The Ultimate Guide to Embedded Analytics Requirements for 2025

Data-driven companies have a hidden advantage!

They’ve consistently outperformed their counterparts, reporting significantly higher metrics across operational efficiency (81% vs. 58%), revenue growth (77% vs. 61%), and employee satisfaction (68% vs. 39%). How is this possible?

This advantage stems from a simple fact: access to actionable insights empowers smarter, faster decision-making.

Leaders across industries are recognizing this and moving fast to prioritize data democratization—ensuring data is accessible to everyone—as a foundation of their SaaS development. According to a recent survey, 91% of business leaders agree that democratizing access to data and analytics is crucial to their software’s success.

Embedded analytics tools are pivotal in achieving this goal, seamlessly integrating data insights into everyday workflows. Whether you’re building internal tools or customer-facing products, embedded business intelligence (BI) brings the power of data for all users.

In this detailed guide, we’ll cover the embedded analytics requirements for selecting an embedded analytics tool, its transformative benefits for product analytics, and the available implementation methods.

Introduction to Embedded Analytics

Embedded analytics delivers real-time data insights directly within the applications your teams or customers use every day. By integrating analytics into existing workflows, users can make data-driven decisions faster—without relying on separate tools or external teams—saving time and driving productivity. Traditionally, companies have tackled analytics through two main approaches:

• Centralized Teams: Data-savvy users work with specialized tools like Tableau, Excel, or Jupyter Notebook. While effective, this approach often burdens data teams with a flood of requests.
• Decentralized Efforts: Non-technical users may outsource analytics, creating bottlenecks and inefficiencies.

Embedded analytics solves these pain points by providing insights directly within your application, allowing sales teams to track performance metrics in their CRM and operations teams to monitor workflows through embedded dashboards. This removes the hassle of switching apps or needing specialized training, letting users focus on decisions—not data gathering.

How Embedded Analytics Works

Embedded analytics integrates insights directly into your application’s workflows, giving users real-time data exactly where they need it. When users interact with embedded reports or dashboards, the platform retrieves data from connected sources, processes it into actionable insights, and visualizes it seamlessly—all without interrupting their workflow.  Behind the scenes, this process includes:

• Data Retrieval: Pulling data from connected sources like databases or APIs.
• Processing: Transforming raw data into actionable insights through analytics engines.
• Visualization: Presenting data through intuitive charts, dashboards, or reports.

This seamless integration ensures users get real-time insights in the context of their tasks, streamlining decision-making and improving the overall experience.

Core Requirements for Embedded Analytics in 2025

Organizations and ISVs looking to embed analytics into their software products must prioritize certain key requirements when comparing embedded analytics tools

Real-Time Data Access

 Users need real-time insights to make proactive decisions. Embedded analytics delivers up-to-date data, helping users monitor performance and respond quickly to market changes. This reduces delays, breaks down data silos, and empowers swift action to minimize risks and seize opportunities.

Self-Service Customization

Both technical and non-technical users should be able to tailor dashboards and reports effortlessly. Look for platforms with drag-and-drop interfaces for easy modifications, while also supporting advanced customizations for technical teams. This dual focus ensures all users can derive value, regardless of their expertise.

True Embedded SDK

 An embedded analytics solution should blend seamlessly with your product, feeling like a natural part of it rather than an add-on. Solutions like Reveal achieve this with a fully branded, SDK-first approach, enabling smooth integration into your applications. This methodology provides the flexibility to create highly customizable experiences that match your product’s vision and deliver direct value to your users.

Scalability in Price & Performance

Scalability shouldn’t mean hidden costs! Choose a platform with predictable, fixed pricing to plan for growth without worrying about unexpected charges as your usage increases or paying per user. Reveal’s transparent pricing lets you focus on delivering value to your users while keeping costs predictable.

As your business grows, so will your data needs. Ensure your chosen platform can handle increased workloads without compromising performance, delivering real-time analytics integration and maintaining reliability even as data volumes expand. The architecture should be designed to scale seamlessly, ensuring your users experience consistent performance regardless of operational demands.

Security and Compliance

With 29% of cybersecurity breaches involving third-party vendors, security must be a top priority.

Key features to look for include:

• Compliance with GDPR, CCPA, and SOC2 regulations.
• Data encryption in transit and at rest.
• Role-based access controls and robust authentication methods.
• A comprehensive post-breach response plan.

Per IBM, each data breach costs about $4.88 million, underscoring the importance of prioritizing security and compliance as an integral requirement for choosing an embedded analytics platform.

