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Course Description

About The Course

Customer analytics is the process of identifying the behavior of customers based on their transactions and interaction through various channels. Customer analytics involves developing customer segments based on their behavior similarity, building RFM (Recency, Frequency, Monetary) models, identifying the life time value of the customer. Insights which come out of the customer segments and models built will help in building the right services to various customer segments and personalized services to high profile customers. Customer analytics also include identifying the potential customers who might churn out which can help in taking proactive actions to retain the customer.

Some of the areas where customer analytics are extensively used are

Retail industry to understand customer purchasing behavior and how to use the purchasing pattern for cross and up sell

  • Financial industry to understand customer life time value, churn analysis etc. and provide personalized services
  • Telecom industry to understand the customer usage behavior and provide bundled packages and other incentives to increase the revenues and reduce customer churn

Additionally customer experience analytics includes identifying the behavior of the overall customer behavior and take insights in building the best products which caters to the needs of different customer segments.

Are you interested in providing solutions to increase the customer experience by understand the behavior of the customer based on the customer transaction data, are you passionate in building products by understanding customer preferences, is your overall objective is to increase the revenue and retain the valuable customers then customer analytics is the right area which you need to focus on.

We provide customer analytics training covering customer segmentation, web analytics, and customer churn management etc. using real time examples with the support of widely used industry tool R.

Course Curriculum

  • MeXL (Marketing Engineering for Excel)
  • Voice of the Customer / Customer Co-Creation
  • Data for Segmentation
  • Managing “Voice of the Customer”Data
  • The Cluster Analysis + Discriminant Analysis Approach
  • Advanced Issues in Segmentation
  • Rationale for Segment Targeting
  • The GE/McKinsey Portfolio Matrix
  • Segmentation using MeXL
  • Analytics for Perceptual Mapping and Product Positioning
  • Product Positioning
  • Relevance of Mapping for Product Positioning
  • Preference Mapping
  • Incorporating Preferences in Perceptual Mapping
  • Advanced Issues in Preference Mapping
  • Perceptual Mapping using MeXL
  • Analytics for Product/Service Design
  • The Relevance of Trade-off Approaches
  • Conjoint Analysis
  • Approaches to Conjoint Analysis
  • Conjoint Analysis using MeXL
  • Complete Conjoint Analysis
  • Interpreting Conjoint Results
  • Optimizing Design using Conjoint Results
  • Analytics for Tracking Customer Growth
  • Application of Bass Model using MeXL
  • Framework to choose among different digital media options
  • Emerging display advertising ecosystem (e.g. ad exchanges bidding) and Retargeting and real time —-bidding) and Retargeting
  • Decision Analytics for real time and targeted display advertising
  • Using Experiments to Optimize Value of Digital Media
  • An introduction to experiments. Why do we need them?
  • Using Logistic Regressions
  • Experiment Design for E-retailing
  • Challenges in selling focal products and their accessories
  • Using multivariate regressions to measure effectiveness of product videos for e-retail
  • Analytics of Multivariate Experiments
  • Testing digital media e.g. websites
  • Experiments with large number of factors
  • Analytics of User Generated Content
  • Text and sentiment analytics
  • Designing effective rating mechanisms
  • Mining positive and negative opinions and assigning their impact for improving business outcomes
  • New Digital Business Models
  • Open innovation, emerging principles and key learnings in crowdfunding
  • Fundamentals of search engine marketing, web analytics,and digital advertising
  • Application of multivariate regression on sponsored search advertising case
  • Digital marketing attribution
  • Fundamentals of social media (Paid, earned and owned media)
  • How are businesses adopting social media: Discussion of Ford Fiesta case
  • Social listening and text analytics
  • Painting the mobile landscape
  • Discussion of mobile analytics
  • Application of multivariate regression on mobile services adoption case

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ExcelR is a training and consulting firm with its global headquarters in Houston, Texas, USA. Alongside to catering to the tailored needs of students, professionals, corporates and educational institutions across multiple locations, ExcelR opened its offices in multiple strategic locations such as Australia, Malaysia for the ASEAN market, Canada, UK, Romania taking into account the Eastern Europe and South Africa. In addition to these offices, ExcelR believes in building and nurturing future entrepreneurs through its Franchise verticals and hence has awarded in excess of 30 franchises across the globe. This ensures that our quality education and related services reach out to all corners of the world. Furthermore, this resonates with our global strategy of catering to the needs of bridging the gap between the industry and academia globally.

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