The Power of Embedded Analytics for Product Companies

Embedded Analytics is the practice of combining the use of data analysis and visualization capabilities directly into your software application or platform. So instead of users navigating to a separate analytics tool, embedded, as the name points out, brings insights and visualizations into the software you’re using to help you work smarter. 

In simple words, it’s like having a built-in analytics tool in your application, giving you relevant data insights into your business, like an all-in-one application. 

Embedding analytics helps organizations deliver a data-driven experience by integrating reports, dashboards, models, data visualizations, and other forms of business intelligence into one interface. 

This enhanced interface gives superpowers to businesses and individuals. They can quickly ask questions about their data and discover meaningful insights without leaving the interface they are already so used to. Everyone loves deeper insights, helping them make faster and more data-driven decisions!

What is the Value of Embedded Analytics?

Embedded analytics make everything simpler. Rather than requiring application users to exit the familiar interface of their daily tools, the integration of Business Intelligence (BI) directly within operational or custom applications enhances user adoption. This transformative approach turns these applications into true game changers. 

One of the significant advantages of embedded analytics is the elimination of the need for writing code to create dashboards. Unlike many product companies that invest substantial effort in developing both front-end and back-end code for dashboards, utilizing BI tools offers a no-code solution. This represents a substantial advantage. Embedded analytics strategically place data and insights precisely where users need them the most: seamlessly integrated into their daily workflow.

According to a study by Sisense
“If a product’s asking price is $20,000, embedded analytics can increase premium pricing by 25%, in an example of 1,000 customers, which translates to an additional $5 million in revenue.”

Examples of how companies are using embedded analytics

You might be wondering,” All of this sounds great, but where and how do I use embedded analytics exactly?”

The application of embedded analytics is widespread, and it simmers down to three places:

  • Internal Data Transformation 
  • SaaS Empowered Embedding
  • Product Websites 

Internal Tools

Embedded analytics can greatly serve your internal operations— such as your CRM, operations, HR, IT, Finance, etc. Teams employing these will gain a more insightful approach to interacting with data from your business. This distributes data insights across the organization and can be a great step toward a data-driven culture fostering data-based decision-making. 

SaaS Platforms

Cloud-based SaaS platforms provide an extensive array of tools and services tailored to meet their customers' business needs. Elevating this offering, embedding analytics emerges as a potent approach to further empower B2B customers, enhancing the platform's value proposition and solidifying its role as a comprehensive solution. 

This is precisely where the versatility of BI tools shines. Instead of resorting to intricate coding, the creation of dashboards and reports becomes a streamlined process via BI tools. These dashboards can then be seamlessly integrated into the product, seamlessly enhancing the user experience.

Product Websites

Product teams who deal with consumer-facing products or software can leverage embedded analytics into their software. With this, a user experience is created for the teams with drill-down analytics and data explorations. 

Retail companies trying to run an inventory can find this very useful. They can keep up with growing customer demand and dive into each product to see how it performs. Armed with this data, retailers can enhance their performance by planning everything from supply chain optimization to marketing. 

Did you Know? 
A recent survey by ThoughtSpot found that 55% of global respondents reported that they already offer embedded analytics in their products. The same survey found that 72% of respondents believe that embedded analytics will be essential for businesses in the future.

What You Should Know About Embedded Analytics for Enhanced Product Performance

In product companies, analytics is no longer an optional addition but a component essential for success. Product companies increasingly depend on data as the cornerstone for informed decision-making, operational optimization, and enriched customer experience. By integrating analytics into their offerings, they empower their users to access data-driven insights within their applications' confines. 

Within the dynamic landscape of product companies, the role of analytics has evolved from a mere optional addition to an essential component of triumph. Progressive product companies recognize that the insights derived from data analysis serve as the cornerstone for informed decision-making, operational optimization, and enriched customer experiences. By intricately integrating analytics into the very core of their offerings, these enterprises empower users to effortlessly access a treasure trove of data-driven insights, all within the confines of their applications.

