What Is Embedded Analytics? A Comprehensive Guide

Business intelligence and analytics enables companies to measure and analyze their data to make better, faster business decisions. Embedded analytics seamlessly integrates that data and analytics within an existing application or platform, enabling external users with the same powerful capabilities you might give internal users. This approach allows for real-time data analysis and visualization within the context of the user's workflow or business application, facilitating data-driven decision making without the need to switch between different applications or reporting tools. 

Table of Contents

1. Embedded Analytics Definition
2. Where Is Embedded Analytics Commonly Used?
3. Benefits of Embedded Analytics
4. Examples & Uses for Embedded Analytics
5. Features of Embedded Analytics Tools To Look For
6. Embedded Analytics: Build or Buy?

Embedded Analytics Definition

Embedded analytics is the integration of advanced data analytics capabilities into other applications relevant to your business. Embedded analytics accelerates time to value for data applications by allowing teams to work together to build applications faster with better user experiences—and reduced development costs. Embedded analytics also allows users to access and analyze data within the context of the software application they are already using without having to switch to a separate analytics tool or platform.

How to Use Embedded Analytics

By embedding analytics into the applications your internal teams already use—such as your CRM, operations, health care, or HR solution—your users will gain a more insightful approach to interacting with data from your business. These insights can help to improve business outcomes and drive better decision making.

Product leaders can also take advantage of embedded analytics by incorporating it into their consumer-facing products or software. By creating a user experience that incorporates drill-down analytics and ad-hoc data explorations, teams can make their products more engaging and provide additional value to users.

Cloud-based SaaS platforms have made the process of embedding analytics more accessible than ever before. All of your organization's transformed, organized, and governed data is stored in one centralized location, allowing product teams to tap into their modern data stack and easily embed analytics into both internal and external applications

While software development can be time-consuming, embedded analytics solutions streamline the process of building a user experience with data, saving critical development time and resources.

Where Are Embedded Analytics Commonly Used?

Embedded analytics makes your work easier and more efficient by integrating dashboards and visualizations directly into your internal and external applications. This helps simplify cumbersome workflows and speeds up the process of discovering valuable insights from your data. For customer-facing applications, embedded analytics also provides significant opportunities to monetize your data.

Most commonly, organizations take the reports, visualizations, and dashboards that they build in BI and analytics tools and embed them into:

1. SaaS Applications: SaaS applications are leveraging embedded analytics solutions to quickly deliver high-quality data products that drive customer and partner satisfaction.
   
2. Analytics as a service: Analytics as a service application that uses embedded analytics could offer insights into consumer behavior, such as purchasing patterns or social media activity, which could be used to inform targeted advertising campaigns.
   
3. Internal business applications: Embedding relevant analyses directly into business workflows increases the ease and frequency of data-driven decision making across the organization. 
   
4. Public-facing web pages: Companies may choose to share research they’ve done around particular industries or global events to garner press coverage and brand awareness.
   

For example, Payload is a cloud-based logistics and supply chain management application that delivers logistics tracking and reporting. Payload’s customers benefit from digitally-managed field tickets, increased operational efficiencies, and compliance management.

Payload spent years trying to perfect its application functionality, eventually shifting its strategy to truly differentiate itself from the competition. “To improve retention, generate new business, and ultimately enable customers to get the full value of our application, we needed to build analytics solutions into our product,” recalled Chris Lambert, who was CTO at Payload at that time.

This new strategy also gave Payload the opportunity to monetize vast amounts of data it collects through its application. “This was a major opportunity for us to jump leaps and bounds ahead of the competition,” said Chris. “The cost of not doing this was incredibly high—we had to make it happen. No one else in the industry was providing this type of insight to customers.”

Utilizing Sigma’s embedded analytics, Payload has improved efficiency without adding new team resources typically required to keep up with increased demand. “We built these data products plus more than 30 other standard reports in just a couple months without having to add any additional headcount,” recalls Iain Letourneau, Payload’s BI Lead.

“Adding Sigma dashboards and insights to the Payload application has had a huge impact on the perceived value of our product,” said Chris. “It’s not only helping us retain current customers, it’s enabling us to expand these accounts as well. Sigma’s A&BI solution allowed us to create an entirely new revenue stream and now plays a key role in generating and closing new business.”

5 Benefits of Embedded Analytics

There are a number of advantages to using embedded analytics within your company.

1. Flexible Data Sharing

Embedded analytics gives companies complete flexibility in sharing insights: it’s possible to keep reports and visualizations in-house or share them more widely. The specifics will vary by platform, but in Sigma, flexible embedding works by generating and embedding a unique and secure URL of the dashboard or dashboard visualization teams want to share, then placing that generated URL into an iframe in an application. This secure URL contains fields to define what viewers will see, areas to ensure that the URL is unique, and a signature created by encrypting the URL. In other words, embedded analytics provides a completely secure solution with access restricted to whom it is deemed necessary.

