Chapter 2

Embedded Analytics: No Longer a Want but a Need

Find out how major shifts in technology are driving the need for embedded analytics.

Why Are Embedded Analytics a 100% Must-Have?

Users have set forth a revolution. Today, people expect information to be available at their fingertips. When a question pops into our heads, we immediately grab our smartphones to find the answer. We rely on increasingly mobile technology to comb through massive amounts of data and solve high-value problems. Bottom line is that analytics has migrated from a trendy feature to a got-to-have. Plus, there is an expectation that tools be visually appealing to boot.

Every App is Doing It

User expectations are high because consumer web applications have established a precedent. They have mastered the art of displaying data in an intuitive way while at the same time driving effortless transactions in their products. Once upon a time, apps like Amazon, Kayak, and Zillow were the ring leaders. Now, every consumer app is doing it. As a result, users expect more from the business applications they use every day, which puts pressure on application providers to satisfy their needs.

Bid Good-bye to Standalone

Users don’t want to have to leave their app or call IT for insights. Standalone is a thing of the past. All of the above points to embedded analytics being not just the trendy route but the essential one.

Users Want to Help Themselves

Data mining is no longer confined to the research department. Today, every professional has the power to be a “data expert.” They can gather information on their own to make key business decisions. According to Hanover Research, 72 percent of end users surveyed personally access analytics in their roles more than once a week.

Natural Evolution of the BI Market

BI was Crystal Reports in the ‘90s and multi-dimensional analysis at the turn of the millennium. The market has since evolved. In this new era, users expect to reap the benefits of analytics in every application that they touch. The addition was once a competitive edge, but the absence is now a business downfall. According to the 2021 State of Analytics: Why Users Demand Better report by Hanover Research, 77 percent of organizations consider end-user data literacy “very” or “extremely important” in making fast and accurate decisions. Users’ varied needs require a shift in traditional BI thinking.

In the past, data visualizations were a powerful way to differentiate a software application. Companies like Tableau (which raised over $250 million when it had its IPO in 2013) demonstrated an unmet need in the market. Their dashboards were visually stunning. In turn, end users were thrilled with the bells and whistles of charts, graphs, and dashboards.

With these capabilities came revenue: Not too long ago, embedding even basic visualizations was often enough for product teams to charge more for their applications. It was enough to set them apart from competitors.

Today, free visualizations seem to be everywhere. Two trends, in particular, are forcing application providers to rethink how they offer analytics in their products.

Data visualizations are no longer driving revenue: Everyone from Google to Amazon now provides low-cost or no-cost visualization tools that drive down the perceived value of data visualizations. Users are coming to expect sophisticated analytics at little or no cost.

End users expect more from analytics too. Data visualizations are not only everywhere, they’re better than ever. These days, data insights are frictionless. They are integrated into everything, from the driving of performance (Progressive, State Farm), to home energy usage (Nest, Belkin). As rich, data-driven user experiences are increasingly intertwined with our daily lives, end users are demanding new standards for how they interact with their business data.

When visualizations alone aren’t enough to set an application apart, is there still a way for product teams to monetize embedded analytics? Yes—but basic dashboards won’t be enough. Read on for new ways to monetize your embedded analytics offerings.

Embedded Analytics Drive Successful Consumer Applications

Consumer web applications have transformed how people use and interact with data. Along the way, products and services that embed analytics benefit immensely by (1) growing their user base, (2) differentiating themselves from competitors, and (3) driving revenue.


Amazon is the leading e-commerce site. They have built a business on low prices, a frictionless one-click transaction process, and fast shipping. Amazon also provides data and analytics – in the form of product ratings, reviews, and suggestions – to ensure customers are choosing the right products at the point of transaction. They have created a superior customer experience, making it unnecessary for most people to visit a brick-and-mortar store and putting a slew of retailers out of business along the way.

