Analytics & BI · 12 min read · May 2026
Embedded Analytics for B2B SaaS in 2026: The Buyer Guide
By Thinklytics Partners, Analytics & BI Practice
Every B2B SaaS PM has the same conversation in 2026: customers want a customer-facing analytics layer, the build-vs-buy decision is harder than it looks, and the wrong call costs 12-18 months. Honest comparison of Sigma, Cube, Looker Embed, Power BI Embedded, and the build-it-yourself path, with a 5-question framework that ends the debate.
Topics covered
- embedded analytics
- B2B SaaS analytics
- Sigma embedded
- Cube embedded
- Looker Embed
- Power BI Embedded
- white-label analytics
- multi-tenant analytics
Frequently asked questions
What is embedded analytics for B2B SaaS?
Embedded analytics is the customer-facing reporting and dashboard layer inside a SaaS product. Examples: HubSpot's reporting tab, Stripe's revenue dashboards, Intercom's conversation analytics. The customer logs into your product and sees charts about their own data, scoped to their tenant. Build vs buy spans from raw chart libraries up to white-label BI platforms.
Build vs buy for embedded analytics?
Build with chart libraries (Recharts, Highcharts, Plotly) when the analytics are tightly coupled to your product UX and you have one or two specific dashboard views. Buy embedded BI (Sigma, Cube, Looker Embed, Power BI Embedded) when customers want self-service exploration, custom reporting, or a metrics catalog. The build path is cheaper for narrow scope; the buy path scales much better past 3-5 dashboards.
Sigma vs Cube vs Looker Embed vs Power BI Embedded?
Sigma is the strongest interactive spreadsheet-style experience for end-customers; works best when your customers are spreadsheet-fluent. Cube is the developer-friendly headless BI / semantic layer; you build the UI yourself but Cube does the modeling. Looker Embed is the most mature for governed enterprise SaaS but Google has slowed investment. Power BI Embedded is the cheapest at scale if your customers are Microsoft-fluent. Each fits a different buyer profile.
How do we handle multi-tenant data isolation?
Three options. (1) One dataset per tenant in the warehouse, joined at query time via a tenant ID predicate. Cleanest, scales to thousands of tenants. (2) Schema-per-tenant. Cleaner isolation, harder to manage past 50 tenants. (3) Database-per-tenant. Strongest isolation, only feasible for small tenant counts (under ~50) due to cost and operational overhead. Most B2B SaaS we work with land on option 1 with row-level security tied to tenant ID.
What does embedded analytics cost?
Build-your-own with a chart library: $0 license + 4-12 weeks of engineering. Cube Cloud: $1K-$10K/month depending on tenant count. Sigma Embedded: $20K-$200K/year depending on tenant count and features. Looker Embed: $50K-$500K+/year typically requires Google sales conversation. Power BI Embedded: capacity-based ($1K-$15K/month) plus per-user fees in some configurations.
When should we replace our build with a vendor?
When customers start asking for self-service exploration, custom reporting, scheduled exports, alerting, or a metrics catalog. The build path tops out at static dashboards; the buy path is what gives you 'here's our data, slice it however you want.' Most SaaS reach this inflection at 30-100 customers depending on segment.
Can we use the same BI tool for internal AND embedded?
Yes, in some configurations. Power BI Embedded uses the same engine as internal Power BI deployments. Sigma works for both. Cube is headless so it sits underneath whatever UI you build. Looker historically powered both internal and embedded. Tableau Embedded API exists but is less common. The dual-use approach saves on tool sprawl but the embedded use case usually has stricter requirements that drive the platform decision.