accurate as more months of cohort history accumulate, so the value compounds over time.

Most platform dashboards report blended, period-over-period numbers — this month versus last month — which hides whether the customers you acquired actually stay and spend. Cohort analytics reads behaviour by the group that produced it, so you can see which acquisition routes build durable customers and where churn quietly leaks revenue. We connect cohorting, retention, and LTV into one workflow, so spend decisions are steered by quality, not just last-click volume.

We work with your existing stack — analytics like GA4, your CRM and billing or subscription system, ad platforms, and your data warehouse where one exists. We unify signups, orders, renewals, refunds, and spend into a clean model, then surface cohort, retention, and revenue views in BI dashboards your team already uses. We don't force a rip-and-replace; the goal is one trusted source the whole team reads the same way.

Success is measured by the decisions the analytics change, not by the number of charts. We track LTV:CAC, CAC payback windows, net revenue retention, and revenue by cohort, then tie those numbers to a weekly review where spend and retention actions get made. When the model shows a channel building higher-LTV cohorts or a fix that genuinely held a leak, that's the ROI — budget moving toward durable growth instead of vanity volume.