Data & BI Dashboards for SaaS & Software Products
MRR, churn and CAC calculated differently by every person who has ever produced a board deck.
Business intelligence work consolidates data from ad platforms, CRM, your product and your accounting system into one warehouse, with agreed metric definitions, and presents it as dashboards. For a SaaS company, the work is judged on a qualified trial or demo that converts to a paid plan. Agreed definitions in the warehouse, with cohort retention and payback computed the same way every month.
What is costing you money today
MRR, churn and CAC calculated differently by every person who has ever produced a board deck.
Treating sign-ups as the goal, so the site and the ads fill the funnel with people who will never pay and hide the real acquisition cost.
What changes once this is in place
Agreed definitions in the warehouse, with cohort retention and payback computed the same way every month.
How saas & software products actually buys
Self-serve in a day, sales-assisted over one to three months with a security review and a procurement step near the end.
- The unit of value
- a qualified trial or demo that converts to a paid plan
- The common mistake
- Treating sign-ups as the goal, so the site and the ads fill the funnel with people who will never pay and hide the real acquisition cost.
- What we do instead
- Define the activation event that predicts payment, instrument it, and optimise acquisition against that instead of against sign-ups.
What it has to talk to
A build for a SaaS company is mostly integration work. These are the systems we expect to exchange data with:
- Stripe / billing
- Product analytics
- CRM & sequences
- Auth & multi-tenancy
- Data warehouse
The words your buyers actually use
Generic service copy loses to copy written in the vocabulary of the vertical. These are the terms that carry intent here, and the ones the pages we build are structured around:
- free trial
- pricing per seat
- integrations
- SOC 2
- onboarding
- churn
- self-serve vs demo
The rules this sits under
GDPR for any EU user, SOC 2 evidence demanded by enterprise buyers, and data-residency commitments that constrain where you deploy.
What you get
- Metric dictionary — Every metric that matters, defined in a sentence, agreed by the people who use it. The most valuable and least exciting deliverable here.
- Data pipelines — Automated extraction from ad platforms, CRM, store, product and accounting systems, with failure alerting.
- Warehouse — A modelled layer where the joins and transformations live once, so every dashboard reads the same numbers.
- Dashboards — Executive, marketing, sales and operations views, each built around the decisions that audience actually makes.
- Attribution model — Spend joined to leads joined to closed revenue, with the model's limitations stated rather than hidden.
- Automated distribution — Scheduled summaries to email or Slack, so the numbers reach people who will not open a dashboard.
- Alerting — Thresholds on the metrics that matter, so a problem announces itself rather than waiting for the monthly review.
- Documentation and training — How the data flows, what each metric means, and how to add a chart without breaking anything.