Streamlining Analytics Integration

Embedded analytics offers a seamless way to integrate analytics capabilities by utilizing Business Intelligence (BI) tools. These tools, whether licensed or open source, allow the creation of interactive dashboards and reports that can be seamlessly embedded within the product interface. This integration simplifies the process and eliminates the need for extensive coding to develop analytics features from scratch.

Centralizing Data and Insights

In many product companies, the same Operational Transactional Processing (OLTP) database serves both the product's core functions and the analytics features. This arrangement can lead to performance bottlenecks and hinder the scalability of the analytics infrastructure. To address this, embedded analytics suggests a separation between the Online Analytical Processing (OLAP) database and the OLTP database.

By establishing a dedicated OLAP database, companies can ensure smooth and efficient data retrieval for analytics reports and dashboards. This enhances the user experience by providing swift access to insights and relieves the operational database from the added load of analytical queries.

Did You Know: Data Pilots’ Embedded Analytics services offer a complete 360-degree view of your operations, helping you make informed decisions with real-time insights and ease.

Efficiency in Development and Adaptation

One of the most significant advantages of adopting embedded analytics lies in the expedited development process. Unlike traditional coding approaches, where each modification or addition to analytics features requires substantial coding efforts, embedded analytics enables swift updates. Adding new Key Performance Indicators (KPIs) or modifying existing dashboards and reports can be accomplished with minimal coding or even none at all, depending on the complexity.

This efficiency in development has a cascading effect on the product's agility. It empowers product teams to rapidly respond to user demands, evolving business requirements, and emerging market trends. Consequently, the product can maintain a competitive edge by staying ahead of the curve in delivering insightful analytics to users.

Cost-Effectiveness and Versatility

While licensed BI tools can introduce costs to the company's budget, open-source alternatives like Metabase provide cost-effective options for implementing embedded analytics. This affordability aligns well with the cost-conscious strategies of many product companies, allowing them to allocate resources more strategically.

According to a study by Sisense
“If producing manual ad hoc reports takes two weeks (80 hours)/month and costs $100 an hour, analytics could reduce the time to eight hours/month, saving 72 hours of labor time/month or $86,400 a year.”
Moreover, the versatility of embedded analytics extends to its compatibility with tools like These tools facilitate the construction of robust analytics stacks, enabling companies to leverage advanced analytics capabilities without the complexities associated with custom coding.


Incorporating embedded analytics as a winning strategy within product companies can significantly elevate their performance and user experience. Data pilot can help you in this intricate process of dashboard development. Companies can efficiently integrate analytics features using BI tools. This streamlined approach, coupled with the separation of OLAP and OLTP databases, ensures optimal performance and scalability.


Why use embedded analytics?

Embedded analytics seamlessly integrates data analysis and visualization within software applications, enhancing decision-making and user experience without the need to navigate to external tools.

How does embedded analytics address scalability for product analytics?

Embedded analytics provides a scalable infrastructure to cater to growing analytics demands, offering an effective solution for serving insights to product users.

Why should product companies consider embedded analytics over code-based dashboards?

Embedded analytics offers a strategic advantage by seamlessly integrating data analysis tools within products, enhancing user experience and decision-making without the complexities of coding.

What is an example of embedded analytics?

An example of embedded analytics is CRM software that displays visualizations of sales trends and customer behavior within its interface, helping sales teams make informed decisions.

What is the main advantage of an embedded system?

The main advantage of embedded systems is their dedicated functionality within devices or systems, optimizing performance, efficiency, and reliability for specific tasks or applications.

What's the significance of having a separate OLAP Database (DWH)?

Having a dedicated OLAP Database ensures that dashboards and reports don't burden the operational data store (OLTP), optimizing performance and user experience.

Are there tools available to simplify the creation of analytics stacks?

Tools like are designed to facilitate the development of analytics stacks, streamlining the process for product companies.

Written by: Ali Mojiz & Shaafay Zia

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