Embedded analytics: A step-by-step guide to unlocking your data's potential

In a time where disruption and change have become the norm, data is the key to thriving amidst the volatility. In order to drive higher application engagement and boost customer satisfaction, product leaders and developers have to build delightful user experiences. Some organizations have turned to traditional business intelligence as a means for analyzing key data and making more informed decisions. 

While traditional BI is certainly valuable, it's limited by its inability to provide insights within existing applications, creating friction and impacting workflows. Similarly, BI fails to monetize data by exposing analytical experiences to customers and end users within applications and services they’re consuming.

Modern businesses and product leaders are embracing the benefits of embedded analytics, providing rich analytical experiences right within an application or product. There are a number of reasons organizations should consider leveraging interactive embedded analytics tools. But let’s start by defining embedded analytics.

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Embedded analytics is the integration of robust data analytics capabilities into other relevant applications. At its core, embedded analytics helps users better understand and use data by incorporating it into their existing business applications, workflows, and software—such as your product or website. 

By embedding analytics into the applications your internal teams regularly engage with—for instance, your customer relationship management (CRM) tool, financial systems, or enterprise resource planning (ERP) solution—users adopt a more data-driven approach to each part of your business. These insights improve business outcomes.

Product leaders might also look for opportunities to embed analytics into their consumer-facing products or software. By creating a user experience (UX) that incorporates interactive data, teams can create stickier products and provide additional value to the user. 

Embedded analytics allows product leaders to embed engaging analytics experiences within their products. However, creating such an experience requires the right set of tools and technologies. By collaborating with established vendors, you can leverage embedded analytics solutions to add dynamic dashboards and advanced analytics tools to almost any application. Even better, you can embed these experiences in days—not months or quarters.

These platforms offer multiple methods for embedding analytics, each with different levels of integration and flexibility:

• iFrames and HTML: Provide a quick and straightforward method for embedding basic dashboards and reports, requiring minimal development effort.

• Web Components: Offer greater control and flexibility, enabling developers to integrate analytics features seamlessly into applications while ensuring a consistent design and user experience.

• Developer-Friendly SDKs and APIs: Empower developers to create fully branded, highly customized analytics experiences that support advanced use cases.

Based on your business needs, such as desired features, scalability requirements, and pricing considerations, you’ll be able to narrow down the choices and find the perfect platform for embedding analytics into your application.

Some organizations choose to build their own embedded analytics solution, as doing so provides them with more control of the software and more options for customization. Plus, it allows a company to handle security issues in-house, which is valuable for those that handle highly sensitive data). 

However, building your own solution also requires a significant amount of time, dedicated resources, and a lofty budget—so it’s not the best option for every business.

Other organizations decide to leverage embedded analytics solutions that have already been built by a well-established provider. Nowadays, these solutions have built-in AI capabilities that you can utilize to monetize your app and create custom analytics experiences. Building such capabilities in-house is tough and expensive option. Plus, it doesn't require dedicating internal resources to create a custom solution of their own. Pre-built solutions generally offer greater ROI, reduced maintenance costs, and improved innovation. 

Embedded analytics puts the power of data-driven insights in the hands of everyday application users. In a recent survey, 55% of global respondents reported that they already offer embedded analytics in their products, citing benefits like increased user engagement, revenue, retention, activation, acquisition, and more.

Whether you’re looking to embed analytics in an internal or external-facing product, there are a variety of benefits, including:

1. Increase and create new revenue

Embedding analytics into your product is a great way to open new revenue streams—in fact, more than half of the PLA survey respondents (57%) said that embedded analytics had a direct result on their revenue. 

Take it from Harri, a SaaS company that helps businesses in the hospitality sector manage their most precious resource—their people. In order to meet the growing demands of the hospitality community during the pandemic, they decided to relaunch their product. The idea behind Harri iQ is to empower hospitality managers with intelligent data insights—getting managers out of ‘firefighting’ mode so they can focus on rebuilding healthy, sustainable businesses.

