Global Retail eCommerce sales are expected to reach $6.5 trillion by 2023. To gain from this growth, eCommerce businesses will need the competitive advantage that comes from on-demand access to the most relevant and actionable insights on their category, product, suppliers, consumers, channels and end-to-end supply chain infrastructure.

Course5 Discovery, an AI-powered Augmented Analytics solution, uses Intelligent Automation, Retail and CPG-focused Knowledge Graph, Machine Learning (ML) and other AI technologies to drive effective multi-channel marketing, customer experience, dynamic pricing, and hyper-personalization decisions by empowering the eCommerce operational and executive teams with curated, relevant, actionable and humanized insights.

Use Cases

Enhanced Multichannel Marketing & Selling

  • Deep integration of cross-channel campaign data
  • Unified cross-channel campaign analysis
  • Curated and humanized insights for marketers
  • Identify high-target remarketing segments
  • Channel and Consumer specific content recommendations
  • Smarter management of premium inventory
  • Simulation and Spend Optimization

Advanced Personalization

  • Deeper integration of cross-channel interactions
  • Enriched audience profiles & micro-segmentation
  • ML-driven content & product recommendations
  • Automated closed feedback loop
  • Augmented customer experience and expedited conversion journeys
  • Higher customer satisfaction and LTV

Dynamic Pricing

  • Deeper integration of transactional, behavioral, PFV, and supply chain data
  • Hybrid Pricing Optimization Engine (leveraging ML and Business Rules)
  • Smarter demand sensing and highly responsive price adjustments
  • Real-time experimentation
  • Automated closed feedback loop analysis
  • Configurable rules engine for 4P team

Predictive Product Recommendations

  • Smarter blending of behavioral, marketing, transactional & supply chain data
  • Consumer profiling & micro-segmentation
  • Look-alike audience modeling
  • Hybrid product recommendation engine (leveraging ML and Business Rules)
  • Smarter placement of recommendations across multiple devices
  • Automated closed feedback loop analysis
  • Higher percentage of repeat business and profit maximization

Predictive Behavioral Modeling

  • Smarter integration of structured and unstructured data
  • Deeper psychographic profiles of known customers
  • Spot emerging trends and predict unknown customer behavior
  • Predict future interactions with the content and catalog
  • Optimization of cross-device and cross-channel journeys
  • Automated closed feedback loop analysis
  • Better engagement, with higher conversion and CSAT
  • Enable smarter sales and marketing plans

Maximizing the potential of your Customer Communities

  • Deeper integration of engagement, transactional and post-purchase data
  • Enable on-demand engagement and sales bots with-in digital communities
  • Predict member’s intentions and facilitate resonating experience
  • Predict buying signals and drive consumers to the stores
  • Predict signals for lower engagement and community drop-outs
  • Recommend contextual and actionable content to community members
  • Bring the power of ML and AI to drive members up in the value chain