Key Features to Consider When Evaluating Embedded Analytics Vendors

Adding embedded analytics to your SaaS product is a big step. It can be overwhelming, but with the right approach, you can make a choice that fits your needs perfectly.

This guide will help you understand the critical features to look for when evaluating software vendors.

Why Buy an Embedded Analytics Solution?

Feature requests will destroy product management teams if they can’t deliver. When it comes to analytics feature requests, users will figure out how to build their reports with or without you.

Want a super-sticky product?

Embedded analytics gives users the tools for self-service analytics. This means users can build their custom reports within your SaaS application. Keep them in your application and they’ll never leave. This is one of the best ways to increase customer retention.

Still unsure about buying vs building?

This is typically the first hurdle product teams must face. It’s easy to think you can build a self-service analytics feature, but most team underestimate the effort.

To help we put together a build vs buy center with an ROI calculator and guide to help you in your journey.

READ: Build vs Buy (Guide + ROI Calculator)

So what features are important?

Embedded analytics is more than just charts. Multi-tenancy adds a complex dimension that requires planning. Internal analytics skips this step so it should be on your radar from the beginning.

Let’s look at the key feature areas.

Data Integration

Data Location and Types
The first thing you should consider is where your data lives and what types you have. Your analytics solution needs to connect seamlessly to all data sources, whether on-premise, in the cloud, or on third-party systems. Be clear about whether your data is structured, unstructured, SQL, or NoSQL, and ensure your vendor can handle it all.

Data Volume and Security
Understand how much data you have and how much you’re generating monthly. Some vendors may struggle with large data volumes, which could impact performance.

Additionally, security is paramount—especially if you’re dealing with sensitive data like PII or HIPAA-compliant information. Make sure your solution architecture aligns with your company’s data security policies.

Analytics Features

Customization and Visualization
Your customers will want to build their own reports and dashboards. Make sure the embedded analytics platform offers robust chart and dashboard builders. Also, consider if the platform allows mixing data from different sources on one screen and supports advanced visualizations like trend lines or goal markers.

TRY: Check out our interactive Demo Center

Automation
Workflow automation is a must-have feature for embedded analytics platforms. Ensure that the vendor offers true automation capabilities, not just simple email alerts.

AI/ML Capabilities

Technology is changing fast and the future of AI is taking shape now. If AI/ML is a priority, ask about how these features are integrated and what’s possible within the platform.

Developer Features

Ease of Embedding
Embedding analytics should be straightforward. Look for platforms that offer pre-built widgets, written in JavaScript for easy integration and avoid iframes for security reasons.

White Label Analytics

The ability to white-label the solution is also crucial for maintaining your brand’s consistency. When integrating a third-party product, users should never know. So don’t rush through the UI customization portion of the software evaluation.

API and Multi-Tenancy Support
A strong API suite is essential for creating custom experiences. If you’re running a multi-tenant SaaS application, check for support in handling user/tenant-based security models and ensure the vendor offers robust row-level security.

Deployment and Architecture

Deployment Models
Decide whether you need a cloud-based or an on-premise solution. This decision has significant security and scalability implications.

If your solution needs to be deployed within your cloud environment, ensure your vendor can meet your requirements without compromising on performance. Preferably, the solution you choose deploys within containers so you’re not wasting money on server rental.s

Scalability and Performance
Scalability should be a top concern. If your application grows, your analytics should grow with it. Evaluate how well the vendor’s solution can scale. There’s a big difference between scaling containers and scaling server clusters.

Company Fit

Vendor Experience and Support
Your analytics provider should not only meet your technical needs but also be a good fit for your company. Check if the vendor has experience working with SaaS providers and aligns with your company’s values.

Consider their customer support policies and how transparent they are with their product roadmap.

Pricing and Licensing
Understanding the embedded analytics pricing model is crucial. Ask detailed questions about licensing fees, including whether they’re based on users, data volume, or a combination of factors. Ensure there are no hidden costs that could surprise you later.

Next Steps

Choosing the right embedded analytics for SaaS solution is about more than just features. It’s about finding a partner that understands your needs, supports your growth, and fits seamlessly into your existing ecosystem. By focusing on these key areas, you can make a confident, informed decision that benefits both your product and your customers.

Check out our guides to the best vendors:

• Best Embedded Analytics Tools
• Best Embedded BI Vendors

Qrvey is here to help. Have questions? Want a personal demo?

Let’s chat and we’ll help steer you in the best direction.