Embedded Analytics

What is Embedded Analytics?

What is Embedded Analytics?

Embedded analytics is a subset of business intelligence (BI) which is a group of technologies, methodologies, systems and people that seek to analyze all aspects of a business’s operations and is tightly integrated into a user’s workflow. With traditional BI practices, there are gaps in what can be analyzed, such as in-application usage. Embedded analytics is built directly into the application itself to deliver usage statistics and valuable reports. But these robust software systems can do so much more than just report on in-application user behavior.

Summary of Benefits

  • Display and benchmark performance metrics
  • Ask your own questions about data and explore solutions
  • Ensure interactive reporting on mobile devices
  • Increase productivity

Choosing from solutions that offer embedded analytics isn’t like choosing furniture. It’s more like choosing a friend who’ll join you on a journey over the course of the next few years. A journey that, in a fast-changing world, will be filled with unknowns and challenges. Luckily, you’re not flying blind. This guide will help you understand the basics of embedded analytics, what it does and how to choose the right solution for your business. With so many different types of analytics out there, it can often be confusing to differentiate between the different flavors of data-deducing applications and methodologies. So let’s start with some basics.Embedded analytics offers neatly packaged and valuable insights that can be used for a variety of purposes, which we’ll cover later in the article. So where does it fit in?

Embedded Analytics Definition

Benefits In Detail

Embedded analytics sounds pretty cool, right? But what’s in it for the user? Why might someone choose them over a standalone business intelligence or business analytics system? Here are a few of the most important benefits:

Display and benchmark performance metrics

Embedded analytics is apt at reporting usage behavior by themselves, but becomes even more powerful when the results can be compared against user-defined metrics, often called key performance indicators (or just KPIs). This is a process known as benchmarking, and it’s essential in helping users to measure their progress.

Embedded analytics will take all these user-defined metrics and compare them against user-defined benchmarks, making it easier for managers and analysts to see that. For example, entering patient information is taking significant time for a staff member. With this kind of data in hand, a manager can implement a new solution to hopefully cut down on entry time. Then, in order to gauge performance over a set period, you can use embedded analytics to generate daily reports on how much time you shaved off by implementing your solution.

Embedded analytics gives users the power to diagnose their own issues and then interrogate their data.


Because it is designed to be embedded in another software platform, embedded analytics has extensive integration capabilities. Integration opens up data processing speed, pulls data directly from the source system and streamlines interfaces.

Ask your own questions about data and explore solutions

The power of embedded analytics is that it integrates into a user’s workflow and collects data on in-application usage and performance. If your company has a sales department, you might be familiar with Salesforce, a popular customer relationship management platform. Embedded analytics features a user-accessible, built-in analytics suite that empowers even the least tech-savvy of your users to explore their own data and look into solutions.

Ensure interactive reporting on mobile devices

Embedded analytics is widespread across the spectrum of devices and technologies, including mobile, which is a mission-critical sector of the business intelligence market. Professionals across the business spectrum are making the shift towards mobile technology. For example, field service workers have long since been champions of the “mobile workforce” philosophy. Essentially, this means equipping a worker with a cellphone, an app that can handle essential back-office tasks and then sending them on their way. Embedded analytics comes in handy when you’re monitoring users’:

  • Application usage and interaction
  • Response times
  • Locational data
  • Application installs

And that’s just the tip of the iceberg. With a mobile-enabled workforce, embedded analytics allows managers to keep tabs on their users’ behavior, and again, compare those accrued metrics against key performance indicators to assess performance. At the same time, users have the ability to track their own progress and ensure that their workflows stay intact and that more available data can be collected.

Increase productivity

So far, we’ve talked a lot about user workflows. But that really is, at its core, one of the benefits of building analytics into products or building a product that can “embed itself” in other applications. You won’t have to drop out of your current application to log any analytical data. Even application-specific data can be logged by a solution, such as sales figures or payroll information. All of this saves your workers time and can save you money. It’s estimated that employees lose up to 10% of their time on task switching, and that includes switching between applications. Embedded analytics helps to alleviate this problem by unifying your analytics solution and your work-focused application.

For example, let’s say you’re using a CRM and want to generate a sales report for the end of the month. Without embedded analytics, you’d have to open up a new application, export data from the CRM and then generate the report that way. With embedded analytics, you can generate a live, robust report right from your CRM application with just a few clicks.


