Embedded Analytics

Embedded analytics has evolved significantly, enabling organizations to enhance user experience, streamline workflows, and drive data-informed decisions. Let's delve deeper into the tools used and real-world case studies across various industries to provide a more comprehensive view.

Essential Tools & Platforms for Embedded Analytics:

Several tools and platforms offer embedded analytics capabilities, allowing organizations to integrate robust data analysis features directly into their applications.

1. Tableau Embedded Analytics:

• Features: Interactive dashboards, drag-and-drop data visualization, customizable reports, and AI-driven analytics.
• Use: Enables developers to embed Tableau's analytics directly into their applications or websites.
• Integration: API-based integration with various systems (CRMs, ERPs, etc.) for seamless user experience.
• Case Study: JetBlue AirwaysScenario: JetBlue uses embedded Tableau analytics within its operations platform to monitor real-time performance data such as flight delays, crew scheduling, and maintenance needs.Outcome: Reduced operational disruptions by providing real-time insights, resulting in improved customer satisfaction and efficient resource management.

2. Power BI Embedded:

• Features: Customizable reports, natural language queries, AI-driven insights, and integration with Microsoft products.
• Use: Embedding Power BI dashboards and reports into apps, websites, and portals.
• Integration: Azure services, Microsoft apps like Dynamics 365, Office 365, and external data sources.
• Case Study: Milliman (Insurance)Scenario: Milliman, an actuarial consulting firm, uses Power BI embedded analytics to create customizable insurance dashboards for its clients.Outcome: Clients can access real-time insurance risk data, generate on-demand reports, and forecast trends, improving decision-making in risk management.

3. Looker (Google Cloud):

• Features: Real-time data exploration, self-service analytics, and advanced visualizations. Looker integrates deeply with the underlying data model, providing rich context to the user.
• Use Embedding analytics within web-based applications, SaaS platforms, and internal tools.
• Integration: Built-in connectors for Google Cloud, SQL databases, and third-party data sources.
• Case Study: GoCardless (FinTech)Scenario: GoCardless embedded Looker into its payment platform to provide customers real-time payment data and insights into failed transactions and payment timelines.Outcome: Enhanced customer experience by delivering actionable insights into payment behaviour and improving the success rate of transactions.

4. Qlik Sense:

• Features: Self-service analytics, augmented intelligence, and dynamic reporting. Qlik provides robust APIs for deep embedding of analytics into applications.
• Use: Allows businesses to embed analytics into their core systems, web apps, or mobile apps for interactive data exploration.
• Integration: Works with cloud environments, enterprise systems, and custom-built applications.
• Case Study: Hertz (Car Rental Industry)Scenario: Hertz embedded Qlik analytics to monitor vehicle maintenance, fleet availability, and customer usage patterns across its global operations—outcome: Reduced vehicle downtime, optimized fleet management, and increased customer satisfaction through real-time operational insights.

5. Sisense:

• Features: API-driven analytics, machine learning integration, interactive dashboards, and customizable user experiences.
• Use Embeds data visualizations and analytics into internal or customer-facing applications, allowing non-technical users to leverage advanced analytics.
• Integration: Cloud and on-premise systems, such as Salesforce, Snowflake, and AWS.
• Case Study: GE AviationScenario: GE Aviation uses Sisense to embed analytics within their engine maintenance software, providing airlines with real-time diagnostics and predictive maintenance insights.Outcome: Airlines reduce unscheduled maintenance and downtime by leveraging embedded predictive analytics, enhancing operational efficiency.

6. Domo:

• Features: Real-time data monitoring, customizable dashboards, machine learning models, and AI-driven insights.
• Use: It allows businesses to embed data analytics and visualizations into their apps and internal systems.
• Integration: Connects to over 1,000 data sources, including SQL, SaaS apps, and spreadsheets.
• Case Study: DHL (Logistics)Scenario: DHL embedded Domo analytics into their supply chain management system to track real-time shipping metrics, route efficiency, and customer delivery performance—outcome: Improved delivery accuracy, reduced operational bottlenecks, and increased customer transparency.

Case Studies and Use Cases by Industry:

1. Healthcare:

• Tool: Tableau
• Case Study: Seattle Children's HospitalScenario: The hospital uses embedded analytics to track patient care metrics and operational performance across departments.Outcome: Reduced patient wait times, optimized resource allocation, and improved overall care quality through real-time performance tracking.
• Use Case: Hospitals embed analytics to monitor bed occupancy, patient discharge rates, and infection control measures in real-time.

2. Financial Services:

• Tool: Power BI Embedded
• Case Study: Metro BankScenario: Metro Bank implemented embedded analytics to provide real-time dashboards for customer service teams, showing account activity, loan statuses, and risk exposure.Outcome: Faster customer service response times and improved client engagement through better data visibility.
• Use Case: Financial institutions embed analytics into their CRM to give loan officers real-time risk assessments and customer profitability insights.

3. Retail & E-Commerce:

• Tool: Looker
• Case Study: The RealReal (Luxury Consignment)Scenario: The RealReal embedded Looker analytics into its platform, enabling sellers to view sales performance metrics and customer engagement data.Outcome: Improved seller decision-making and more efficient inventory management based on real-time sales data.
• Use Case: Retailers embed analytics into e-commerce platforms to track product performance, customer behaviour, and inventory levels.

4. Manufacturing:

• Tool: Qlik Sense
• Case Study: Harley-DavidsonScenario: Harley-Davidson embedded Qlik analytics in its manufacturing system to track production efficiency and quality control—outcome: Reduced production time by 25% and increased operational efficiency through real-time monitoring.
• Use Case: Manufacturers embed analytics into production systems to monitor equipment performance, track downtime, and ensure quality compliance.

5. Education:

• Tool: Sisense
• Case Study: University of California Scenario: The university embedded Sisense analytics to track student engagement, academic performance, and retention rates—outcome: Increased student retention by identifying at-risk students early, leading to targeted interventions.
• Use Case: Embedding analytics into learning management systems (LMS) to monitor student performance and engagement.

Benefits of Embedded Analytics:

• Improved User Experience: Embedding analytics enhances user experience by providing seamless access to insights within their workflows.
• Real-Time Decision-Making: Real-time dashboards and analytics enable organizations to respond swiftly to changing business conditions.
• Customization: Users can personalize dashboards and reports to meet their needs, improving decision accuracy.
• Cost Efficiency: Reduces the need for separate BI tools, minimizing costs and user learning curve.
• Scalability: Embedded analytics can scale with business needs, growing alongside the organization's requirements for data insights.

Embedded analytics empowers businesses across sectors to leverage data in a more integrated, real-time, and user-friendly manner. With the right tools, organizations can transform data into actionable insights directly within their workflows, improving efficiency, decision-making, and overall performance.