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Embedded Analytics

As businesses continue to make analytics and BI their top investment priority, choosing the right embedded analytics vendor to partner with is paramount. But what exactly does embedded analytics do, what are its benefits and key elements, and how to choose the best solution for your business needs are all questions that we know a lot of you still ask yourself. Here, we’ve gathered everything that you need to know about embedded analytics.

When you integrate analytics into your business applications, you can achieve many benefits, such as:

Another difference between traditional BI and embedded analytics is that sometimes BI fails to deliver the intended value because it is not integrated with the user’s workflow. Due to that, it doesn’t give the context and the insights needed to act. On the other hand, embedded analytics helps the decision-making process by providing insights on a dashboard — users can use it to take immediate action and report at any time.

Not all analytic products have been designed to be embedded. Many of today’s embedded analytics and BI vendors built their standalone applications first so they are not purposely designed to be embedded into applications.

Also, they are designed from the ground up for web, cloud, and mobile delivery. Modern embedded analytics platforms also make it easier for developers to create custom analytic applications.

When using embedded analytics, users are looking at key business data in context, which removes the need of bouncing between multiple different apps to find the insights that they need. Therefore, when users don’t need to switch from business applications to analytics tools they can spend more time and focus on essential tasks. Plus, seeing data being represented in beautiful visualizations also drives perceptions.

One of the biggest benefits of embedded analytics is the competitive edge that it provides both software providers and end-users, including:

Users won’t waste time switching between apps but instead focus on the value that the embedded analytics software provides. Having their answers and key insights right in front of them leads to increased productivity and increased customer satisfaction.

On top of that, embedded analytics tools can provide additional revenue streams. Thanks to its huge value for the business, some of the features and functionalities could become extra and your sales team could upsell them to new and already existing customers.

Embedded analytics provide insights to users, but on the other side, it also provides useful insights to your team. Presenting accurate and up-to-date data enables analytical thinking that could ultimately drive innovative ideas and improved products.

These are some of the key functions that are included with embedded analytics software:

Dashboards are embedded analytics tools that visually display data patterns for analysis, presentation, and easy understanding. Dashboards can consist of pie graphs or charts, bar or line graphs, scatter plots, color-coded maps, or any other kind of visual data representation.

Key features include:

Drill-down takes a user from general overviews to more detailed analysis with a single click.

Wikipedia defines statistics as the study of the collection, analysis, interpretation, presentation, and organization of data. In terms of data analytics, this can include key statistical functions such as outliers detection, time series forecasting, and linear regression, as well as the ability to embed these interactions into visualizations or allow features such as dashboard drill-downs and dashboard linking.

Outliers Detection lets users easily detect points in their data that are anomalies and differ from much of the data set. They can show or hide these outliers from view, so they’re always showing or so they don’t interfere with the analysis.

Linear Regression lets users visually see trends in their data by finding the relationship between two variables and seeing a linear approximation of the data — including future trends. Along with Linear Regression, other algorithm trend lines include Linear Fit, Quadratic Fit, Cubic Fit, Quartic Fit, Logarithmic Fit, Exponential Fit, Power Law Fit, Simple Average, Exponential Average, Modified Average, Cumulative Average, and Weighted Average.

Building your own embedded analytics solution might be the right option for those who could afford a higher budget and the human resource to do that. It gives you total control over the software, as well as it has more options for customization.

Also, building your own embedded analytics platform allows you to solve any security problems internally. This is important and might be a great bonus to those who are working with sensitive data that requires higher security levels.

Most organizations decide to buy an already established embedded analytics solution to integrate with their existing software. One of the top reasons why this is the preferred option is that buying it instead of building it saves you both time and money. It also allows you to free up your developers’ resources and time so that they can focus on your core competency and what your business was initially designed for.

Depending on the solution provider, you may be limited to basic dashboards and reports, as well as have limited customization options.

A recent 2019 survey report produced by Infragistics found that the most popular applications that development teams were either actively embedding analytics into or were planning to do so soon are shown in the graphic below:

Some leading industries that incorporate the power of embedded analytics include:

With the power of embedded analytics, marketing teams can gain a better understanding of their customers’ and campaigns’ performance. Marketers can observe how consumers react to their campaigns, determine what strategies and types of content are working and what isn’t working, and use these insights to improve their marketing activities in the future so that they lead to an increase in sales.

Native metrics from social media platforms give you limited information, which is why most of these networks use embedded analytics to help them see their campaigns from a broader perspective. Embedded analytics tools help them to predict campaign performance, suggest content recommendations, recommend the best time for publishing based on time zones, offer various paid ads analytics, and more.

Your Facebook, for example, always knows what you have bought online and uses this data to up-sell related items each time you log in to the app.

Netflix and Spotify, for example, use embedded analytics to come up with relevant series/song recommendations that they know their users would love.

Allows transportation managers to track the path of an order: order fulfillment, shipping, and delivery tracking, and if there are any issues that require attention and action. Furthermore, transportation and shipping companies use embedded analytics for their business to increase the productivity of their workers so that warehouse managers could keep track of key indicators such as average time or shipping and preparing the order.

Native integration with your app — the embedded analytics solution must be able to seamlessly integrate with all your applications. You don’t want to burden your IT team, so look for a solution that won’t add additional weight and complexity. Look for a solution that has been built from the ground up with embedded in mind first.

Connectivity — if the solution cannot connect to all of your data, what good is it? Make sure that the embedded analytics vendor offers seamless integration with all the data sources that you need.

APIs — the embedded analytics solution that you decide to invest in should also include an application programming interface (API), which allows the business application to use custom hooks when embedding the BI capabilities.

Scalability — the scale of the solution’s operations must be able to upscale or downscale in response to an increase/decrease in its user base. This means that a good embedded analytics solution will allow you to increase your existing resources to accommodate increased business needs or changes.

Pricing — many vendors use shady pricing tactics to maximize their profits. You don’t want to partner with a vendor that will charge you unpredictable costs like usage and users, for example. We recommend choosing an embedded analytics solution that has a 100% transparent pricing model that won’t escalate as your app sales increase.

As you can see, whether you produce an app or a service, and regardless of in which industry your business lies, embedded analytics comes with tremendous opportunities to expand your business, add value for your customers, increase productivity, and of course, drive revenue. In today’s business era, embedded analytics is no longer ‘’nice to have’’, but a ‘’must have’’ solution.

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