While every software comes with a very different price tag, embedded analytics is often a more cost-effective solution than a more robust standalone BI platform. For SMBs or cost-conscious users that have already invested in other types of business software, this may be the perfect solution.


So now we know what embedded analytics is, but how does it deliver on these promises? Embedded analytics can be broken down into several groupings of features. Each solution varies in its offerings, but the core features are more or less universal. Here they are in no particular order:


This refers to the features that make the analytics embeddable. First, the system needs to offer white-labeling. This makes the application customizable so users can match the look and feel of the host application. Next, there’s multi-tenancy support. Every user needs a unique version of the software, and this feature allows that. Version control helps development teams manage source-code changes over time. These features allow users to embed unique versions of the same software into a range of applications, customize those systems, and store previous versions to protect against crashes or hacks.

Dundas BI Dashboard

Dundas BI embeds into CRMs and integrates with call center data to provide a seamless experience for the user

Data Management and Visualization

BI tools are designed to analyze and visualize data, so data management is a huge aspect of the software. Embedded analytics explores, prepares, maps, diagrams and models data into a range of visualizations like line, bar and pie charts. They can also be presented via interactive dashboards that let users interact with their visualizations. Users can examine these visuals for data trends and patterns in order to draw insights from them. Embedded analytics supports online analytical processing (OLAP) which allows multi-dimensional data analysis.

Exago Data Visualizations Dashboard

Exago presents complex data sets in simplified visualizations


Reporting refers to summaries of data points and trends. Users can create ad-hoc reports that deliver information on a specific key performance indicator (KPI) or metric, scheduled reports, recurring reports, and more. These reports can then be exported in a range of standard formats for easy sharing.

Sisense Reporting Capabilities

Sisense offers robust reporting capabilities that can be portrayed in intuitive visualizations


Embedded analytics offers a range of analytical capabilities. These include predictive, descriptive, prescriptive, diagnostic, ad-hoc and decentralized analytics. Users can identify benchmarks and monitor business practices, generate business plans based on data predictions and share data throughout the organization.

Microstrategy Data Visualizations

Microstrategy performs advanced analytics on datasets and presents them in a range of intuitive visualizations, allowing users to draw insights

Datasources Integration

This feature allows embedded analytics to integrate data from a range of sources. This includes Excel and the Microsoft Office suite, CSV, XML, and more. It also enables users to connect to big data sources like Hadoop. Embedded analytics can draw data from both relational and NoSQL sources via parametrized database connections, also known as passwords and usernames.

Logi analytics Data Visualizations

Logi analytics can draw data from a range of datasource types and combine them into detailed visualizations

Extensibility, Availability and Scalability

This collection of features refers to the ability of the software to be scaled and stretched. Embedded analytics by nature should be very versatile and adaptable, so extensive scalability features are crucial to the software growing with your business.

Embedded analytics should be vertically and horizontally scalable. Vertical scalability involves a software system’s ability to grow by adding extra resources like CPU or processing power. Horizontal scalability connects other devices or programs into a single unit.

Dynamic solutions can automatically scale resources in order to accommodate different amounts of throughput during the workday. This relates to the system’s availability — more simply, the amount of time a system is up and running.

JReport Extensibility

JReport scales with your business as it grows


How does embedded analytics work?

It works by either being built into a product or embedded externally into the product (this is common for apps that don’t have powerful analytics platforms already built-in). The ladder is a feature known as embeddability, and it essentially means an entirely separate analytics product is integrated with a non-BI program to perform in-application analysis. The BI app then measures a variety of statistics and metrics for the user, and it can generate reports and insights directly within the application.

How do I know I’m ready for embedded analytics?

Embedded analytics can bring significant benefit to any user who is either trying to collect all available data or is dependent on a piece of software that doesn’t have a good analytics suite built-in. So it’s safe to say that there’s a number of indicators that will tell you if you’re ready for embedded analytics. Here’s just a few:

  • You’re trying to track every piece of data you can for analysis
  • You’re dependent on software for most of your work (and this software doesn’t have analytics built-in)
  • You’re trying to diagnose deficiencies in your business
  • You’d like to make data-driven decisions in regards to your application usage

How do I select the right tool?

