As the digital economy becomes the economy, everyone who interacts with your business and products, from external customers, vendors, and partners to internal stakeholders benefits from having access to data. Requiring them to step out of their existing workflows and log in to a specific BI tool to do so, however, often means forgoing analytics altogether.
Embedded analytics are a great way to integrate real-time insights into the tools your users already leverage, whether it’s an existing customer-facing application or an internal tool used by colleagues. With so many embedded platforms on the market, it can be daunting to figure out which one is best for your particular needs. By asking yourself a few simple questions about user experience, scale, flexibility, and cost, you’ll be able to narrow down the choices and find the perfect platform for embedding analytics into your application. Read on so you can make an informed decision when selecting an embedded analytics platform for your business.
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An embedded analytics platform refers to a software solution that allows businesses to integrate analytics and reporting functionalities directly into their applications, products, or services. Instead of leveraging or building separate analytics tools, an embedded analytics platform enables organizations to add capabilities like data visualizations, Liveboards, generative AI, and reporting capabilities to their existing software interfaces, providing users with rich, real-time insights in context, without the need to switch between different applications. This allows companies to build data-driven cultures, monetize data, and even build entirely new revenue streams with data apps.
Embedded analytics have revolutionized the way organizations leverage data, build products, generate revenue, and retain customers. Let's explore the five main benefits in detail:
1. Empowering data-driven decision making
One of the most significant advantages of using an embedded analytics platform is its ability to empower data-driven decision-making, both across an organization and beyond to customers, partners, and vendors. By making data insights readily available, organizations can foster a culture that values data-driven decision-making. Embedding a self-service analytics experience within a product or service helps every user access and analyze data relevant to their roles without having to change processes. This enables them to make informed decisions based on objective insights rather than relying on intuition or guesswork. The ability to leverage data effectively empowers organizations to identify trends, spot opportunities, mitigate risks, and gain a competitive advantage in the market.
2. Enhanced data visualization and reporting
One of the primary benefits of using an embedded analytics platform is the ability to enhance data visualization and reporting capabilities. These platforms offer a wide array of visualization tools such as charts, graphs, maps, and dashboards. By embedding these visualizations directly into applications, users can easily interpret and understand complex data sets. Interactive data visualizations allow users to endlessly explore these visualizations, drill down into details, and uncover related, meaningful insights. Enhanced data visualization empowers users to communicate data effectively, leading to better-informed decisions and actions.
3. Seamless integration and customization
Modern embedded analytics platforms, especially those that are part of the modern data stack, offer seamless integration with existing applications or products. This enables organizations to bring the best, more innovative capabilities from across the data ecosystem, and expose them to users in the workflows they already utilize. Furthermore, these platforms often offer customization options, allowing organizations to tailor the analytics experience to their specific needs and branding.
4. Increased user engagement and adoption
Embedding analytics can be an incredibly powerful part of a user engagement strategy. By embedding analytics directly into applications, organizations can give users more value, significantly increasing user engagement and adoption of analytics capabilities. Users no longer need to switch between multiple tools or platforms to access data insights. Instead, analytics functionalities are readily available within their familiar application environment. Ideally, the embedded analytics experience is so easy, that every kind of user can intuitively leverage it without additional training. This convenience encourages users to explore and interact with a product more, leading to increased engagement, a higher adoption rate, and more robust data-driven decision making practices. With easy access to analytics in the tools they already know and love, users become more empowered to make informed decisions based on real-time insights.
5. Time and cost efficiency
Embedded analytics platforms offer significant time and cost efficiency benefits compared to building analytics capabilities from scratch. These platforms provide pre-built analytics components, including data connectors, visualization tools, and reporting functionalities, reducing the time and effort required to develop and maintain analytics capabilities. Further, by using the right embedded analytics tools, customers can get access to cutting-edge technology from an organization purely focused on analytics, instead of having to continually build these capabilities internally, leaving them behind the innovation curve. By leveraging an embedded analytics platform, organizations can save development resources, reduce time-to-market, and allocate resources to other critical business areas. Additionally, these platforms often offer flexible pricing models, enabling organizations to scale their analytics capabilities while maintaining cost efficiency.