Net sales of $386 billion in 2021

200 million Amazon Prime members worldwide


As the leader in sales tracking, Salesforce takes great advantage of the latest and greatest in analytics. They take their reports and showcase them through an instantaneous visualization on record pages. Salesforce monitors the activity of a prospect through the sales funnel, from opportunity to lead to customer. Salesforce Account Managers use this to display and filter their report chart. The functionality allows them to zero in on the pipeline data that is associated with the account record of interest. Managers like the flexibility that comes with viewing this chart so that it is filtered automatically to a unique Salesforce account record.

2004: First went public

2021: Annual revenue $21.25 Billion


Fitbit is the leader in fitness wearables. Their devices monitor a user’s activity and transmit data to the cloud. Users can then analyze their activity through the online application. This helps them to understand how they are performing and discover ways to adjust future activity. As a business, Fitbit not only sells devices, but also generates revenue through a premier membership program. The program offers valuable data analysis-based services such as benchmarking and personalized fitness plans.

2020: $1.13 billion revenue, 31+ million people use once a week

Strategic Benefits for Commercial Application Providers

For commercial application providers making a case for embedded analytics, let’s take a look at the benefits your business can expect to achieve.

Increasing Revenue and Competitive Differentiation

Building a business case for any project most often centers around three strategic benefits: (1) attracting new users, (2) increasing revenue, and (3) creating product differentiation.

This holds true for embedded analytics as well.

  • Attract new users: By adding capabilities to the product, software providers more easily attract both new clients and new users at existing client companies. All benefit from the enhanced functionality and additional reporting and analytics.
  • Increase revenue: Ninety-eight percent of commercial application providers say embedded analytics has helped them increase revenue; 68 percent say they’re able to charge more for their products because of the value embedded analytics brings. Revenue growth can take a variety of forms. You might price embedded analytics as an independent add-on, or you might upsell customers to a plan that includes analytics. Other money-making strategies include adding users in a per-seat structure or achieving price-dominance in the market due. The latter is due to value-added functionality.
  • Differentiate your products: Software providers aim to differentiate themselves by adding self-service functionality and advanced analytics. They strategize to make things as easy as possible for the user through intuitive, out-of-the-box capabilities. With contextual embedding and analytics-driven workflows (a topic we will explore in the next chapter), providers succeed in more deeply integrating analytics.

Embedded analytics also help commercial application providers improve customer satisfaction, product demonstrations, and user experience.

Hanover Research conducted a study that researches the role of analytics from the view of “knowledge workers.” These are people who handle or use information as part of their jobs. The sample included 1,931 knowledge workers from various industries, including financial services, healthcare, and manufacturing. All were also tagged as end users, and are familiar with the analytics tools within their apps.

Hanover’s study revealed the following about analytics end users:

  • 70% use their analytics to organize their data
  • 63% deem analytics important in goal-setting
  • 53% use analytics to streamline processes
  • 87% use their analytics “often or very often” to make business decisions

Operational Benefits

With enhanced embedded analytics, commercial software providers can also improve internal operational efficiencies.

  • Reclaim development resources: Users of a self-service tool no longer have to rely on IT/software developers for data insights. In a survey of 500 applications teams, nearly 50 percent reported that with embedded self-service analytics, they were able to reduce the number of reporting requests from users. By adding self-service capabilities, the technology team will have more time to devote to other development tasks.
  • Fill the funnel: With visually engaging analytics, sales and marketing teams will find it easier to generate leads, push them through the sales cycle, and prove product value.

These operational efficiencies are key to calculating the full value of embedded analytics. They can sway executives to green-light a project just as quickly as the revenue-driving benefits.

Strategic Benefits for IT Application Providers

IT application providers stand to reap the benefits of embedded analytics. Taking non-commercial applications to the next level of analysis can be widely helpful.

Business End-User Benefits

Embedding analytics into essential applications makes analytics more pervasive. As a result, end users can better view shared metrics (backed by accurate data), which ultimately drives performance.