This is a tough question with a lot of different answers, because fundamentally, all businesses are different, and they have different needs; your business is no exception. It’s important to keep a few standards in mind, however.

Some companies are able to maintain a project with the same set of requirements for years. This isn’t the norm, however. Products and solutions evolve quicker and quicker every day, and your embedded analytics module will have to keep up with this evolution.

Here’s an example: according to an IcCube survey, over the past four years, only one icCube customer has continuously run the same version they initially launched with in a 24/7 production environment without installing any updates. A robust integration like this was only made possible because of the great teams, months of testing and a complete list of detailed requirements obtained beforehand.

While some organizations may have a strong IT team that can handle the technical side of implementation, you should still expect to need assistance during the process. You’ll most likely find yourself working closely with your vendor — not only during the integration phase, but for the next few years. Like trekking in the middle of the mountains when bad weather hits, you’ll appreciate being with somebody you can count on. Choosing a high-quality partner is an important factor to ensure you’ll have a smooth journey.

Some ways to identify a good vendor partner are:

Assess Your Needs

First, assess your needs and wants. Your needs are, obviously, the essential components that you can’t skimp out on. You should find out what applications you’d like embedded analytics to work for, and what exactly you need the tool to do. If it won’t integrate with your most commonly used app? Scrap it. Next comes your wants, which are ideal features that aren’t necessary to the core functioning of your business. Our advice is to be flexible with this. Sound like a lot so far? We’ve got you covered, with our helpful requirements checklist.


Next comes the budget, which will play a major role in determining whether or not you can go with a certain piece of software. The budget should be on par with your requirements, but above your wants, as far as priorities go.

And once you’ve cleared those two essential hurdles, it’s time to start on the monolithic request for purchase (RFP). RFP’s are beasts on their own, involving long hours of commitment and communication. If you’re lost on how to start, we’ve got an analytics-specific guide to creating an RFP right here.

Read Reviews

One of the best ways to get a feel for how a vendor treats its customers is to read testimonials by previous or current customers. There are many places to find reviews on the internet, and we recommend a third-party site rather than the vendor’s own page.

Keep in mind that this isn’t a surefire way to determine the quality of vendors — in one survey pool, 95 percent of people who had a bad experience with a company told someone else about their experience, versus 87 percent of those who had good experiences.

Graph Showing How Often Unhappy Customers Share Their Experiences

Identify User Support Features

Because embedded analytics changes so frequently and needs upkeep and updates, a consistent contact line with the vendor is important to resolve issues and get questions answered. Support offerings go all the way from email ticketing only up to 24/7 live chats and phone support.

Organizations with a robust IT department might not feel a need for more extensive customer support lines. There is also a cost benefit to less support — the more they offer, the more it will likely cost the user. But if customers want speedy resolutions to problems and attentive customer service, the user support is often more than worth the cost.

Explore Community Support

It’s often not wise (or even possible!) to rely solely on the vendors for communication and troubleshooting, so another thing to keep an eye out for is a community support platform. These can exist in many forms — for example, Salesforce has a platform of videos, forums and Q&As called Salesforce Knowledge that helps users answer simple problems and build collective experience.

Difficult times happen even to companies that deliver high-quality products, so choose a partner you can make your journey with; a partner that shares your values and is flexible enough to align with your goals.

Embedded analytics can bring your business all the benefits of business intelligence with the convenience of staying put in your other software systems. Users can generate a range of report types and perform analysis of their data in order to make informed business decisions.

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Embedded analytics articles are written and edited by:

Zachary Totah

Content Manager

As SelectHub’s Content Manager, Zachary Totah leads a team of more than 35 writers and editors in their quest to provide content that helps software buyers find the right system for their company.

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Hunter Lowe

Content Editor and Senior Market Analyst

Hunter Lowe is a Content Editor and Senior Market Analyst at SelectHub. He writes content for Construction, Inventory, Warehouse, and Supply Chain Management.

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Ritinder Kaur

Market Analyst

Ritinder Kaur is a Market Analyst who writes content on Business Intelligence, Big Data Analytics, Business Analytics, Embedded Analytics and Enterprise Reporting.

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Payal Tikait

Market Analyst and Technical Content Writer

Payal is a Market Analyst and Technical Content Writer at SelectHub. She is passionate about curating content for business intelligence, ERP and human resource domain.

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