6. Monetize data
The most innovative organizations, such as Guidewire, Harri, and Verisk, have taken embedding analytics further. Instead of simply adding analytics to their products, they are turning this data into dollars. With the right embedded analytics platform, you can charge a premium for access to this analytics experience in your product or service, or build entirely new data apps that offer new paths to profits. The end result is greater data monetization, turning data from a cost center into a revenue-generating engine. In fact, research from Product-led Alliance and ThoughtSpot found that 44% of product leaders expect revenue gains from embedding analytics.
1. ThoughtSpot Embedded
We might be a bit partial, but when it comes to embedded analytics tools, ThoughtSpot Embedded truly shines. Offering a comprehensive suite of features, ThoughtSpot Embedded allows you to seamlessly embed analytics and search capabilities into other applications, portals, or websites, extending the reach of data insights beyond standalone tools and integrating them into your existing digital ecosystem. With search-driven analytics, users can effortlessly explore and analyze data through natural language queries, making data exploration intuitive and user-friendly. Customization options enable you to tailor the embedded analytics experience to match your brand and specific user requirements.
Additional features
Boosting developer productivity, ThoughtSpot provides readily available analytics services, robust APIs, and a collaborative developer community.
Integration with leading cloud platforms such as Snowflake, Databricks, and Amazon Redshift ensures scalability and efficiency, while additional features like commenting, ThoughtSpot Modeling Language (TML) for scriptability, and Git integration offer enhanced functionality.
With ThoughtSpot Sage, analytical capabilities can be seamlessly integrated into any data app, further expanding the scope and impact of embedded analytics within your product.
2. Looker Embedded
Looker’s embedded analytics platform provides integration capabilities, enabling organizations to embed data visualizations, dashboards, and insights directly into their existing applications or workflows. This integration ensures that users can access analytics within familiar interfaces, reducing the need to switch between different tools or platforms. It allows organizations to combine data from across their business and define metrics that matter most for their stakeholders. They can access real-time insights to make informed decisions quickly and effectively.
However, integrating Looker Embedded can be complex and may require significant technical expertise. It entails licensing fees and additional costs for customization, support, and maintenance. Users, especially developers and administrators, may face a learning curve when working with Looker Embedded.
3. Tableau Embedded Analytics
Tableau Embedded Analytics allows organizations to integrate Tableau's data visualization and analytics capabilities directly into their applications or websites. Organizations can customize the embedded analytics experience to match their branding and user interface requirements. This includes the ability to customize colors, fonts, and layouts to create a seamless user experience within their applications.
Moreover, integrating Tableau's embedded analytics directly into applications allows seamless data exploration and analysis. It facilitates dynamic reporting, real-time updates, and customized dashboards. However, integrating Tableau's embedded analytics may incur licensing costs for expanding user bases, pose a learning curve for new users, and encounter potential performance issues with resource-intensive demands.
4. Sisense
Sisense is an embedded analytics platform that enables organizations to integrate analytics directly into their applications, products, or websites. It offers features such as data integration from multiple sources, data visualization through dynamic charts and dashboards, and AI-powered analytics for automated insights. Users can perform self-service analytics with an intuitive interface, and the platform is scalable to handle large datasets and support thousands of users simultaneously.
Yet, Sisense comes with potential drawbacks that include a complex implementation process requiring skilled developers and a learning curve for new users. Additionally, the cost may be prohibitive for smaller organizations.
5. Qlik Embedded Analytics
Qlik Embedded Analytics facilitates access to insights and decision-making capabilities within the same interface, eliminating the need for users to switch between multiple tools or platforms. With Qlik Embedded Analytics, organizations can create dynamic and interactive data visualizations, including charts, graphs, and maps. Users can explore data through intuitive interfaces, drill down into specific details, and uncover insights. It offers robust data connectivity and integration features, allowing users to access and analyze data from multiple sources.
