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A Quick and Easy Guide to Embedded Analytics

It’s been said that in business, it’s not what you know, but who you know. For those brands that rely on embedded analytics to give them a competitive advantage, though, what you know is almost more important than anything else.

Although business intelligence has been around for a long time – and is a staple of most companies’ day-to-day activities – embedded analytics are definitely a step up. Not only can you get a holistic understanding of your business’ overall health, you’ll also have vital information to make important decisions right at your fingertips.

Learn how Improvado can help you make better decisions on marketing campaigns


What is embedded analytics?

While it may sound like technical mumbo-jumbo, the name actually reveals exactly what it is: “analytics” that are “embedded” into your software. Instead of having to flip between applications that have different data sets, embedded analytics allow you to see information that is relevant to you inside the software’s dashboard.

Embedded analytics are different from regular business intelligence systems that monitor and aggregate key metrics for your company. With BI, you get an interpretation of data from several different sources, collected into a single report. Embedded analytics lets your employees see how their department directly interacts with others inside the company.

The real advantage is empowering those at every stage of your business requirement to make the best decisions possible. Instead of reporting back to management the status of a product or service, embedded analytics lets the person see how their work corresponds with others in real time. 

If you’re a salesperson, think of embedded analytics as the dashboard to your sales software. You can customize your homepage to include data from the departments that are most important to you – such as leads closed and conversion rate – then use that data to improve your performance. That info is relevant to you and it’s updated constantly.

What results from embedded analytics are employees that make quicker and better decisions in their everyday work, without having to wait for a data analyst to inform them of the next step.

Embedded analytics models diagram
4 models in embedded analytics

The benefits of embedded analytics

More information isn’t always a good thing, but the beauty of embedded analytics is the fact that you can customize the flow of data to what suits you the most. When used as intended, embedded analytics provides a host of benefits to your team.


It’s not enough to have reports. They need to be accessed quickly and in context with metrics from different applications. But since the user can customize these reports, they only see what they need instead of having to wade through a bunch of numbers that are irrelevant to them.


More efficient reporting usually means quicker data analysis. By viewing these integrated reports, employees are able to make objective decisions rather than simply trusting their intuition. By incorporating Istio or a service mesh into the infrastructure, companies can not only achieve more efficient reporting but also enhance control of their micro services architecture.

Data visualization

Different applications display data in different ways, and it can be difficult to see how these numbers work in concert with each other. When that information is displayed on the same graph, you’ll be able to interpret it much clearer. 

Competitive differentiation

Companies that have the most up-to-date information on industry trends and metrics have a huge advantage on their competition. A correct interpretation of data not only tells you what is happening, but why, so you can anticipate moves quicker than others.

User adoption

In the SaaS world, an application’s ease-of-use can be a difference-maker between adoption and abandonment. Embedded analytics creates a user-friendly interface that gives adoptees everything they need to know on a single screen. Better yet, the longer the customer uses the software, the more information is gleaned about the user’s preferences, making it even more difficult for the person to switch apps.

Efficiency and productivity

When users don’t have to switch between screens to get the information they need, their work is more seamless. Productivity improves and time wasted begins to plummet.

How can you get started with embedded analytics?

Despite the wealth of information available through embedded analytics, getting started can be intimidating. The more users you have involved with your software – especially if it’s going to be used by your customers – the more daunting it can be.

Fortunately, there are a few steps you can take to make the transition as seamless as possible.

Choosing the right tool

Some businesses will choose to build their own embedded data analytics software. If that’s what you want to do, you have to consider a few things, primarily what kind of quality you expect of your finished product in relation to the resources you have at your disposal.

A developer will not only have to build the software, but maintain it and troubleshoot any issues. Is your staff able to handle that workload?

An in-house embedded analytics solution costs a fortune and requires a lot of time from engineering talents. You'll probably need to hire new developers with proper expertise that can handle the task and fulfill your business objectives. For example, here's a comparison between building a DIY embedded marketing analytics software and purchasing a third-party solution:

Improvado's build vs buy cost comparison
Cost comparison of DIY analytics solutions vs. third-party platforms

It’s a huge resource commitment for many companies to DIY their embedded analytics, which is why most turn to outside software sets to handle this for them. It’s not nearly as expensive (or difficult) as you may think, and the results are usually superior to anything that can be developed in house.

When deciding on an analytics solution, try to find one that can grow with you. You won’t only need the analytics capabilities of today; try to think about the use cases for that software a few years into the future. Make sure it’s customizable for your specific needs.

Also, consider how well this software integrates with all the major analytics platforms like Google Tools. If your business has a website – which nearly all do – you’ll want to have access to Google Analytics data in addition to other data sets.

Google analytics usage statistic
Percentage of websites that use Google Analytics

Key takeaways:

  • Don't rush for DIY software. Consider third-party solutions.
  • Assess your resources wisely.
  • Make sure your embedded analytics solution integrates with other analytics platforms.
  • Think of scalability and tools you'll need in the future when implementing the embedded analytics platform.

Using a modern data and analytics platform

Most analytics platforms offer up the traditional metrics that your user base needs, such as traffic, leads, and conversion rate, among others.

A modern data analytics set uses advanced reporting to help you make decisions, namely in the form of artificial intelligence. Machine learning can take the various sources of data that are incoming to your business and make recommendations based on best practices. It can also help identify gaps for your company to exploit. 

Modern revenue data platforms can turbocharge your marketing and sales teams' performance. For example, Improvado automatically extracts data from 500+ platforms to convert raw information into analysis-ready insights.

Improvado's supported data sources
Some of Improvado’s supported sales and marketing integrations

The platform features data transformation algorithms that automatically clean, deduplicate, and normalize acquired data to make it easily digestible for further analysis.

