"Self-service BI" and "embedded analytics" sound related but solve different problems. If you're evaluating BI tools right now, the choice between them shapes which products even belong on your shortlist. Here's the practical difference.
Self-service BI is internal-facing
Tools in this bucket — Tableau, Power BI, Looker, clariBI — are for your own team. The users are employees with logins. The dashboards are about your business. The currency is "how fast can a non-data person get an answer".
Self-service BI optimizes for:
- Time-to-first-insight for non-technical users.
- Breadth of integrations across your own operational tools.
- Collaboration features (comments, sharing, scheduled reports).
- Governance — who in your company can see what.
Embedded analytics is customer-facing
Tools in this bucket — Sigma, Cube, Embeddable, Metabase's embed mode — are for your customers. They live inside your product. The users are external. The dashboards are about each customer's own data inside your application.
Embedded analytics optimizes for:
- White-labeling and theming to match your product.
- Row-level security so each customer sees only their own data.
- SDKs and APIs for tight integration with your application.
- Performance under concurrent multi-tenant load.
How to tell which one you actually need
Ask: who are the users?
- Your own team: self-service BI.
- Your paying customers: embedded analytics.
- Both: almost always two different tools. Treat them as separate purchases.
Where clariBI fits
clariBI is self-service BI. The product is designed for your internal team to ask questions about your business data — Stripe, HubSpot, Linear, your databases, your CSVs. It's not a customer-facing embedded analytics product. If you're building analytics into a SaaS product for your customers, look at Sigma, Cube, or similar.
If you're trying to solve "how does my team understand our own business", clariBI is in the conversation. Start a free trial and connect one of your operational tools.
The middle ground that doesn't exist (yet)
Several tools claim to do both. In practice, the product opinions for these two use cases pull in opposite directions — internal users want flexibility and breadth; external users need stability and tight integration. Most teams end up with a self-service BI tool for internal use and a separate embedded tool for product analytics. Plan for that from the start.