22 Explorium Case Studies

Company Size

Read 22 Case Studies from real Explorium users sharing their business challenges and results after using Explorium software.

  • Behalf Uses Explorium-sourced Data to Accurately Segment Potential Business Customers, Improving Marketing Efficiency and Streamlining Operations
  • Explorium External Data Platform Gives BlueVine the Tools to Automate Online Processes, Reduce Risk and Fraud, and Enhance KYB Fulfillment
  • Increased Conversion Rates Using Better Data For Retargeting
  • Higher Response Rates With Direct Mail Optimization
  • Enhanced Recommendation Models for Ecommerce
  • Accurate and Fast Anomaly Detection for Anti-Money Laundering
  • GlassesUSA.com Uses Explorium to Grow Revenue by Double Digits
  • GlassesUSA.com Increases ROAS on Facebook Dynamic Ads by 10% with Explorium
  • Lower Cost Per Action With Data Science-Driven Ad Bidding
  • Increase Revenue With Optimized Promotion Scheduling for Retail
  • Idea Financial Partners with Explorium to Prescreen Loan Applicants; Cuts Data Expenses by 50%
  • Drive Smarter Selling Using Enhanced Datasets
  • Smarter Conversion Predictions for Insurance With the Right Data
  • Drive Revenue With Smarter Lead Scoring Using Enhanced Datasets
  • Ecommerce Company Boosts Their Overall Facebook Retargeting Revenues by 43% With Explorium
  • Marketing Firm - Customer Case Study
  • Melio Payments Uses Explorium’s External Data Platform to Improve Conversion Rates and Streamline Operations
  • Improved Fraud Detection Rates Using Dynamic Models For Insurers
  • Online Insurer - Customer Case Study
  • Mitigating Application Fraud Risk for Online Lenders
  • Reduced Lending Risk and Better Repayment Rates With Enhanced Default Risk Models
  • Boosting Debt Repayment With Enriched Data

About Explorium

Explorium offers a new breed of data science platform, fueled by Automated Data and Feature Discovery. By dynamically integrating a company’s internal data with thousands of external sources, the Explorium platform is able to extract the most relevant features and power superior machine learning models.

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