Then, Improvado loads insights to 15+ data visualization platforms to build a holistic picture of marketing and sales performance. All stakeholders, from regular marketers to C-level executives, can get a grasp of the company's revenue efforts, analyze new trends, and get a sense of the direction the organization is going in.

These kinds of platforms save analysts' time, provide highly granular insights, and uncover new trends that might have been neglected earlier.

Key takeaways:

  • Choose platforms that can automate your analytics workflow.
  • Automated visualization features will help you understand how you move towards your business objectives.
  • Recommendation algorithms facilitate decision-making.
  • Data transformation capabilities ensure that your teams get 100% analysis-ready data within minutes, not weeks.

Considering data security

Just because your business has a ton of information flowing through it doesn’t mean that it’s impervious to hacks. The last thing you want is your competitive advantage hijacked by another entity – or worse, sensitive user data compromised because of a breach in your system.

Modern analytics platforms have to be secure (namely HIPAA, GDPR, CCPA, and SOC 2-compliant), and that means integrations with various authentication models. You’ll also have to consider permission sets within the data itself.

For instance, who do you want to have access to certain types of information, and why? While you want your team to have access to the information that is relevant to them, you also don’t want them to see everything for privacy’s sake.

Maintaining a safe environment can be a challenge when the data comes in through different content types, such as through web connectors and Javascript APIs. Strong analytics software will decode that information as simply as possible to minimize opportunities for intrusion.

Key takeaways:

  • Complying with all data regulations might be overwhelming. Choose a trusted partner that provides SLA on data security.
  • GDPR, CCPA, SOC 2, HIPAA are mandatory regulations depending on your industry and region.
  • Establish a data governance process to manage data accesses and keep track of your data sets.

Challenges to implementing embedded analytics

Despite its many advantages, embedded analytics isn’t a slam dunk. Implementing and utilizing such advanced software requires overcoming some unique challenges.

Having Trouble Keeping Up with the Pace of Change

Depending on what field you’re in, your analytics software may require updates more than others. New metrics and KPIs are always revealing themselves to be more important than previously thought (to be fair, many traditional metrics remain valuable, too).

Embedded analytics market size
Importance of mobile analytics

The ability to integrate advances in your field with advances in your technology is something you’ll have to consider. Is your software “future-proof”? Are you confident you’ll be able to stay with the same software service ten years into the future, or will you have to pivot to another vendor just to stay relevant?

Check the reviews for others in your industry to see how well the company responds to industry developments. If it’s been a while since the company has made a major update, it might be wise to look elsewhere.

Plus, go through the platform’s data dictionary. A data dictionary is a collection of all data and reports delivered by the platform. For example, Improvado's data dictionary has 28,000+ reports and metrics, which can meet the most demanding marketers' needs.

A data dictionary example

Lacking Expertise

Regular analytics have a steep learning curve. Users have to be onboarded, taught how to use the individual software, then learn how to match each one of those together to create the overall intelligence picture.

Since you’re also dealing with multiple software vendors, finding support can be confusing.

Although embedded analytics reduce the overall cost of implementation (since it’s based inside a single service), you’re still at the mercy of that one support team. If the customer support or training isn’t adequate, you have no other recourse available to learn the software.

This makes picking the right vendor paramount to analytics success. Be sure to do as much research as possible to find one that will not only give you the right data, but also has a robust help team.

Not Having the Right Kind of Data

It may be difficult to sell your team on the idea of embedded analytics initially, but once they’re able to see the integration of data into a single, visual format, they usually can’t get enough of it. Users crave data, poking around for hours to see all the different sources that each software vendor provides.

During your trial period, make sure that you analyze each software to make sure they provide the data your team needs. Not every solution can integrate with every data source – or provide the level of security that each source requires. Connect each vendor with your data sources to make sure the visualization is conveniently accessed.

Looking for ways to improve your marketing analytics? Don’t miss out on our 12 dashboard templates suitable for all industries and use cases

Managing Device Lifecycles

You can’t afford to ignore the toll that advanced software will take on your devices. It’s important to have a process in place to constantly manage the health of your devices, as well as make sure all systems are operational.

Updating your devices will always be a headache for your business; the larger your organization, the more effort it will take to make sure all your systems are operational. Conversely, de-commissioning devices will also take time due to the secure nature of your data.

Ensure your team is able to remove software and make updates to your devices with relative ease. Once the software outpaces the hardware capabilities though, put the devices out to pasture and reinvest in the machines your software requires to run properly.

product lifecycle stages diagram

Analytics and the future of business

Embedded analytics is about making changes today that will benefit your company in the future. 

How will analytics programs factor into that tomorrow?

For starters, data will always be foundational to all major operational changes. Whoever can collect and interpret the data correctly will remain competitive. 

Ensure your users have the ability to access that information. Use a modern data stack for data integration and control the flow of your data by lowering barriers between users and system, providing easier accessibility for data integration and analytics.

Sales and marketing will be able to use analytics to provide real-time insights into their activities. How is the audience responding to certain activities, and how can sales teams capitalize on gaps in the marketplace or other opportunities that present themselves. Additionally, analytics can gauge the performance of certain individuals to find your star players and put them in places to succeed.

Many companies are also using analytics software to monitor security threats. They can monitor discrepancies in their operations much quicker, and respond immediately to minimize the damage. Plus, since one analytics platform is funneling the traffic, you only have to maintain the single data pipeline instead of navigating a maze of data sources to find and fix security issues.

Final thoughts

Embedded analytics is about starting a new way of dealing with data and integrating it into the everyday business tools that you already use. It allows you to collect data, translate it into valuable insights within your business application, and help your users make better decisions.

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