Unlock the power of data with our compelling case studies featuring cutting-edge analytics solutions across diverse sectors

Tech:

  • Data Integration: Real-time data integration of product usage and cross-channel CX touchpoints, to enable AI-driven insights and actions for a home security company.

  • Product Engagement: AI models to predict customer behavior, auto-detect key issues, and trigger personalized communication to optimize CX strategies in real-time.

  • Churn Reduction: Reinforcement learning ML model that automatically predicts customers with a high likelihood of attrition by analyzing product usage, financial activity, customer experience (CX), subscription plans, and tenure.

  • Customer Journey Optimization: AI model to predict optimal paths for various customer segments and identify key moments of value throughout the customer journey.

Finance:

  • Dual Risk Model (DRR): A comprehensive system of machine learning models designed for a bank to evaluate the likelihood of loan default and estimate potential losses associated with business loans.

  • Pricing: A B2B simulation pricing tool that evaluates the impact of different pricing strategy schedules on a bank’s clients.

  • Marketing Mix Modeling: Multi-model simulation to guide mutual fund media investment decisions and develop a flexible budget allocation plan that adapts to economic conditions, seasonality, brand health, and competitive spending.

  • Forecasting: Credit Card trend models to forecast open accounts, attrition, redemption rates, and redemption expense based on various sales targets.

Healthcare:

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  • Digital Health Management: Impact Assessment tool to measure improvement in medical utilization and cost outcomes due to engagement with digital health management platform.

  • Treatment Optimization: Mobile app onboarding analytics to evaluate member retention, assess content, measure staff efficiency, and quantify medical utilization and cost savings.

  • Claims Analytics: Datamart for healthcare claims analytics to improve cost efficiencies and optimize treatment flow to support Payer/Provider P&L.

Automotive and Mobility:

  • Online Sales Conversion: Integrate digital activity, CX with offline data and apply machine learning to enhance the digital purchase journey, driving increased engagement and improving sales conversion rates.

  • Sales Offer Optimization: Lift model and offer optimization that provides customer-level recommendations on optimal incentive offers to lift sales and maximize ROI.

  • Purchase Propensity Models: Short-term purchase propensity model for customer lifecycle segmentation and model-based targeting.

  • Customer Loyalty: Loyalty score to determine the level of customer engagement and build a marketing communication strategy to improve sales and market share.

  • Traffic Simulation: Agent-based traffic simulation for a major city to evaluate the impact of autonomous vehicles on congestion and urban mobility.

Retail:

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  • Promotions: SKU category level e-commerce promotion effectiveness analytic strategy for successful post-merger integration of major office supply retailers.

  • Price Elasticity: Comprehensive price elasticity simulation for a retailer to measure the impact of price changes on consumer demand across various product categories.

  • Allocation Optimization: A package volume allocation optimization model for a distributor based on shipping patterns, delivery routes, and package sizes.

Telecommunication:

  • Call Resolution: Voice-to-text analytics to assess customer sentiment and optimize selection criteria for the call resolution program, improving call conversion rates and routing customers to the right representative groups.

  • Subscription Retention: Attrition model, customer retention strategy, and off-promotion pricing for a major telecommunications company.

Insurance:

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  • Chronic Pain Management: Develop a chronic pain management solution based on medical claims and auto accident data to predict the likelihood of spinal injections and surgery.

  • Medical Platform Analytics: Develop a comprehensive database to analyze insurance costs and track trends, enabling comparative analysis across states within the industry.

  • Fraud Detection: Early Warning System to detect potential insurance fraud and litigation risks by analyzing medical claims records, policy information, and demographic data.