Given the global circumstances, Harri was looking to accelerate their time to market and provide a real-time, self-service user experience. By leveraging their data in the modern data stack and ThoughtSpot’s easy-to-integrate, embedded analytics solution, they were able to build Harry iQ and launch three monetizable product offerings based on their target user personas.

2. Scale data-driven decisions

Embedded analytics help businesses make better decisions, as it brings insights into the right existing workflows. This empowers every user to utilize data and make smarter, data-driven decisions—not just your IT team. By enabling true self-service analytics, you also free up time for IT teams to focus on higher-value tasks. These are the process improvements that really allow businesses to scale.

For example, embedded analytics tools like ThoughtSpot can create a huge impact on how organizations with frontline workers make day-to-day decisions. With AI-driven capabilities like SpotIQ and interactive Liveboards, users can perform a one-click analysis to understand not only what has changed, but also why it has changed. Armed with such deep insights, they can make decisions with greater precision ensuring that your business always stays ahead of the curve. 

3. Higher ROI on data products

Organizations generate massive volumes of data, but it’s only valuable if you can access it at the point of impact. Embedded analytics provides opportunities to use that data, enabling user-friendly insight that businesses can share both internally and externally. With easy governance and data controls, businesses can determine which users have access to what data and present reports or data visualizations securely.

By finding opportunities to embed data and analytics, businesses can generate revenue from customers and partners who will gladly pay for those deep, data-driven insights. For example, Just Eat uses embedded analytics within their food delivery app to help restaurant partners understand what times of the day are busiest. 

These insights provide value to restaurant owners, allowing them to staff and resource accordingly. Owners can also uncover which individual stores are performing the best and what types of food are most popular in which locations. By providing these important to restaurant owners, Just Eat provides more value with the data they were already collecting—making them an invaluable partner to restaurants.

4. Competitive advantage

The actionable insights gained from embedded analytics can help an organization boost its competitive edge—for both software providers and end-users alike. Consider a company like Nue, who is on a mission to reinvent the world of RevOps. With a mission that bold, you have to have a competitive advantage.

By embedding ThoughtSpot into their product, Nue was able to give customers a truly customizable, self-service BI and analytics experience. Enabling customers to slice and dice their data by any attribute was a core component of their product offering. After receiving their initial seed round funding, Nue is using their embedded analytics functionality  to drive conversations with advisors and investors.

5. Higher customer satisfaction

Because embedded analytics gives users easier, more seamless access to data, customers can quickly find answers to their questions without having to reach out for support. They can ask questions in a way that makes sense to them and gain real-time insights where they’re needed — all without having to log into, navigate, and learn a new tool. This positive user experience ads up to higher engagement. In fact, 61% of PLA survey respondents said that embedded analytics resulted in increased engagement.

Consider Data Recognition Corporation (DNC)—an organization with a long history of test and survey processing and administration for state Departments of Education, local administrators, and teachers. While looking for a way to expand their product offering and grow their annual revenue, they focused their sites on their data. 

DNC’s previous workflow included moving static flat files and spreadsheets between their data warehouse and BI tool. Because this process needed to be completed by a technical user, educators experienced a delay in test results. But as educators conduct more tests online, they expect to have near real-time access to results.

Using ThoughtSpot embedded in DRC’s solution, they’ve been able to give over 55.7k users access to self-service insights on tests. This means that teachers can directly interact with their data to discover which students require additional assistance. And they can do it all with just a few clicks.

6. Increased productivity among users

By reducing the number of tools that team members must use to collect, integrate, and analyze data, embedded analytics ensures greater efficiency. Organizations are more productive when they eliminate the technological barriers often associated with data analysis. For instance, with ThoughtSpot’s Spotter, business users can simply ask a question in plain English and receive instant visualizations. Even better, they can ask the next and the next question—without going back to the data team. This intuitive chat experience also reduces backlog for the data teams, allowing them to focus on strategic, high-value tasks instead of handling routine queries.

What’s more, users can easily identify and resolve issues without having to bounce back and forth between separate applications, which saves time and reduces frustrations. That’s more time back in users’ days to spend on higher-value tasks.