While customizable to match the organization's interface requirements, users may find customization options somewhat limited compared to other platforms. Furthermore, maintaining consistent performance with large datasets and concurrent users may pose challenges for some organizations.
Whether you’re a SaaS company looking to reduce customer churn or an e-commerce company building an application to avoid stockout costs, embedded analytics platforms offer organizations the opportunity to leverage data within their applications to delight customers and users while creating new paths to money. With a variety of options available in the market, choosing the right embedded analytics platform requires careful consideration of several factors. Here are five key steps to follow to help you choose the most suitable platform for your business:
1. Assess your business needs
Begin by assessing your organization's specific needs and requirements. Consider the type of data you work with, the complexity of analytics required, and the intended audience for the embedded analytics, including whether this is for internal users, or something that will be used by external users like customers and partners. Determine the specific goals you want to achieve with the platform, such as improving operational efficiency, enhancing customer insights, or optimizing decision-making processes. This assessment will help you align the features and capabilities of the platform with your unique business objectives.
2. Evaluate integration capabilities
Ensure that the embedded analytics platform seamlessly integrates with your existing applications and technology stack. Assess whether the platform supports integration with your data sources, databases, APIs, and programming languages. Consider the ease of integration and the availability of resources and documentation provided by the platform vendor. A robust integration capability will enable smooth data flow and ensure compatibility with your existing infrastructure.
3. Consider scalability and performance
Scalability and performance are crucial factors to consider when choosing an embedded analytics platform, especially for new products where you don’t know how many users will eventually be leveraging your service. Evaluate the platform's ability to handle large volumes of data and support a growing number of users without requiring a similarly large investment of resources. Consider factors such as response time, query performance, and data processing capabilities. It is essential to choose a platform that can scale with your business needs and deliver fast and reliable analytics performance, even as your data and user base grow.
4. Analyze data governance and security features
Data governance and security are paramount in today's data-driven landscape. Analyze the security features offered by the embedded analytics platform. Look for features such as data encryption, user authentication, and role-based access controls to protect sensitive data. Assess whether the platform complies with relevant industry regulations and standards, such as GDPR or HIPAA, depending on your industry requirements. Additionally, consider features that support data governance, audit trails, and data privacy to ensure compliance and maintain data integrity.
5. Review support and training options
Evaluate the support, community, and training options provided by the embedded analytics platform vendor. Determine whether they offer reliable technical support, documentation, and resources to assist with implementation and troubleshooting. Consider the availability of training programs, tutorials, and user communities that can help your team effectively utilize the platform's features. A vendor that offers comprehensive support and training will facilitate a smoother implementation process and enable your team to make the most of the embedded analytics platform.
6. Ease of use
The end goal of embedding analytics is to make your products more efficient and valuable to users when, where, and how they already work. Embedding an analytics experience that requires technical skills inherently limits the potential pool of users. Instead, look for embedded analytics platforms that deliver a modern, intuitive analytics experience that’s as easy to use as your favorite consumer app. In doing so, you’ll be able to bring this analytics experience to as many users as possible.
Start encouraging users to explore and interact with data
Embedded analytics platforms provide organizations with an efficient way to uncover insights and empower their users to efficiently explore their data. With modern-day embedded analytics platforms, selecting the best platform for your organization’s needs is easier than ever before. They allow you to embed your interactive analytics content in any application, giving you a unified approach for exploring centuries of data across the entire enterprise. After outlining the benefits of leveraging an embedded analytics platform, such as ThoughtSpot, it is clear that taking advantage of such a product offers myriad advantages that can help fuel decision-making and enable fact-based discussions when presented with any kind of challenge or opportunity. Take advantage of new technologies by signing up for a ThoughtSpot free trial today and see how easy it is to get started with using the power of embedded analytics.
