Embedded Analytics: Use Cases and Benefits

by Ramesh Panuganty, Founder & CEO

Embedded Analytics: Use Cases and Benefits

by Ramesh Panuganty, Founder & CEO

Embedding capabilities within the main workflow helps in maintaining a seamless experience for users. While working in the main application, users can continue their natural flow of performing tasks, without getting distracted or taken away to other places. Embedding analytics within business applications that users use frequently makes analytics easy to access and encourages quick, insight-based actions.

Business users work on complex tasks such as managing financial budgets, reviewing marketing plans, tracking sales leads, or optimizing inventory and resource allocations on a daily basis. These high-priority tasks require updated insights and focused attention for making decisions and initiating actions. With traditional BI, business users are forced to move away from their business applications in search of insights. They have to log in to a separate BI application, perform analysis and get the insights, come back to their main business application, and then take an action. This increases the cognitive load in mentally adjusting to new user interfaces and going back and forth between applications to complete the same task.

Embedded analytics makes analytics an integral part of a user’s daily business activities by eliminating friction and encouraging insight-driven decisions. Analytics capabilities can be embedded in customer-facing websites and web applications, and also in internal organizational portals.

Use cases for embedded analytics

Analytics is no longer seen as a standalone process. Users expect it and demand it as an integrated capability while using modern enterprise applications such as finance and banking platforms, CRM platforms, accounting systems, sales and marketing portals, or project management solutions. Embedded analytics has applications across different industries.


Retail and CPG

Retail organizations use sales and customer management applications to manage products and orders, maintain customer details, track pricing and profitability, and deliver various services to their customers. With embedded analytics, retailers can ask questions in simple language to find out products with high demand, compare sales over different time periods, identify the most profitable stores, and so on. These insights can help them understand customer preferences better, create customized offers, maintain optimum inventory, allocate sales staff as per demand, and manage store operations efficiently. Embedded analytics helps retailers understand not just what changes happened in sales, but also why they changed, which drivers were most influential for the change, and how to act upon the change.

Supply Chain

Organizations use supply chain and logistics management applications to manage data about orders, consignment details, transport vehicles, shipment destinations, and location details. By embedding analytics in these applications, users can track important metrics in real-time such as location, shipment status, driver performance, staff allocation, and so on. Based on insights available within the application itself, they can quickly optimize transport routes, improve warehouse operations, reassign drivers based on availability and demand, and reduce delivery time delays. Embedded analytics helps users assess inventory levels, visualize distribution patterns, and identify areas with most disruptions in the supply chain to plan ahead for ensuring smooth movements.


Healthcare professionals and hospitals use various healthcare applications to maintain patient health records, conduct clinical research and studies, and manage facilities and equipment. With embedded analytics, users can access and explore data from all these applications in a fast, easy, and intuitive manner. In critical situations, getting instant and real-time insights on patient health can help medical professionals mitigate risks and make key decisions confidently without delays. Hospitals can also track occupancy rates and equipment usage to ensure readiness for any emergencies. Embedded analytics can help provide better healthcare experience, increase care quality, improve patient satisfaction, reduce wastage, and manage costs better.


Marketers always have their fingers on the pulse of the market. The digital marketing platforms help marketers manage campaigns, create social media content, track leads and conversions, and pursue customer engagement activities. By embedding analytics in these applications, marketers can track important metrics in real-time such as click-through rates, bounce rates, conversion rate, cost per lead, and so on. Embedded analytics helps them gain clear visibility of customer segments, assess campaign outcomes, improve effectiveness, and learn more about customer preferences to customize their marketing strategies without delays.

Customer Success

Customer relationship managers use CRM applications to maintain details about their customers such as demographics, purchase history, and preferences. With embedded analytics, they can track various customer success metrics such as churn rate, retention and renewal rates, customer lifetime value, and customer satisfaction score. These insights can help them understand customer needs better, track profitably customer segments, create personalized offers, identify cross-sell opportunities, and retain existing customers while targeting new ones.

Benefits of embedded analytics

With embedded analytics, organizations can gain the following benefits to extract more returns from their analytics investments.

1. Self-service analytics

A simple search box embedded in a business application can significantly boost self-service analytics. Users no longer have to depend on experts to get answers to their daily business questions. They can simply type their questions in simple language in their own application and get answers instantly.

2. Easy analytics adoption

Embedded analytics ensure a seamless experience to users. When integrated as a feature within enterprise applications, users find it easy to access and intuitive to use. They find the matching application experience convenient and comfortable. They do not have to learn new systems or familiarize themselves with new interfaces. Their confidence in using analytics increases and improves the overall BI adoption in the organization.

3. Improved productivity

With embedded analytics, users don’t have to navigate between several applications to receive insights. They are able to reach insights faster using a single integrated application and save time. With lesser cognitive load in understanding different interfaces, user can focus better on their tasks, resulting in improved productivity.