Support and Training

Adoption hinges on ease of use and ongoing support. Choosing the right embedded analytics platform means prioritizing a solution that guides you every step of the way:

• Expert-Led Onboarding: Onboarding teams that ensure a seamless implementation process, working closely with your teams to align capabilities with your specific needs. From setting up integrations to configuring dashboards, you need help you get up and running quickly.
• Comprehensive Training Resources: Select a vendor that provides an extensive library of documentation, tutorials, and videos designed to empower users at all technical levels.
• Responsive Technical Support: Ensure there is a dedicated support  team that is always ready to assist, addressing technical challenges and answering user queries promptly. With embedded analytics, you’re not just adopting a product—you’re gaining a partner committed to your success.
• Ongoing Assistance and Updates: The embedded analytics vendor should stay ahead with regular updates, new features, and proactive insights to maximize the platform’s value.

Expansive Analytics Capabilities

Future-proof your investment by selecting a platform with advanced features like AI-powered insights, machine learning, predictive analytics, and real-time monitoring. Even if not immediately needed, these capabilities will support your evolving requirements.

What Are the Methods of Implementation of Embedded Analytics: iFrames vs. SDKs

When embedding analytics into your application, there are two primary approaches to consider:

1. iFrames:  
   This common approach involves embedding reports or dashboards with minimal development effort, making it suitable for teams with limited resources or tight deadlines. While convenient, this method has significant drawbacks, such as limited customization that can make analytics feel disconnected from your product. It also often lacks advanced features like dynamic filtering or real-time updates and may face performance challenges as data volumes grow.
2. SDKs and APIs: SDKs (software development kits) and APIs (application programming interfaces) offer a more robust and flexible approach to embedding analytics. By integrating analytics at the code level, SDKs allow for seamless customization and branding, ensuring the analytics feel like a natural extension of your application. With SDKs, developers can create deeply personalized user experiences, enabling features like contextual filtering, dynamic visualizations, and interaction-driven updates. APIs complement this by providing connectivity to various data sources, making it easier to pull and transform data in real-time.

Why SDKs and APIs Are the Superior Choice

While iFrames might suit basic use cases, SDKs and APIs are the gold standard for software companies seeking advanced functionality, seamless integration, and full control over the user experience. SDKs allow for tighter integration with your application’s workflows and UI, enabling you to maintain their product’s unique branding and functionality without compromise. This approach also provides more significant opportunities for innovation, allowing businesses to adapt their analytics capabilities as their needs evolve.

Reveal: Built with an SDK-First Approach

Reveal is a leading SDK-based embedded analytics platform, offering unmatched flexibility and seamless integration. With Reveal, you can:

• Deliver a fully branded, white-labeled analytics experience that aligns with your product’s identity.
• Leverage robust APIs to connect to any data source, enabling real-time insights across multiple systems.
• Integrate advanced features, like filtering, drill-down capabilities, and interactive dashboards, directly into your application.
• Provide a smooth and consistent user experience, ensuring analytics feel like an integral part of your product rather than an add-on.

Summary: By choosing Reveal, you’re opting for an SDK-first solution that meets your users’ needs today while ensuring effortless scalability for the future.

For an in-depth overview of these methods, please read our “Embedded Analytics SDK vs. iframes: Which is the Better Integration Option?” guide.

How Embedded Analytics Transforms Product Analytics

Embedding analytics into product analytics enhances your product in several ways, including the following methods:

1. Enhanced Decision-Making: Embedded analytics puts actionable insights directly in users’ hands, enabling faster, more reliable decisions without leaving their workflow.
2. Empowered Users: By democratizing data, embedded analytics empowers all team members, fostering a data-driven culture where insights fuel innovation.
3. Real-Time Monitoring: From spotting trends to addressing issues before they escalate, real-time analytics unlocks agile decision-making and operational efficiency.
4. Improved Productivity: Eliminating data silos and reducing reliance on external tools streamlines workflows, saving time and boosting team performance.
5. Increased ROI: Embedded analytics accelerates product development and enhances user satisfaction, leading to higher engagement, retention, and revenue growth.
   

Conclusion: The Future of Embedded Analytics in 2025

In 2025, the right embedded analytics platform will unlock your data’s full potential. Reveal’s embedding-first approach ticks all the boxes, offering real-time insights, seamless integration, advanced customization, and robust security. Discover how Reveal can transform your products and empower your users.
Book your personal demo today to find out how Reveal can help!