Here are just a few examples:

  • Increase revenue by identifying potential customers who are more willing to spend or renew, targeting specific market segments, or securing referrals through improved customer satisfaction.
  • Decrease costs by improving inventory management of goods, monitoring processes to increase resource utilization, or simply making it faster and easier for users to access the analytics they need.
  • Manage compliance through up-to-the-minute performance measures, workflow automation, and essential regulatory reports.

The benefits to your end users will depend on your application and target use cases, so use the examples above as a starting point for your own analysis.

Technology Operational Benefits

With enhanced embedded analytics, application providers can also bring operational efficiencies.

  • For those who have developers assigned to managing their current solution, choosing the right solution will free precious resources for other projects.
  • By adding self-service analytics capabilities, the technology team will reduce the number of ad hoc report requests from end users, freeing themselves for other development tasks.
  • When budgets are established, it will be easy to provide business justification for the embedded analytics project because it provides demonstrable value in a visually engaging way.

These benefits are integral. They help to comprehend the full value of analytics. It may make stakeholders more likely to approve a data project.

The Cost of Embedded Analytics

Every embedded analytics project looks at these investment areas when building a business case.

Software Licensing

The cost of software varies depending on your target requirements and approach. We will cover the most common methods at length in the next chapter.

These licensing terms are critical:

  • Perpetual license vs subscription: Subscription is a pay-as-you-go model that provides flexibility as you evaluate a vendor. Perpetual, by contrast, is paid up front. Software upgrades and maintenance are commonly included for an additional 15 to 30 percent annual fee.
  • Pricing model: The pricing scale is dependent on several factors. These include the number of customers, users, or servers deployed. In some instances, an “unlimited” model is also an option – though you should be mindful of how the contractual terms may fence you in. It is important to find a vendor who can align with how you deliver value to your customers today and grow with you as the business evolves over time.
  • OEM contract: Commercial application providers should double-check that the licensing terms give you rights to distribute the software to your paying customers.


Technical and consulting services are employed to make sure that implementation and maintenance go smoothly. The technical requirements and development resources approach will dictate the types of training and support you may need.

Developer resources

Internal developers should be included in the initial phase of implementation. They will also be responsible for upgrading and maintaining the embedded analytics functionality. Teams who dedicate substantial developer resources to their analytics may at some point adopt a third-party platform in order to move those resources back to the core application.

End-user training

To ensure the success of your solution, it’s important to invest in end-user training – even if the majority of your user base opts for self-service options, such as pre-recorded videos. Focusing on UX will reduce the amount of end-user training needed and accelerate user adoption.


You’ll incur an ongoing cost to maintain the solution, particularly as the number of users and usage grows. Some of these costs may be developer resources, while others may be non-technical ones, such as business user administrators.

Return on Investment

Now we bring it all together to calculate the ROI on embedded analytics.

  • Timeframe: Quantitative analysis for a technology investment is performed over an extended period of time, typically three to five years.
  • Benefits: The combination of the strategic benefits (e.g., revenue increase) and operational benefits (e.g., cost reduction).
  • Costs: The investment to develop and maintain the solution.
  • “-1”: The formula assures that a positive ROI is achieved only when benefits exceed the costs.

Commercial Application

As an example, let’s say a commercial SaaS provider brings in $2 million in revenue per year. They expect that this new embedded analytics functionality will drive a 10 percent increase in sales. (To keep this simple, we’ll ignore annual compounding). Over three years, that comes out to $600 thousand in added revenue. The self-service functionality is expected to free up half of one developer’s time (we’re assuming a $100 thousand internal cost per year per developer), thereby improving developer efficiency by $50 thousand per year. The total benefit comes to $750 thousand over three years.

Build versus Buy

In Chapter 4 of this guide, we tackle the “build versus buy” question and explore when it makes sense to choose one option over the other. Then, in Chapter 5, we outline the important criteria for evaluating third-party embedded analytics solutions.

The costs are expected to be $50 thousand per year in software plus $25 thousand in expert technical services. If a developer dedicates one quarter of their time to this project, your developer costs are $25 thousand per year. That makes the total cost $250 thousand over three years. The formula looks like this: ($750k / $250k) = 3, so the ROI is 200 percent.

