Picture this: you're paying $2,400/month for Fivetran feeding data into BigQuery, visualized in Looker. A contractor maintains the pipelines. Total data stack cost: ~$5,500/month.
What are you actually using it for? Checking six numbers every Monday morning. MRR. New customers. Churn. Pipeline. ROAS. Support backlog. Six numbers. $5,500/month.
The Problem With "Proper" Data Infrastructure for SMBs
Enterprise data stacks are built for enterprise problems: petabyte-scale data, hundreds of analysts, complex joins across dozens of source systems. Most SMBs don't have that problem. They have six to fifteen business metrics they want to watch weekly, and they're massively overpaying for infrastructure designed for a different use case.
The hidden cost isn't even the tooling — it's the maintenance. ETL pipelines break. Schema changes in HubSpot cascade into broken dashboards. Someone has to fix them. That person charges by the hour.
What the Math Actually Looks Like
Say you're tracking 30 metrics — a comprehensive scorecard for a business with $2M–$10M ARR. At $1/metric/month with Orbit Scorecard, that's $30/month. No pipeline maintenance. No warehouse. No contractor. The integrations connect directly to your source systems and sync automatically.
The Trade-Off Is Real
We won't pretend Orbit Scorecard replaces a full data warehouse for every use case. If you need complex multi-touch attribution across a dozen ad channels, you probably still need a data engineer and a proper warehouse.
But if what you actually need is a reliable weekly view of your key business metrics — with red/yellow/green status, owned by named team members, reviewed at your Monday meeting — Orbit Scorecard is purpose-built for that at a fraction of the cost.