4. Better and faster decision making

Embedded analytics enable users to receive insights within the context of their business task. The seamless experience removes a lot of frictions and hesitations users may feel while using analytics and basing their decisions on insights. When users take insight-driven decisions, they minimize the risks and losses due to bad judgement and guesswork. Embedded analytics helps usher in an insight-driven decision making culture within an organization.

5. Increased revenue with real-time insights

Embedded analytics enables users to get real-time insights where they actually need to take important actions, that is, within their enterprise ecosystem itself. This considerably reduces the time-to-insights. Users are always ready with updated business data and insights which helps them convert leads faster, spot deviations and threats sooner, identify new revenue streams, and thereby increase revenue from emerging business opportunities.

6. Quicker deployments

With easy embeddable APIs, organizations can enhance their existing systems with various analytics capabilities, without going through an infrastructure overhaul. They can pick the analytics capabilities according to their requirements for embedding. They no longer have to invest in time-consuming deployments and can get started on analytics soon.

7. Improved ROI

Organizations invest heavily in analytics, but miss out on its advantages due to poor user adoption and reporting backlogs. By simplifying the insight discovery and consumption process, embedded analytics not only increases user adoption but also establishes an insight-driven decision making culture. This saves huge engineering efforts in creating ad hoc reports, saves support costs and helps organizations improve ROI significantly.

Essential capabilities of an embedded analytics platform

Not all analytics platforms are built to be embedded. Analytics leaders must thoroughly consider the embedded analytics capabilities while evaluating analytics platforms.

1. Self-service Intelligent Search

An intelligent search box is equipped with natural language search, search suggestion, ambiguity corrections, and context recognition. These abilities help business users ask their questions in simple language, without learning any syntax or technical details. The embedded search must be intuitive for users to carry out their conversations with enterprise data in a self-service manner, just like they do with a Google search.

2. Decision Intelligence

Decision intelligence makes insights more understandable, relevant, and actionable. Business users want to understand not just “What” metrics changed but also “Why” they changed. Embedded decision intelligence makes exploring the “What” intuitive, identifies the key business drivers and influencers that reveal the “Why”, and simplifies the “How” with impactful data storytelling.

3. Real-time Click-less Insights

Since analytics is embedded in the main business application, it should have to the ability to access real-time data for performing analysis and extracting insights. Business users must receive business headlines and insights as they happen in data in a click-less manner, and not just when they search. This way, as business events unfold, users are in a strong position to take quick actions.

4. Interactive Stories and Visualizations

Embedded analytics must offer audio-visual data storytelling as an important capability. Business users can consume insights better and faster if presented as interesting and engaging data stories. Interactive visualizations, audio narrations, and text summaries not only improves understanding but also encourages users to use analytics more in their day-to-day business.

5. Reporting and Dashboards

Embedded analytics must ensure that business users never have to raise requests or wait for reports. Business users must be empowered to create and share reports and dashboards quickly and easily, without any help or dependency. Interactive dashboards with built-in presentation capabilities save time and efforts while presenting in meetings or sharing with teams.

6. Ease of Embedding and Deployment

Embedded analytics must make integration fast and friction-less for developers using powerful and easy-to-use APIs. Quick deployments and hassle-free interactions can maximize developer productivity, prevent infrastructure overhauls, and help organizations get started with analytics faster in their own ecosystem.

Why organizations are shifting to embedded analytics recently?

The global market for embedded analytics is growing rapidly in the recent years. Organizations are realizing the benefits of embedding analytics and democratizing insights for their employees and customers.

Organizations accumulate substantial data through their enterprise business applications. However, these applications often lack the means to unlock the full value of this data. Learn how MachEye incorporating LLM analytics enables organizations to transform these business apps into valuable 'data apps,' generating actionable insights without any additional setup.

By “residing” within business applications, embedded analytics essentially makes insights available where users need them the most for taking decisions and actions. Organizations can address the needs of their employees and customers better by embedding the required analytics capabilities. For example, a RevOps company offering revenue intelligence to sales teams empowered its users by embedding MachEye’s intelligent search box to ask ad hoc questions about deals, pipelines, and wins in simple natural language.

Organizations can reduce time-to-insights and save significant efforts and costs required to do iterative manual tasks by embedding analytics in their workflows. For example, a digital communications management company reduced time-to-insights by 90% for their customer success managers by embedding MachEye’s analytics capabilities to track product usage and build dynamic reports and dashboard within minutes, instead of hours.

Embedded analytics with MachEye

By offering true self-service capabilities, MachEye’s embedded analytics copilot enables organizations increase user engagement, make products stickier, and encourage adoption of data-driven decision making. MachEye offers powerful and easy-to-use APIs and SDKs to embed various analytics capabilities such as intelligent search, actionable insights, business headlines, dashboards, and charts. With MachEye, users can go beyond knowing “what” happened, to identify the “why” behind business events, and learn “how” to take the right actions. Interactive stories help users consume insights better and faster through audio-visuals. Experience seamless integration, quick deployments, and powerful self-service analytics with MachEye’s embedded analytics.

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