Internal Application

Consider this second example: an internal manufacturing application that helps process $2 million worth of product a year. Embedded analytics help to streamline the process, reduce waste, and bolster the yield, all to the tune of 10 percent per year of total production. This results in $600 thousand in savings over three years. And just like the first example, with $600 thousand in revenue – if we make the same assumptions for additional benefits and for cost – we also end up with 200 percent ROI.

Getting Buy-In

In some cases, not all team members will immediately see the value of investing in embedded analytics. To get them on board, you’ll need to understand their priorities and what challenges stand in their way. Then you can connect the dots for them and show how embedded analytics address their specific concerns.

When you’re trying to gain internal support for the project, match it with the strategic initiatives of the organization. Position it as a potential solution to the high-value problems your business faces by showing how it will significantly impact your customers and the bottom line. This will help your organization see the project as a priority instead of putting it on the back burner.

The persuasiveness of your business case hinges on how well you address the challenges and goals of each stakeholder. When trying to convince your executives, be transparent about time-to-value and the effort the project will take. Don’t overpromise and then under-deliver. Embedding analytics is a journey, so the benefits and costs will be realized over a period of time. Getting value takes a strong plan, time, and effort.

4 Tips to Sell Embedded Analytics Internally

  • Get to know stakeholders’ problems and strategic goals. Create a business case that addresses their challenges. Create a quantitative analysis that proves how embedded analytics are the key to meeting these goals. For example, if increasing revenue is the main objective, build your case based on that.
  • Discuss, don’t present. Start by asking questions to understand what stakeholders are looking to achieve. Then transition by saying, “If I could show you how to meet those objectives efficiently and effectively, would you be interested in learning more?”
  • Support your position with real-life case studies, particularly from companies that are similar to yours.
  • Be prepared for a “yes” answer. Have your high-level plan ready along with an overview of next steps, timeframes, and required resources.

Positioning Embedded Analytics for Each Executive

Here are some tips on understanding executives’ priorities and getting them on board with the project.

CEO Priorities

  • Grow revenue and “hit the number”
  • Manage costs and meet profitability goals
  • Attract and retain talent
  • Innovate and out-perform the competition
  • Manage risk

Connect the Dots

  • Present embedded analytics as a way to differentiate from the competition and increase revenue.
  • Show how embedded analytics will enhance sales and marketing through better demos and shorter sales cycles.
  • Explain how an embedded solution would enable you to bring analytics to market faster.
  • Point out that embedded analytics helps attract and retain technical talent by allowing developers to devote more of their time to more engaging tasks.

CTO Priorities

  • Deliver the functionality the market needs at a high level of quality
  • Bring products to market faster
  • Utilize development resources effectively
  • Continually improve products to stay competitive

Connect the Dots

  • Discuss how embedded analytics platforms can help deliver needed functionality while reducing the developer resources required.
  • Educate them on platforms that encourage long-term business growth.
  • Discuss the option of receiving ample implementation support from an analytics partner knowledgeable in security, white labeling, and UI/UX requirements.

CFO Priorities

  • Manage expenses and cash flow
  • Enable profitable growth
  • Contain risk
  • Plan for the future

Connect the Dots

  • Do the math. Present your business case. Don’t worry too much about the fact that you’re making estimates, provided that they’re clearly labeled. You’ll build credibility simply by walking in the door with a spreadsheet and showing you can speak the CFO’s language. According to a 2019 ESG survey, developers were able to customize analytics based on what was best for the applications instead of making design choices to work with existing tools and were able to offer products that improved average selling price (ASP)and/or order value, which increased by as much as 25 percent.
  • Discuss how analytics help the organization to drive revenue while self-service functions free up technical resources.

