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Engagement, Loyalty, Costs & Growth - Driving Retail Success with Predictive Analytics and Decision Management
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Engagement, Loyalty, Costs & Growth - Driving Retail Success with Predictive Analytics and Decision Management


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A Decision Management Solutions Webinar - Retailers see tremendous value in business intelligence and real-time analytics as a way to make sense of the vast amount of data they collect. The challenge …

A Decision Management Solutions Webinar - Retailers see tremendous value in business intelligence and real-time analytics as a way to make sense of the vast amount of data they collect. The challenge is determining where to focus their efforts. To succeed in applying analytics, retailers need to understand how predictive analytics and decision management affect real-world decision-making scenarios.

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  • 1. Engagement, Loyalty,James Taylor, CEO Costs and GrowthBrad Turner, VP Marketing and Driving retail successBusiness Development with predictive analytics & decision management @inkriu @decisionmgt #decisionmgt
  • 2. Your presenters James Taylor Brad Turner CEO of Decision VP Marketing and Business Management Solutions Development at Inkiru 20+ years working with 25+ years in technology, clients to improve the way focused on networking and they build systems. cloud-based database © Decision Management Solutions, 2013
  • 3. AGENDA 1 2 Building Customer Engagement & Controlling Costs 3 Driving a Long Term Growth Strategy Loyalty 4 5 6 Key Benefits of Questions and How to Get Inkiru Predictive Answers Started Analytics Platform
  • 4. Staying Competitive Requires Analytics #1 Data #2 Know-how #3 Intelligence © Decision Management Solutions, 2013
  • 5. Building CustomerEngagement & Loyalty
  • 6. How do I find my most profitablecustomers and build deeperrelationships with them? How can we predict which products will be most popular among our regular shoppers?How can I build stronger customerloyalty than my competition? © Decision Management Solutions, 2013
  • 7. Target individuals with analytics © Decision Management Solutions, 2013
  • 8. Personalize every response The best response changes in each situation Target with analytically derived micro segments Personalize messaging and offers Focus predictive analytics on each decision © Decision Management Solutions, 2013
  • 9. Success requires a clear target © Decision Management Solutions, 2013
  • 10. Controlling Costs
  • 11. How can we reduce fraud-related expenses?How can we makeoperations smoothand efficient? How can I use analytics to reduce back-office staffing? © Decision Management Solutions, 2013
  • 12. Break operational ratios with analytics © Decision Management Solutions, 2013
  • 13. Real-time fraud detection Business event Decision latency Action taken © Decision Management Solutions, 2013
  • 14. Predictive analytics drives actionOperational Systems Decision Management Systems link Decision analytics to operational systems Analytic Systems © Decision Management Solutions, 2013
  • 15. Driving a Long Term Growth Strategy
  • 16. How do I build a marketing strategy thatmaintains its effectiveness? How do I send out fewer offers and get more responses?How do I find out which promotions willwork and which will not? © Decision Management Solutions, 2013
  • 17. Maximize LTV in all channels Decision © Decision Management Solutions, 2013
  • 18. Continuously improve decisions © Decision Management Solutions, 2013
  • 19. Industrialize analyticsCottage industries don’t scale Factories do © Decision Management Solutions, 2013
  • 20. Key Benefits of the InkiruPredictive Analytics Platform
  • 21. Key Benefits • Algorithms and response models score transactions in real-time during the customer interaction on your site • Integration with external data sources20 Confidential and Proprietary Information
  • 22. Key Benefits • Simple integration • Data is taken advantage of and utilized during the peak of its shelf life • End-to-end model design, development, deployment, maintenance21 Confidential and Proprietary Information
  • 23. Key Benefits • Hosts a variety real-time models • Allows for multiple scoring algorithms to score the same event22 Confidential and Proprietary Information
  • 24. Use Cases Marketing Merchandising Operational Excellence • Dynamic Ad Campaigns • Product • Fraud/Risk • Improve Customer Recommendations Management Loyalty • Price based Promotions • Inventory Optimization • Offer Customization • Upsell and Cross sell • Payment Optimization • Customer Lifetime • Shopping Cart Value Predictions Abandonment23 Confidential and Proprietary Information
  • 25. Case Studies24 Confidential and Proprietary Information
  • 26. Case Study—Operational Excellence Automated fraud detection lowers loss while raising profits 20% for this social entertainment website.25 Confidential and Proprietary Information
  • 27. Case Study—Marketing Automated email campaign optimization increases click-thru rate 10%.26 Confidential and Proprietary Information
  • 28. Case Study—Merchandising Increased personalization enhances customer experience—boosts first-page conversion 120%27 Confidential and Proprietary Information
  • 29. Questions?
  • 30. Conclusion
  • 31. How to Get Started Focus on key decisions in customer engagement, cost control and growth Drive better decisions with integrated predictive analytics at scale Focus on using predictive analytics in real-time using decision management systems © Decision Management Solutions, 2013
  • 32. Learn More Download the free whitepaper Using Predictive Analytics and Decision Management in Retail Visit us at © Decision Management Solutions, 2013
  • 33. Thank You James Brad Turner