As you embark on your embedded analytics journey, It’s important to remember that not all solutions are built equally. To reap all the benefits of embedded analytics, organizations should first evaluate their options against some critical functionalities, including: 

1. Self-service analytics: If you want your embedded analytics to drive value, it needs to be accessible to all users—not just technical users. The solution should have an intuitive interface that allows users to create interactive visualizations, drill down into any data point, and uncover insights independently. 

2. UI customization toolkit: Choose an embedded analytics solution that offers UI customization tools. These tools enable you to tailor the interface to match your brand guidelines, ensuring a cohesive experience that aligns with your application’s look and feel.

3. Cloud-friendly: Your embedded analytics should easily connect and sync with your modern data stack. Seeing your up-to-date data and reusing pre-written data models and descriptions are a key component in delivering real-time insights.

4. Secure and governable: Not all users need access to the same data. To maintain compliance standards and uphold security, your embedded analytics solution must offer robust and flexible access controls. By implementing granular access permissions, you can ensure that sensitive data remains protected. 

5. Scalable: Embedded analytics solutions should aid your business growth—not hinder it. Look for a solution that can analyze your data as it scales without slowing you down.

6. Actionable: Look for a solution that can drive actions and automate business processes between apps like Slack, Salesforce, and Google Docs. APIs that connect your data to your processes fuel insight into action.

7. Developer-friendly: Look for a developer-friendly embedded analytics solution. This will allow you to get to market faster, keep your data product running smoothly, and limit developer frustrations as you grow.

In the evolving landscape of data-driven decision-making, integrating AI-powered features into your software or digital platform is more than just a technological upgrade—it's a competitive necessity. Here are the top ways AI-enabled embedded analytics solutions can help your customers, employees, and partners gain greater value from their data: 

1. Conversational, personalized data experiences

AI-powered embedded analytics is creating a paradigm shift in how users interact with their data. What this really means is that these solutions allow users to easily access and engage with real-time data, create reports on their own, and gain automated answers, enabling them to go from insight to action. 

For instance, by embedding an AI-powered analytics solution like ThoughtSpot, you empower your users to become the architects of their data journey. With Spotter, as their dedicated AI Analyst, they can simply ask questions in natural language and receive personalized insights and visualizations, making data exploration as simple as having a conversation. 

2. Enhanced data storytelling

Forget basic dashboards and static reports. With AI in the picture, users can easily spin up real-time, interactive visualizations to understand why changes occur in their data. They can monitor and analyze KPIs in real-time and explore different dimensions until they’ve crafted the exact data story they need to make informed decisions.

ThoughtSpot’s Liveboards elevate this experience further with drill-anywhere visualizations, customizable dashboards, and instant insights via AI capabilities. Users can easily pin, share, and present their data story, making it easier to analyze trends and identify actionable insights. 

3. Augmented analytics for advanced use cases

Previously, business analytics were primarily descriptive, providing insights solely about past events. However, with the rise of augmented analytics, you can now go beyond surface-level insights and leverage AI and ML to forecast trends, discover answers to complex business questions, and perform complex statistical analysis. 

For instance, embedded analytics solutions like ThoughtSpot offer SpotIQ that surfaces hidden insights within seconds. Using the power of machine learning and AI, SpotIQ automatically delivers insights and helps users anticipate outcomes, identify patterns and anomalies, or gain AI highlights, effectively closing the gap between data and outcomes.  

With data flowing from every direction, companies across industries are eager to understand how to turn their data assets into working dollars. If you're looking to do the same for your business, you can leverage embedded analytics tools to turn your data into dollars. In fact, research from Product-led Alliance and ThoughtSpot found that 44% of product leaders expect revenue gains from embedding analytics. Here are three powerful ways you can start monetizing your data with embedded analytics:

1. Value from improving

This data monetization strategy focuses on using data to support operational decision-making and achieve measurable improvements in business performance. For instance, by embedding analytics into daily workflows, product leaders can enhance various aspects of the business, such as boosting time-to-market, reducing customer churn, or optimizing the supply chain. The goal is to utilize embedded analytics to gain real-time insights into existing business processes to identify bottlenecks and reduce overheads. This, in turn, will increase your revenue streams. 

