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Price Discovery Techniques for e-commerce Stores & R Google Analytics

Event Date: 22/04/2015

Event Time: 08:30 PM IST

Education Level: Beginner Level

Who is it for:  

CMO, CEO, Director of Web Analytics, Sr. Web Analyst, Digital Marketing Manager

About This Webinar

E-commerce as a business has four main drivers: users, conversion rate, avg. product price & quantity.

Traditionally, most of the focus has been on getting more users to the site or to some extent converting them to buy something. This leads to a huge opportunity that exists for optimization of the Price component within the avg. order value.

This presentation is a walk-through of techniques of conjoint analysis & regression analysis to help e-commerce stores identify products for which the price could be improved.

Key Takeaway Points

In this 45 minute informative session you’ll learn how to:

Introduction to 4 Different Quantitative Revenue Drivers
Why Focus on Pricing as a Lever to Drive More Revenue
How to Identify Products which Consumers are willing to pay higher prices using Conjoint Analysis & Product Demand Index
Why Use R to solve complex business problems and 3 Real Life Case Studies


Ravi Pathak

Ravi is the co-founder of Tatvic and an expert at managing different web analytics tools. He actively works on conversion optimization projects to improve conversion rate and test newer hypothesis with e-commerce companies. He is also an expert at R, SPSS & predictive modeling for web analytics data. He has worked intensively on Omniture & Google Analytics to help clients generate value out of the web analytics data.

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