The presentation discussed how predictive analytics and decision management can help drive retail success by improving customer engagement, controlling costs, and enabling long-term growth strategies. It highlighted Inkiru's predictive analytics platform for integrating real-time predictive models with operational systems to personalize customer experiences, reduce fraud and optimize operations. Case studies demonstrated benefits like increasing click-through rates by 10% and boosting conversion by 120%. The presentation concluded by encouraging attendees to focus on high-impact decisions and leverage predictive analytics at scale for competitive advantage.

1. Engagement, Loyalty,
James Taylor, CEO
Costs and Growth
Brad Turner, VP Marketing and Driving retail success
Business 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 Customer
Engagement & Loyalty

6. How do I find my most profitable
customers and build deeper
relationships with them?
How can we predict which
products will be most popular
among our regular shoppers?
How can I build stronger customer
loyalty 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 make
operations smooth
and 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 action
Operational
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 that
maintains its effectiveness?
How do I send out
fewer offers and get
more responses?
How do I find out which promotions will
work 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 analytics
Cottage industries don’t scale
Factories do
© Decision Management Solutions, 2013

20. Key Benefits of the Inkiru
Predictive 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 sources
20 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,
maintenance
21 Confidential and Proprietary Information

23. Key Benefits
• Hosts a variety
real-time models
• Allows for multiple
scoring algorithms
to score the same
event
22 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 Abandonment
23 Confidential and Proprietary Information

25. Case Studies
24 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
decisionmanagementsolutions.com
inkiru.com
© Decision Management Solutions, 2013

33. Thank You
James Taylor
james@decisionmanagementsolutions.com
Brad Turner
brad@inkiru.com