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Embedded analytics

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Embedded Analytics enables organisations to integrate analytics capabilities into their own, often SaaS, applications, portals, or websites. This differs from Embedded Software and Web Analytics (also commonly known as Product Analytics).

This integration typically provides contextual insights, quickly and conveniently since these insights should be present on the web page right next to the other, operational, parts of the host application. Insights are provided through interactive data visualisations, such as charts, diagrams, filters, gauges, maps and tables often in combination as dashboards embedded within the system. This setup enables easier, in-depth data analysis without the need to switch and log in between multiple applications.

Definition

Embedded Analytics is the integration of analytic capabilities into a host, typically browser-based, business-to-business (B2B), SaaS, application. These analytic capabilities would typically be relevant and contextual to the use-case of the host application.

The use-case is, most commonly, B2B, since businesses typically have more sophisticated analytic expectations and needs than consumers. Here, though, the word "business" in "business-to-business SaaS", could also refer to organisational, operational use cases that ultimately benefit consumers (such as healthcare, for instance), e.g.: clinics & hospitals, care & correctional facilities, educational establishments (on/offline), government departments, municipalities, museums, not-for-profit organisations, overseers & regulators amongst others.

Business-to-business-to-consumer (B2B2C) use-cases might also be possible, for example a wealth management SaaS application serving wealth management organisations, where a user might be an advisor to consumers.

History

The term "embedded analytics" was first used by Howard Dresner: consultant, author, former Gartner analyst and inventor of the term "business intelligence" said Howard Dresner while he was working for Hyperion Solutions, a company that Oracle bought in 2007. Oracle started then to use the term "embedded analytics" at their press release for Oracle Rapid Planning on 2009 [citation needed]. In 2014, Dresner Advisory Services published "Embedded Business Intelligence Market Study" as part of the Wisdom of Crowds Series of Research, including 24 vendors. [1]

Considerations with Embedded Analytics

When evaluating embedding analytics, consideration would normally be given to integration at various levels, these would likely include: security integration, data integration, application logic integration, business rules integration, and user experience integration.

This is in contrast to traditional BI, which expects users to leave their workflow applications to look at data insights in a separate set of tools. This immediacy makes embedded analytics much more intuitive and likely to be viewed by users. A December 2016 report from Nucleus Research found that using BI tools, which require toggling between applications, can take up as much as 1–2 hours of an employee's time each week, whereas embedded analytics eliminate the need to toggle between apps.

Use-cases for Embedded Analytics

The use-cases for embedded analytics are as diverse as the vertical (industry-specific) or horizontal (function, process or role-specific - across industries) host applications in which they are embedded, some examples include:

Vertical Examples

Horizontal Examples

References

  1. ^ "2014 Embedded Business Intelligence Market Study Now Available From Dresner Advisory Services". Globe News Wire (Press release). 2014-10-29.
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