Big data

Why Businesses need Embedded Analytics to Transform into Smarter Enterprises

Why Businesses need Embedded Analytics to Transform into Smarter Enterprises

Change is the only constant.

We have repeatedly heard this phrase and it’s never been truer until now. With the pace at which the technology is transforming the world, companies either adapt or simply fail to make it work. Technology is one of the most significant external force driving the market today.

Today, we see lawmakers leveraging newer technology for various policies, encouraging organizations to be transparent in their way of processing consumer data. The market is also changing and companies like Google, Amazon, and Airbnb  are dominating the market scene. These companies have managed to carve out entire market segments and industries for themselves. This invariably means that no matter which sector you are in, you will increasingly feel these giant’s presence and will have to compete with them.

In response to these external forces, companies are hurrying to transform themselves digitally by harnessing new technology to future-proof themselves of the ever-transient market and trends. And data is at the heart of this transformation. Data enables usage of new technology and actionable insights which companies can rely on for better decision making.

Enter Embedded Analytics

Raw data itself means nothing. It will be just a bunch of numbers and random information till its analyzed and converted into insights that can be used for decision making. But apart from analytics, there is another new trend in the industry that is gaining popularity very fast: Embedded Analytics.

Usually, analytics refers to data acquisition, data transformation, and business intelligence development to convert raw data into actionable insights.

Embedded analytics, is all about using analytical capabilities in a transactional business application. Traditionally analytics exist in a singular infrastructure where one needs to constantly toggle between business workflow applications. With embedded analytics, we bypass the problem of toggling between two different structures saving a lot of time and energy and delivers relevant insights into the workflow with minimal disruptions.

How embedded analytics transforms business processes?

Adopting embedded analytics can transform your business processes in the following ways:

  1. Improves business performance

The integration of business operations with embedded analytics allows users to take immediate actions based on the process and insights. With embedded analytics, decision making within the operational space continuously improves operations by enabling action based on real-time situations.

While the traditional spreadsheet method is easy to use, it kills productivity with drawbacks such as static data, little data validation, high susceptibility to data corruption, difficulty in pinning down a single source of truth and embedded macros that tend to malfunction for unaccountable reasons. Switching to embedded analytics avoids these issues and leads to productivity gain.

  1. Improves decision making

A key characteristic of organizations which rely heavily on decision making is to use the data in a persuasive way. This is where embedded analytics plays a major role. By presenting timely insights during the normal workflow, conditions them to think analytically during their normal working hours, increasing efficiency.

  1. Increases competitiveness

Embedded analytics is transforming consumer applications. Some of the most widely used apps like Fitbit have leveraged its usage like no other and paved the way for many more to follow. These apps blend in so seamlessly into the user’s lifestyle that we even forget to notice that they are there, yet they continue to effectively influence consumer behavior. Combining traditional workflow with contextual insights can give a unique value proposition to the consumers, depending upon the depth of your analysis.

According to Logi analysis, there are 5 levels of analytics-

  • Standalone- Analytics live in a separate surrounding than the business application.
  • Bolt-on- Integrate analytics and business applications into the same framework.
  • Inline- Analytics appear with the business application as a separate portal or tab.
  • Infused- Analytics are embedded into the core functionality of the business application.
  • Genius- Infuse analytics with self-serving capabilities.  
  1. Improves customer satisfaction

Take an example from Amazon or Netflix. Their strategy to integrate embedded analytics with their customer-facing storefronts can lead to repeated sales, larger shopping carts, and very happy customers.

Building upon the viewing habits of almost 125 million viewers, Netflix was able to make a huge array of data management platforms and curate content that their users loved. With the help of targeted viewing recommendations, they allowed users to explore different types of content. With the help of embedded analytics, they were able to produce 1$billion a year in customer retention.

Rivaling Netflix’s abilities is Amazon’s point of sale recommendations. These appear just as the consumer is about to checkout and combined with Amazon’s one-click purchase and efficient distribution network, they have grown immensely.

  1. Increases Revenue

There are 4 opportunities that embedded analytics provide that can help increase revenue.

  • Increased in-rate- Adding analytical capabilities can revamp existing applications interesting new users.
  • Decreased churn rate- Analytical capabilities can secure existing users by providing new problem-solving abilities to demonstrate a commitment to improving the application.
  • Expand product licensing- Adding embedded analytics can help you cast a wider net to a different type of users.
  • Feature monetization- It can give new opportunities for existing customers to buy new value-added functionality.

A company that’s got these revenue tricks right, is Fitbit. The Device transfers users activity the cloud, which then feeds personalized analytics to help user optimize their performance. Fitbit has monetized this user data by creating personalized benchmarks and fitness plans that can be sold to its user base. With this Fitbit now owns approximately 70% of the fitness wearable device market.

Looking to embed analytics with your day to day operations? Contact us Datahut, your big data experts.

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