predictive analytics webinar

In today’s data-driven world, we’ve become accustomed to companies predicting what we need even before we think we need them. A purchase on Amazon will immediately suggest other products that might be of interest. Similarly, Netflix can predict the type of movies that you might enjoy based on your previous TV watching habits. Companies such as Netflix and Amazon take advantage of predictive and prescriptive analytics to increase customer engagement and sales.

How do we use the concepts of predictive analytics to improve service levels, reduce inventory costs, and tap into additional business opportunities; especially as you move further up in the supply chain?  

The webinar: “How to Use Predictive Analytics to Drive Sales & Delight Your Customers,” hosted on Wednesday, April 12, 2017, from 11 am -12 pm EST by Arkieva COO – Sujit Singh – discusses practical examples of how you can use predictive analytics to uncover additional sales opportunities.

Key Discussions on Predictive Analytics Include:

  • How Upstream manufacturers can reduce inventory levels using data they have right now.
  • How to use customer order patterns to create additional sales opportunities and drive revenue.
  • How to deliver a better customer experience using data-driven proactive ordering processes.
  • Simple B2B Demand Generation & Shaping implementation techniques that will help you reduce inventory levels drive sales, and build customer loyalty

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About Sujit Singh

Sujit Singh is the Chief Operating Officer at Arkieva. Sujit is a recognized subject matter expert in demand planning, forecasting, and Sales and Operations Planning (S&OP). He is a certified fellow in production and inventory management (CFPIM) and a certified supply chain professional (CSCP) by APICS, the Association for Operations Management. In 2010, Sujit was named as a “Pro-to-Know” by Supply and Demand Chain Executive Magazine. His industry experience includes work in the semiconductor, chemicals, and glass (industrial and commercial) industries.