Embedded Analytics
for SaaS Companies
A practical framework for SaaS product leaders evaluating analytics platforms based on real-world experience, not vendor hype.
8 min read
Why this guide exists
The SaaS application market is fiercely competitive. Vendors face immense pressure to innovate rapidly, while customers increasingly need to justify their return on investment. Embedded analytics play a crucial role in helping SaaS companies retain customers, win new business, and drive new revenue streams.
This guide is designed to help product managers, technologists, and business leaders evaluate analytics platforms based on real-world requirements—focusing on the less glamorous but far more critical platform capabilities that drive lasting success.
Eight guiding principles for evaluation
These principles can save you time, help you cover more ground, and avoid spending time on undifferentiated product areas.
- 01
Multi-tenancy: don't assume feature parity
Many general-purpose BI platforms offer reduced or altered functionality in multi-tenant deployments. Validate how well a platform supports multi-tenancy in practice—not just in theory.
- 02
Avoid being misled by visual appeal
Attractive interfaces rarely determine long-term success. Most SaaS companies will customize the visual layer to match their branding. Focus on the capabilities that will make or break your deployment.
- 03
Evaluate AI: prioritize flexibility over novelty
Today's cutting-edge AI features may become obsolete within months. Evaluate platforms by their ability to flexibly integrate new AI capabilities as they emerge—not by the novelty of current features.
- 04
Don't overinvest in commonplace features
Capabilities like interactive dashboards and standard visualizations are ubiquitous. Spend your evaluation time on the edge capabilities that separate a functioning platform from one that fuels growth.
- 05
Use analytics to differentiate your product
The analytics platform you choose directly shapes your product's differentiation. Prioritize platforms with distinctive features that resonate with your users and set your product apart.
- 06
Plan for evolving requirements
SaaS companies face unpredictable future needs driven by shifting markets, competition, and regulation. Prioritize flexibility—the right platform must adapt to tomorrow's unknowns.
- 07
Value-added services also matter
The right partner can help shape your monetization strategy—identifying how analytics delivers differentiated value and uncovering new revenue opportunities. Evaluate the company, not just the product.
- 08
Prioritize proven SaaS experience
A vendor's depth of experience in serving SaaS companies, understanding multi-tenant architectures, and history of successful deployments are strong indicators of future success.
Four critical areas for platform evaluation
These are the pillars of a resilient analytics strategy. Focus your evaluation here.
Self-service experience
Self-service capabilities—such as building dashboards, customizing visualizations, and modifying datasets—are essential for empowering customers and reducing support overhead. However, multi-tenancy introduces unique challenges. Features that work well in a single-tenant setup may not scale or function the same way across multiple tenants.
When evaluating self-service functionality, confirm that capabilities are not only present but also secure, scalable, and easy to manage in a multi-tenant deployment.
The ability for tenant users to independently build dashboards and share them with colleagues—without requiring support from your product team—is essential. Without this, customers become frustrated and your team gets overwhelmed by custom dashboard requests.
The ability for tenant users to customize datasets—by renaming fields, adding new ones, or creating entirely new datasets—enables customers to tailor your application to their specific business needs.
If your platform can't manage your data,
it can't manage your analytics.
Core evaluation areas at a glance
| Capability Area | What to Look For | Why It Matters |
|---|---|---|
| Self-Service | Tenant-level dashboard building and dataset customization | Empowers users, reduces support load |
| Data Management | Built-in data engine, transformation, semantic layer | Ensures performance, scalability, and cost control |
| Deployment | Multi-cloud support, modern deployment tech (e.g., Kubernetes), content migration | Aligns with your infrastructure, simplifies operations |
| Embedding | Web component-based embedding, full-featured backend APIs | Delivers seamless UX and operational automation |
Pitfalls and strategic considerations
Keep these in mind as you narrow your evaluation.
Common pitfalls to avoid
- Assuming multi-tenancy works the same across platforms
- Overvaluing visual polish over backend capability
- Relying on semantic layers without a data engine
- Choosing SaaS analytics platforms that conflict with your data privacy model
Strategic considerations
- Flexibility: Can it evolve with your product and market?
- Differentiation: Does it give your product a competitive edge?
- Scalability: Will it support growth without re-architecture?
- Control: Do you retain ownership of data and deployment?
12 questions to ask before choosing a platform
Use these questions during vendor evaluations to cut through marketing and get to what matters.
- 01
Self-service dashboard building
Can tenant users build and share dashboards independently?
- 02
Dataset customization
Can users customize datasets with field renaming, calculated fields, and new dataset creation?
- 03
Secure multi-tenancy
Does the platform support secure, scalable multi-tenancy with co-mingled and segregated data models?
- 04
Built-in data engine
Is there a built-in data engine and transformation layer—not just a semantic layer?
- 05
Future flexibility
Can the platform evolve with your product and market as requirements change?
- 06
Modern deployment
Does it support modern deployment models like Kubernetes and serverless?
- 07
Multi-cloud support
Can you deploy in your cloud(s) of choice?
- 08
Environment management
Are content migration and environment management built in?
- 09
Seamless embedding
Does it offer web components (not just iframes) with APIs that expose all key functionality?
- 10
Product differentiation
Will it differentiate your product in the eyes of your customers?
- 11
Advisory services
Does the vendor offer advisory services to help shape your analytics or monetization strategy?
- 12
SaaS track record
What experience does the vendor have working with SaaS companies in production environments?
What they say when we're
not in the room.
The flexibility and ease of use with Qrvey's platform allows us to satisfy any use case that our customers ask for. They are blown away all the time when we say "Sure, we can support this request. We will have this ready for you later today." That directly helps our customers run more efficiently and deliver a better experience — so nothing falls through the cracks.
Read the EvenFlow case study →
Qrvey unlocks next-level tenant flexibility and dashboard management, helping us deliver a fully personalized analytics experience for every customer.
Qrvey 9 brings to the table some incredible enhancements — the biggest release we've seen yet. We're particularly excited about the revamped dashboard creation experience, native dashboard sharing options, dataset creation and subscription improvements. On top of that the snappier/cleaner UI has us absolutely pumped to bring this to our customers.
Read the JobNimbus case study →
Qrvey allowed Impexium to go to market quickly and get analytics into the hands of our customers.
Read the Impexium case study →
Ready to evaluate with confidence?
See how Qrvey's embedded analytics platform is purpose-built for multi-tenant SaaS companies.