Embedded Analytics is the ruler of the businesses at the present time. Analytics have been embedded ubiquitously into almost all the areas of life starting from applications, consumer gadgets, and other intelligent things.
According to Market Research Future, the market for embedded analytics is forecast to grow by 14% per year to a $52 billion market by 2023.
Technically, Embedded Analytics is the use of analytics and reporting capabilities in transactional business applications. Using Embedded Analytics the need to toggle between separate systems to extract the useful insights is eliminated enabling great control over the entire process to its users. At the present time, companies are actively implementing Embedded Analytics to make decisions that are context-specific and have many wide-ranging benefits. The companies are becoming more customer-oriented and hence, insights obtained from Embedded Analytics help them to understand their audience better and provide them all the information they expect.
Following types of Intelligence is provided by the Embedded Analytics to the companies:
1. Intelligence On the Process
This type of intelligence enables customers to use their data strategically to identify trends and analyze the business and analyze business performance metrics.
2. Intelligence In the Process
Intelligence In the Process works while a process is running or simply we can say that it changes the process.
3. Intelligence DRIVING the Process
Intelligence DRIVING the Process uses metrics to modify the process flow and automatically trigger the decisions. These types of intelligence provided by the Embedded Analytics are very useful in enhancing the overall functioning of the applications.
Now, let’s take a look at some of the benefits which businesses can have if they make use of Embedded Analytics:
Using Embedded Analytics, the companies get timely data insights that help them in thinking in an analytical way and make data-driven decisions for the organization. The benefit of Embedded Analytics
does not end here; it also provides an opportunity for companies for agile analytics development. It has also been observed that Embedded Analytics not only provides business analytics to the users
but also provide user insights to the analytics development team, helping the team to improve their existing offerings and in developing new products.
According to the Gartner Group, “A key characteristic of a data-driven culture is using data in a pervasive way. Data-driven companies establish processes and operations to make it easy for employees to acquire the required information.”
Embedded Analytics have helped B2C businesses in a lot many ways. For example, Amazon and Netflix experienced the benefits of using
Embedded Analytics in terms of repeated sales, larger shopping carts, and happier customers. With the larger family of approximately 125 million viewers, Netflix actively combines an array of Big Data Management platforms, content curation, and data science tools to deliver targeted recommendations to the audience. It’s been confirmed by Netflix that the use of analytics behind its recommending engine has significantly decreased its customer churn by several percentage points and has increased the number of lifetime clients producing $1 billion a year from customer retention.
Talking about Amazon’s point-of-sale recommendations, the analytics embedded in its customer portal such as ratings, reviews, and product recommendations are almost unnoticeable and comes in front of the customer at the right time when they are about to make a purchase. These analytics have made Amazon stand out from the rest of its competitors from the past 7 years almost now. So, we can see the important role Embedded Analytics plays in bring in customer satisfaction.
According to Logi Analytics, the business user adoption rate of traditional BI applications is 21%; for embedded analytics it’s 60%. And, it also found that 84% of business users report they spend more time in applications that feature embedded analytics.
It is a well-known fact in the I.T. industry that developing stand-alone products require a great amount of work done in order to acquire and transform data into useful insights. The I.T. people know that the Extraction/Transformation/Load (ETL) phase of an analytics project is always “the long pole in the tent”. Along with being time-consuming, it is also quite expensive to source, profile, clean, test,
audit, confirm and validate data prior to analytics use. But, with the implementation and stickiness of Embedded Analytics, the risk associated with businesses can be reduced to a great extent.
Performing analytics using the legacy methods involve using spreadsheets to prep, analyze, visualize and distribute analytics. These spreadsheets along with being easy to use have some drawbacks which kill the productivity of the associated team. These drawbacks include little data validation, static data, high susceptibility to data corruption, malfunctioning of embedded macros and much more. By trading spreadsheets with Embedded Analytics all such pitfalls can be easily overcome and productivity
gains can be experienced. Using Embedded Analytics, the users have to spend less time in switching between applications and analytics tools and spend more time on value-added activities.
Embedded Analytics can help businesses to increase their sales, retain customers and expand product offerings. Businesses can have 4 distinct opportunities using Embedded Analytics:
– Decreased Churn Rate: Analytics-enables applications have problem-solving capabilities to secure existing customers.
– Increased Win Rate: Adding Embedded Analytics helps the businesses offer new features to the audience which can attract some new users as well.
– Expanding Product Licensing: By adding Embedded Analytics, businesses can help to target different types of users.
– Feature Monetization: Embedded Analytics can provide new opportunities to the existing customers to buy new value-added functionality.
Among many businesses, FitBit is the best example to look at. FitBit uses all the above-mentioned four revenue opportunities into action. The device transfer the user activity data to the cloud which is then used to develop personalized analytics designed to optimize the performance which further help to decrease the churn rate.
Overall, Embedded Analytics helps businesses with many tremendous opportunities to increase productivity, strengthen competitive positioning, and improve customer satisfaction.