CMRP Overview

Structure of the Comprehensive Marketing Research Examination (CMRE)
The CMRE consists of two parts of 3.5 hours each. The passing mark for each part is 65%. Both parts must receive at least 65% to pass the Exam.

Types of questions
The examination includes the following three types of questions:

Market Research Designation

CMRP

The CMRP (Certified Marketing Research Professional designation) or PARM (Professionnel agréé en recherche marketing) was introduced to further MRIA’s goal of raising the level of professionalism within the marketing research industry.

Obtaining the CMRP designation signifies a high level of knowledge and capability in marketing research theory and practice, and adherence to rigorous ethical standards set out in MRIA’s Code of Conduct and Good Practice.

By achieving the CMRP designation you:

First step towards social media analytics

Expectedly, insights from social media and online communities are increasingly becoming imperative to device close loop marketing. According to Nielsen, an average american spends ~10 minutes a day on facebook alone. However, with this opportunity comes challenge of analyzing tens and thousands of blogs posted every day.

One needs systematic and targeted approach in collecting, synthesizing, filtering, and analyzing social media data. Although we are still catching up on different techniques, there are several tested approaches – from very basic to complex algorithm based techniques. Naive users can simply start by using free tools. One of the tool I found interesting and useful is Tweet Feel (http://www.tweetfeel.com/). This tool is developed by Conversition company that specializes in social media analysis. Worth looking at this tool!

 

Key Driver Analysis

I was fascinated by statistical innovation’s new offering on key driver analysis. Throughout these years I have used regression and perceptual maps to perform and present key driver analysis. Considering the variable type we use and type of market research data, regression often does not yield strong results explaining cause and effect relationship. However, the new tool from statistical innovations – XLSTAT-CCR seems very promising and provides functionalities to transform data, particularly ability to deal with multicolinearity due to correlated predictors effectively even with high dimensional data (more variables than cases).

Has anyone had opportunity to use this tool?

Link to statistical innovation tool.

GRIT Research Industry Outlook

2011 GRIT report concludes no major surprises. Social media analytics and text analytics are top two paradigm shifting waves. Key conclusions: