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.
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.
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.
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.
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.
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.
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
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.
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.
With enhanced embedded analytics, commercial software providers can also improve internal operational efficiencies.
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.
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.
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.
With enhanced embedded analytics, application providers can also bring operational efficiencies.
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 software varies depending on your target requirements and approach. We will cover the most common methods at length in the next chapter.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.