2. Encourage Data-Driven Decision Making

All types of business users, such as marketing, sales, finance, or operations, can utilize embedded analytics to generate real-time insights quickly. This means more insights covering a more comprehensive range of questions. As a result of this abundance, data-driven insights can inform all types of decision making—strategic, tactical, and operational. There’s no longer a limit on what kinds of decisions get data or BI team resources allocated to them.

3. Increase Productivity

When business teams can run their own analyses, they don’t need to wait around for the BI team to deliver dashboards or reports. They can handle their own information needs, making them much more efficient. At the same time, data and BI teams become more productive because they no longer have to spend most of their time running reports—instead, they can focus on work more aligned with their specialized skills.

4. High Adoption Boosts ROI 

The combination of more decisions informed by data—and greater productivity—translates to a better return on a company’s analytics investment. According to a survey by Dresner Advisory Services, embedded analytics tools have, on average, a 59% adoption rate compared to the 27% average adoption rate of traditional BI tools.

5. Monetize Your Data

Many organizations are generating unique, valuable data that customers and partners would happily pay to access. Embedded analytics makes it easy to transform data, reports, and visualizations into a product that generates revenue, or that can be used as a value-add for existing products or services, allowing companies to be more competitive or even raise pricing.

Examples & Uses For Embedded Analytics 

There are a number of ways that embedded analytics can be used. See below for some examples.

Public Web Pages

When companies want to make the public aware of data that continually changes, creating an embedded analytics visualization is the ideal solution. Using a simple HTML embed code, it is easy to share visualizations, dashboards, and reports that automatically update as data changes. 

Internal Web Portals

Insights intended only for specific teams can be securely embedded into internal web portals using row-level security and column-level security. The advantage of web portal pages is that several data reports and visualizations can be grouped together for ease of interpretation or for diving in deeper while looking at context. These pages can also be used to feature important dashboards that teams want their colleagues to be able to easily find and use.

Third-Party Applications

Embedding analytics capabilities directly into third-party applications allows teams to streamline existing workflows without having to exit the software they find familiar. Users can query and visualize data directly in the software they use every day. This capability is especially beneficial for sales and marketing teams. Being able to produce relevant analyses within Salesforce and other applications leads to faster and more informed decision making by eliminating the need to switch between applications to access the data that users need. 

Customer Products

In a recent webinar, Greenwich.HR’s Founder and CEO Cary Sparrow and Director of Product Development Daniela Chita-Perez discussed how they:

• Reduced time-to-value, creating custom dashboards in weeks (vs. months.)
• Enabled clients to drill down and ask complex questions while saving $100k+ in resources.
• Projected 7-digits in revenue from new incremental sales over the first year for WageScape.

Features of Embedded Analytics Tools to Look For

‍To maximize the benefits of embedded analytics, you’ll need specific features in your analytics software. Here’s what to look for in an embedded analytics platform to ensure your people can use it effectively.

Unconstrained Drill Paths

The insights revealed by high-level dashboards almost always trigger additional questions. Why is this pattern showing up? Why is that trend happening? What would happen if we changed this variable? For scalable business intelligence that doesn’t depend on BI teams that are overwhelmed with endless to-do lists, business teams must have the ability to drill down into the live data underlying their dashboards to find answers to questions in a timely manner. 

Intuitive Interface

To be truly data-driven, business users must be able to find answers quickly on their own—and they shouldn’t have to learn SQL or a proprietary coding language to do so. A good embedded analytics platform should have an intuitive and familiar user interface, such as a spreadsheet. 

Direct Connection to Where the Data Lives

For most forms of data analytics, the freshness of data impacts the accuracy of the insights derived from it. Users must have the ability to connect directly with the cloud data warehouse or data platform to access live data and take advantage of the power of the cloud for fast and scalable ad-hoc data exploration. 

SaaS, Not on-Premises

A SaaS-based embedded analytics solution requires minimal deployment and maintenance resources. There’s no need to procure hardware or deal with configuring, maintaining, or backing up software. 

Lightweight Modeling and Configuration

To maximize adoption and ease of use for all stakeholders, dashboards should not require code to build and should provide fast data-modeling capabilities. Additionally, they should be easy to embed in both private and public websites and applications with a single URL. 

Robust Access Permissions

For privacy and security purposes, an embedded analytics platform should offer granular control over what viewers can see and do, including seeing and exploring only their data. Must-have security features include access permissions, user impersonation by admins to validate and test access policies, object security options, and one-time signed URLs. A platform should also provide a variety of row-level and column-level security mechanisms to ensure each user has access to allowed data.

Authentication Options

Another crucial security feature is providing multiple authentication options, including through external applications. Users need to work quickly, and adoption will increase as friction is reduced.

Flexible Dashboard Builder With Pre-Built Content

Dashboards should be customizable and interactive, so viewers quickly get the data they need, but they shouldn’t take a lot of time to build. A good embedded analytics solution will offer pre-built or custom themes and layouts, chart types, data tables, colors, and fonts. Additionally, users should have the option to display either a full dashboard or a single visualization or table within a dashboard. 

