Embedded Analytics Becomes More Pervasive
Application vendors are realizing that they have to keep their customer engaged in the application. Embedded analytics, which integrates data analytics within business applications, helps to increases customer engagement while ensuring competitive advantage, reveals the Logi Analytics fifth “State of Embedded Analytics Report” for 2017. While the adoption of standalone Business Intelligence (BI) tools has been around 20% during the last three years, the adoption of embedded analytics has increased to 60% in 2017 per the report.
Embedded analytics has till now been used by OEMs and SaaS vendors. The report finds that while traditional BI tools focused on deriving insights from data silos, embedded analytics helped organizations empower their employees to take decisions that are data-driven, by incorporating the required data in the application itself.
The report is based on a survey of 500 people who are involved in product management, software engineering, product development, and IT. The respondents include executives who work with Software as a Service (SaaS) providers, and commercial Independent Software Vendors (ISVs). It also includes executives who work with the internal IT-managed applications.
The report reveals that embedded analytics is incorporated in about 85% of non-commercial applications and about 95% of commercial applications. About 21% of the users who had access to standalone BI tools, accessed them on a regular basis. Comparatively, 60% of the users who had access to embedded analytics, leveraged them on a regular basis.
The main drivers of this adoption were top management (40%), product management staff (34%), development staff (11%), customers (10%) and competition (3%). Executives are showing more interest as they see their competitors win new customers and retain old customers because they increasingly use analytics.
About 55% of the ISV respondents said that adoption of embedded analytics helped improve their win rate. About 57% said that it helped to differentiate their product while 71% said that embedded analytics helped improve revenues. The percentage value attributed by embedded analytics to the overall product value of an organization was pegged at 54% for 2017.
Improved customer satisfaction, increased end-user adoption and improved user experience were the main benefits got from leveraging embedded analytics.
While 84% of the respondents prefer to access analytics within their applications, 66% keep switching to separate tools for analytics. The report says that this is because “as application providers offer self-service capabilities to end users, those users begin to expect certain capabilities as they explore data — for example, drilling, filtering, and workflow integration. If the self-service analytics UI has been implemented poorly, it can lead to user frustration — and thus more ad hoc requests.”
Embedded analytics is also providing ISVs with a new revenue stream, with 78% of the commercial ISVs charging more for analytics, with the charge depending on the level of embedding. About 74% of Level 0 and Level 1 embedders charged more for their application, while 63% of Level 2 embedders, 74% of Level 3 embedders and 83% of Level 4 embedders respectively charged more for their analytics.
The report reveals that vendors that provided subscription-based services, charged about 1.4 times for analytics when compared to the vendors who had one-time purchases. Subscription vendors were charging more as their tiered offerings allowed them to reduce upfront costs by charging according to the tiers.
With top executives showing interest in embedded analytics, there are more resources being allocated to these initiatives. As a result, about 32% of the respondents took less than four months to add embedded analytics to their applications. About 76% of the respondents preferred to build or have a combination of buy and build for adding embedded analytics.
About 72% of the respondents were planning to increase their future investments in embedded analytics. The additions planned include dashboards (15%), mobile access (13%), self-service analysis (13%), reports (12%), predictive analytics, data preparations, workflows, write-backs, natural language generation and building connections to new data sources.