Head of Sales Priorities

  • Make quota
  • Get an accurate forecast
  • Beat the competition
  • Expand market share
  • Facilitate customer success

Connect the Dots

  • Remember that the sales team is on the front lines. They provide market feedback based on what they hear from their prospects. Explain how embedded analytics can deliver the capabilities customers need. This strategy will ultimately increase sales, and prove a competitive advantage.
  • Discuss how embedded analytics help their team to deliver better sales demos, decrease sales cycles, box out the competition, and drive new revenue.
  • Discuss the value of embedded analytics to its end users. It drives increased renewal rates, exposes new opportunities to sell more products, and can create new revenue streams.

Product Manager Priorities

  • Deliver features and functionality customers are asking for
  • Bring products to market faster
  • Differentiate from the competition
  • Increase user adoption
  • Deliver a superior user experience

Connect the Dots

  • Help them visualize how the product will be enhanced through embedded analytics. Answer questions like, “what will users be able to accomplish” and “what is the value of solving those problems?”
  • Discuss how embedded analytics are a must. Highlight the competitive advantages. It is a way to enhance sales effectiveness through better sales demos, shorter sales cycles, and increased revenue.
  • Educate them on marketplace options for adding analytics quickly while meeting launch deadlines and bolstering UI/UX.

Business End-Users Priorities

  • Increase operational efficiencies
  • Make smarter decisions through the use of data
  • Effectively share and collaborate on analytics
  • Want technology that is easy to use, fits seamlessly into the course of everyday work, and doesn’t require much training

Connect the Dots

  • Paint a picture of how analytics will create a smarter organization, and focus on the key metrics that drive the business.
  • Build the vision of how insights will be readily available inside the applications in which they already have access.
  • Discuss the full breadth of functionality that will be available to them and its ease of use.

The Cost of Delaying

Here are some common reasons why people may delay investing in an embedded analytics platform and how you can overcome them.

I don’t need to use a third-party tool because I can build this all internally.

With enough time and energy, you can build anything. But do you really want to spend years building analytics? A third-party solution enables you to go to market faster and save money. Analytics vendors spend 100 percent of their time trying to make analytics faster and easier for you and your end users. By utilizing a third-party platform, you can do what you do best. Use the experts in analytics to add value to your product.

Let’s just give our customers access to the data. Let them do what they want outside of the application.

You’ve settled for becoming a data collection tool rather than adding value to your product. You’re leaving value on the table. While data exports may satisfy a portion of your customers, there will be many who simply want reports and insights that are available “out of the box.” You need to get out of the business of serving custom report requests. With embedded analytics, you will become the data expert that your customers expect you to be.

We don’t have the resources necessary to do this successfully.

This is all the more reason to integrate with a third-party product. They bring the domain expertise necessary to implement embedded analytics successfully. These include how-to guides, best practices, and in-person consultations. You can start small, and look for tools that conform to your architecture and your development process.

The days of Big BI are over. There are many options that will enable you to add real value to your applications without consuming massive resources.

We know our customers want something. We just don’t know exactly what it is they want.

If your customers are communicating any sort of pain, you need to investigate the root cause. When utilizing third-party products, you’ll first go through a thorough evaluation. Once they build a proof of concept with your very own data, you can use it to validate your direction with your customers.

It’s important to choose a platform that provides a broad range of functionality. One that supports prototyping will allow you to pivot on the fly. For these reasons, creating a solution that also supports self-service BI is an imperative.

Embedded analytics is nice to have, but it’s not a “must-have” for us.

Educate them on how analytics has changed the game for consumer and business applications. It is now most definitely a need-to-have. Show how analytics a) builds product value and b) enables users to work more productively with your application. To support your case, present findings from the State of Embedded Analytics study. The study outlines the clear benefits of embedded analytics: improving sales demos, driving faster revenue growth, and providing a competitive edge.

Bottom Line

There’s never a perfect time to roll out new software or start a new project. Don’t let the delay go on too long. You’ll always be busy. Once you’ve determined that you will benefit from the investment, move forward. The longer you wait to implement embedded analytics, the longer you’ll have to wait to see a positive impact.

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