We all know analytics is the process of transforming data into insights to help businesses make better decisions, improve customer satisfaction, and increase revenue. Analytics can be applied to various aspects of a business, such as marketing, sales, operations, finance, and more.
However, analytics is not only useful for internal purposes. It can also be leveraged to create value for external customers, especially when it comes to software-as-a-service (SaaS) applications. By embedding analytics into SaaS applications, businesses can provide their customers with relevant, timely, and actionable information that can enhance their user experience and satisfaction.
What is Embedded Analytics?
Embedded analytics is the integration of analytical capabilities and content into SaaS applications, such as dashboards, reports, charts, graphs, maps, and more. Embedded analytics allows users to access and interact with data and insights within the context of their workflow, without having to switch to a separate analytics tool or platform.
Embedded analytics can be implemented in various ways, depending on the level of customization and complexity required, but always requires connecting to the data source in use by the SaaS application back-end so that end users can analyze the data they are creating on the platform.
What is a Modern, Cloud Native Application?
A modern, cloud-native application is an application that is designed and developed to run on the cloud, taking advantage of its scalability, reliability, and flexibility. One of the best approaches to use serverless technology, which is a way of running applications without having to manage or provision servers.
Serverless technology allows developers to focus on the business logic and functionality of their applications, rather than the infrastructure and operations. Serverless technology also enables applications to scale automatically and dynamically, based on demand and usage.
Examples of serverless technology are:
Functions as a service (FaaS), are small, stateless, and event-driven units of code that execute in response to triggers, such as HTTP requests, database changes, or messages. Some examples of FaaS platforms are AWS Lambda, Azure Functions, and Google Cloud Functions.
Backend as a service (BaaS), which are cloud-based services that provide common backend functionalities, such as authentication, database, storage, notifications, and more. Some examples of BaaS platforms are Firebase, Parse, and AWS Amplify.
Here is a previous post we wrote about the benefits and considerations of using serverless with B2B SaaS applications.
Why is Embedded Analytics for SaaS Applications Important to a Company’s Revenue Growth?
Embedded analytics for SaaS applications can provide several benefits to a company’s revenue growth
Increasing customer retention and loyalty by providing customers with valuable insights that can help them achieve their goals, solve their problems, and improve their performance.
Enhancing customer satisfaction and engagement, by providing customers with a seamless and intuitive user experience that allows them to access and interact with data and insights within their workflow, without having to switch to a separate analytics tool or platform.
Differentiating from competitors, by offering customers a unique and innovative value proposition that can help them gain a competitive edge in their market.
Generating new revenue streams, by creating new opportunities for upselling and cross-selling, such as offering premium analytics features, functionalities, or content, or charging for additional data sources, integrations, or usage.
Embedded analytics within SaaS applications is a powerful way of creating value for both businesses and customers, especially in the context of modern, cloud-native SaaS applications. By embedding analytics into SaaS applications, businesses can provide their customers with relevant, timely, and actionable information that can enhance their user experience and satisfaction, and ultimately, drive revenue growth.
At Qrvey, we know that SaaS companies need strong analytics to remain competitive within their respective markets. That’s why Qrvey is built from the ground up exclusively for embedded analytics within SaaS applications powering platforms with a solution that includes both the front-end user-facing tools and the back-end developer tools to get to market fast.