Rapid Deployment With Built-in Scalability

An embedded application should allow organizations to roll out embedded analytics in their products and portals in as little as a few hours. Applications change frequently, and new insights and changes to existing insights should be deployed to your customers instantly, increasing customer satisfaction. 

Extensive Monetization Opportunities

Embedded analytics applications should allow you to monetize the power of data gathered by your applications. Organizations should be able to select the embedded dashboards that the customers and partners should see based on the role they play in your application by using account types for fine-grained control over embedding features enabled for each user.

Embedded Analytics: Build or Buy?

It’s important for buyers to understand that integrated BI demands analysis, flexibility, and user-friendliness for non-technical users. The processing of seamless embedding into the host application, lifecycle management, and scaled distribution are other important elements. When it comes to your application, the distinction between creating and purchasing analytics tools may be well summarized as the one between working assiduously and working intelligently.

There are certain crucial embedded BI use cases you need to be aware of, including self-service analytics, democratizing governed data, and boosting user adoption, regardless of whether the debate between building vs. buying analytics for your embedded project will come up now or in the future. Businesses that encourage user sharing of data tend to prosper because analytics innovation is almost always a direct outcome of this democratization. Here, we outline the build vs. buy comparisons:

Advantages of Building Your Own Embedded Analytics Solution 

Building solutions are most useful in businesses with specialized, non-time-sensitive requirements. Building your own analytics platform allows organizations to have specialized resources that provide them with complete control over their data without intervention from outside parties. Here are some other benefits of building embedded analytics in-house:

• Customization: By creating your own embedded analytics system, you can customize it to fit your unique business requirements. Because you can tailor the analytics features and functions to your precise needs, you can be sure that your solution gives your users the information they need to make wise decisions.

• Integration: You can effortlessly combine analytics with other apps and organizational processes by developing it internally. A more simplified and effective analytics experience is achieved by utilizing current data sources and integrating analytics into your operations.

• Control: You have all control over the development process when you create your analytics solution in-house, including the option to oversee upgrades and improvements. This degree of control may be necessary to guarantee data security and privacy, as well as to satisfy legal compliance obligations. 

Advantages of Buying an Embedded Analytics Solution

Buying an embedded analytics solution entails contracting out the creation and upkeep of a data visualization platform to other businesses, and may be a good option for businesses with limited internal resources. These businesses may overcome their resource constraints by purchasing and integrating an analytics tool, which offers a high-performance and scalable solution. To discover the best fit for their business goals, firms must take into account several aspects before selecting an integrated BI product. Here are some other benefits of buying pre-built embedded analytics solutions:

• Time-to-market: The shorter time-to-market is one of the biggest advantages of purchasing pre-built embedded analytics systems. Without the need for an intensive development effort, you may instantly start using a pre-built solution. This is especially helpful if you have short deadlines or must quickly provide your users with information. 

• Cost-effective: Compared to creating one from scratch, purchasing an embedded analytics system that has already been established is more affordable. You can save money by avoiding the costs of finding and training expert personnel as well as ongoing maintenance and solution updates. 

• Expertise: Pre-built embedded analytics solutions are created by specialists in the industry; you can benefit from their knowledge without having to develop it internally. If you don't have the particular expertise and abilities needed to create an analytics solution on your own, this can be very helpful. 

• User-friendly: For non-technical users to access and visualize data, embedded analytics tools offer a straightforward and user-friendly interface. They provide unique action-based dashboards for tracking and viewing data to boost data engagement for more insightful analysis.

• Scalability: In order to stay up with industry standards, embedded analytics tool developers continuously update their products. This enables your analytics tool to expand in accordance with your shifting business requirements. Additional features are handled by the tool's developers without requiring much work from your teams.

• White labeling: The ability of an embedded BI solution to seamlessly integrate with your program and white label the embedded analytics is one of its most beautiful advantages. It means that you are not controlling a separate tool; rather, it is integrated into your product like an internal solution to provide seamless analytics integration.
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• Dedicated support team: Embedded analytics applications typically provide a dedicated support team to assist throughout the implementation process as well as usage of the product. The support teams are experts at the product and can help resolve any technical issues, as well as provide best practices and troubleshooting guidance. Having a dedicated support team ensures that you have experts available to guide you through the challenges and minimize any operational downtime.
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Experience the Benefits of Embedded Analytics

Without a good embedded analytics tool, collaboration is certainly possible, but it’s limited. Organizations need embedded analytics to ensure adoption so they can benefit from the knowledge and perspectives of people in a variety of roles, as well as generate insights to inform a wide range of decisions in a timely manner. Additionally, the ability to share dashboards and visualizations and build upon one another’s work is foundational to collaboration. 

Request a demo of Sigma’s embedded analytics tool to experience the benefits for yourself.