2. Value from selling

This strategy centers on embedding advanced data analytics capabilities directly into your products or services, creating a valuable offering for external customers. By doing so, you can charge a premium for access to these enhanced analytics features or build entirely new data apps that offer new paths to profits. Providing customers with these powerful tools allows your business to generate new income streams through high-value subscription plans, pay-per-use models, or other licensing strategies.

3. Value from wrapping

Data wrapping is the practice of adding contextual layers, such as metadata or summaries, around raw data to make it more meaningful and actionable. By integrating real-time data insights into internal tools, businesses can make informed, data-driven decisions that enhance customer experiences, improve resource allocation, and boost loyalty. With this enhanced visibility, organizations can quickly adapt to changing market conditions and seize emerging opportunities. As a result, data wrapping helps businesses boost productivity, lower expenses, and drive sustainable revenue growth.

While embedded analytics and business intelligence are similar in their objectives, they vary greatly in terms of context, use case, and results. 

Embedded analytics integrates analytics into existing websites, software, or applications to enable users to unearth insights relevant to the application or associated workflow. This empowers users to take data-driven actions. The data leveraged for embedded analytics might come from a variety of sources, including the application it’s embedded into. Embedded analytics isn’t necessarily a centralized view of all your data. Instead, it provides a specific, focused overview of information to help users make smart decisions based on the context around that information.

The most successful companies aren’t just using data to power their own apps. They’re putting that data, and more importantly, the insights buried within it, into the hands of their users. By embedding analytics into your custom-facing applications, companies can build better products and find new avenues to monetize their data.

In contrast, traditional business intelligence requires users to toggle between the business apps they use on a daily basis and the separate set of tools they use for data insights. Business intelligence solutions can provide immense value for managers and C-Suite decision makers, as they can gain a centralized overview of information. But because BI isn’t integrated into existing user applications and workflows, it tends to hinder productivity and efficiency. It also doesn’t offer the contextual insights needed to make swift, informed decisions within the same interface.

Organizations use embedded analytics to inject their everyday applications with real-time intelligence, which makes the overall user experience more meaningful and efficient. Here are a few examples: 

1. Websites

Embedded analytics can be especially useful to businesses that rely on accurate inventory to keep up with growing (or shrinking) customer demand, particularly in times of uncertainty. A big-box retail store, for example, can leverage an AI platform that uses machine learning to analyze sales data and identify patterns—such as an increase in purchases of a certain item. 

They can use that real-time information to deploy proper inventory to meet demand or to ask specific questions about their products or stores. Armed with this data, retailers can improve demand planning, inventory management, supply chain optimization, and even marketing.

2. Internal tools

A company’s internal tools (and the workflows built around those tools) can benefit from embedded analytics, too. Consider, for example, a loan broaker’s CRM. This solution should streamline business functions, including analytics, so that brokers can spend more time building relationships with clients. However, it’s important to know that analysts aren’t a technical audience, they need a clean interface with relevant embedded analytics so they can make decisions fast without switching between their CRM and BI application.

This was the case for Australia’s Loan Market Group. By embedding ThoughtSpot into their CRM, they were able to seamlessly and securely integrate their cloud data into their broker’s workflow. Embedded analytics allowed Loan Market Group to increase their broker's access to data and improve decision-making across their front-line workers.

“The slick search-based interface makes it simple for our brokers to answer questions themselves in addition to the prepackaged Liveboards we are shipping with MyCRM, We knew we had found the key to dramatically accelerating our time to market for a seriously sticky and interactive version of the product.”

Santiago Murisengo, Product Manager at Loan Market Group

3. Within a product

Modern businesses who build products with embedded analytics are able to leverage powerful data for a better, more customizable user experience. Users can explore data within the product through simple, familiar interfaces, and implement those insights to better leverage the product. This also creates opportunities for organizations to monetize their data.

Consider MDaudit. By embedding ThoughtSpot into its flagship revenue integrity software platform, executive users were empowered to find strategic insights without needing to leave the product. With ThoughtSpot Embedded, MDaudit got to market 10x faster. Even better, they have seen a 50% increase in user growth from 2021 to 2022. 

Here’s what Ritesh Ramesh, CEO at MDaudit, has to say about ThoughtSpot Embedded: 

1. ThoughtSpot

When it comes to embedded analytics tools, ThoughtSpot Embedded is the go-to choice for the world's most innovative companies.ThoughtSpot delivers decision-ready insights that allow you to drive better outcomes for your business, customers, partners—or any other external stakeholders.

With ThoughtSpot Embedded, you can easily embed conversational AI and agentic analytics experiences into your apps, portals, and products, creating new revenue streams and a faster time-to-market for your business. With ThoughtSpot Embedded Developer SDKs, you can ship scalable, tested, and fully customized analytics experiences—without compromising speed or security. 

Core features: 

• Low-code interface: Infuse ThoughtSpot’s AI-powered analytics into your web and mobile applications with just a few lines of code.

• A range of embed options: Choose whether you want to embed certain components—like the conversational AI experience, entire dashboards, single visualizations—or the full capabilities of the platform.

• Custom white labeling: Create on-brand, personalized data experiences for your customers and partners with multiple customization options.

• Enterprise-ready SDKs: Access a full range of programmatic capabilities to manage and maintain your embedded deployment. 

• Integrated developer playground: Give your developers the ability to prototype and preview workflows directly within the platform.

• AI-driven analytics: Empower users to find insights from their data faster with Spotter, interactive Liveboards, and AI Highlights. 

• Seamless integration: Connect your data from various sources, including cloud databases and other business tools. This powerful integration enables you to extend their platform’s value without requiring substantial resources.

Experience for yourself how ThoughtSpot Embedded provides a real-time, self-service analytics experience for your users—schedule your demo today.

2. Looker Embedded

Looker is Google’s embedded analytics platform that supports integrating advanced visualizations and dashboards into applications. However, the platform does present users with certain challenges. For example, LookML, Looker’s data modeling language, has a steep learning curve, which can hinder business users from fully utilizing the platform's capabilities. Moreover, performance issues and limited customization options may impact the overall user experience.

Core features:

• Dashboards and reporting: Dashboards can be embedded into applications or shared with stakeholders.

• Integration with Google Workspace: As part of Google Cloud, Looker integrates with Google Workspace tools like Google Sheets, BigQuery, and Drive.

• Version control: Git integration and version control capabilities for managing embedded deployments.

3. Sisense

Sisense is another player in the market that enables businesses to embed analytics into their applications. It provides capabilities, such as data integration, visualization, reporting, and data modeling. While it offers some low-code functionalities, it is critical to know that embedding dashboards often requires significant development effort. Cube mapping is another concern, particularly when managing complex data models or integrating data from multiple sources. 

Core features:

• Multiple data connectors: Supports integration with data sources, including cloud-based and on-premise databases, APIs, and third-party applications. 

• UI customization: Offers low-code capabilities to help users customize the look and feel of embedded content.

• Data transformation: Allows users to prepare and check data for inconsistencies and missing values, ensuring it is in the right format for analysis.

4. Power BI Embedded

Power BI provides an embedded analytics solution for integrating data visualizations within applications, especially for businesses already using Microsoft products. Although Power BI Embedded excels in dashboard aesthetics, it can be quite challenging for users to understand the entire suite of advanced capabilities. Mastering the platform requires a strong analytical background and a complicated interface restricts dashboard customization. Additionally, the pricing model is quite complex and can become expensive as usage scales. 

Core features:

• Custom-built visuals: Allows businesses to embed custom visuals and dashboards into applications, websites, and other portals. 

• Integration with Microsoft products:  Connectivity with other Microsoft products such as Azure, Dynamics 365, and Office 365. 

• Data transformation: Power Query for data cleaning, shaping, and transformation.

If you’re not providing embedded analytics to your customers, you’re likely leaving revenue-driving opportunities on the table. In fact, almost half (44%) of PLA survey respondents think that embedded analytics will boost their revenue. So what are you waiting for? Learn more about how ThoughtSpot helps businesses build interactive analytics apps, and start your free trial today.