Tag Archives: Data Scientist

Dirty, Sexy Business Intelligence vs. Sober marketing research

Bi Sounds so cool and hot these days, while marketing research has started to sound redundant. Though they both basically achieve the same objective – ‘drive informed decisions’

I have this observation about MR (marketing research) fraternity. Today, when everyone is talking about Big Data – ESOMAR is quiet.

When everyone is opening their wallets to data scientists and business intelligence analysts, we chose to ignore them.

I wonder why that is. Are you guys allergic to money?

Now, let me share my opinion as to how marketing research can benefit from the ‘big data’ trends and what business intelligence can learn from Marketing Research. After all, Marketing Research is one of the oldest, most documented professions in the space of data management and analysis.

Marketing research is one of the oldest, most documented professions in the space of data management and analysis. And BI or Big data cant be successful without learning from it.

The common terms between BI & MR

 Meta Data Management

A hot word, but if you have operated in marketing research you know about the profiling of the data sets at variable levels. Example: This is the opinion of a 30 year old, man, SEC A, living in xyz. They both are the same thing.

 ETL (Export, Transform, Load)

Yet another cool term being used in the field of BI quite often, a similar concept exists in marketing research and it is called data cleaning. The phase, where punched data is processed and sorted out in a ready to analyze format. That is equivalent to ETL in BI.


It is a regular crosstab, where you can manage to go back all the way to raw data to the level where you actually reached to an respondent level variables

Dimensional Data

At the stage of proposal we do sampling and we decide all the profiling variables across which the data will be cross tabbed and the depth of each cross tab. That is equivalent to Dimensional Data in Business Intelligence

Data Governance

Now that is mostly about Data QC management and records management defined by ESOMAR’s guidelines

These are the thoughts at the top of my head, many more to come. And as I learn more about BI, I will update my Marketing research friends on how much potential marketing research has in today’s world of data and analysis.

Till then have fun, by the way don’t forget to check out these articles about the job descriptions of the savvy business intelligence analyst and our marketing researchers. And if you are implementing something cool, please share your experiences with me/us, I am on a roller coaster ride since i started working on the BI tools.


Professional Skills: How and Why Marketing Researchers will lead from front

We are all hearing about Big Data – The question is what is about and how it effects our daily business.

How Big Data is helping Marketing research to lead from front

 So what exactly is Big Data? it is nothing but a large number of complex data coming from multiple sources. From business perspective I don’t agree with the general definition of Big Data.

In my opinion, Big data that is useful for the businesses is the huge amount of semi-processed information coming at a fast pace from multiple internal and external sources.  

Big Data is not about Complex formulas it is about hidden insights

Big Data is not about Complex formulas it is about hidden insights

Is it something we didn’t prepare ourselves for? For experienced staff that has spent years in marketing research and/or information management and/or knowledge management I think they are prepared for it. But the new joiners and the close to retirement staff are the ones where we might experience problems in terms of handling this large amount of data.

As information managers, I suggest we ask the following questions from ourselves before we start to follow the flow.

  • How can we capitalize this information?
  • How can we accelerate our career progression through this data revolution? 

 Capitalizing the information – The Forte of Marketing researchers

  • Apply the 80/20 rule: 20% of the information streams can be translated into actionable business decisions. Focus on that. I usually take a top to bottom approach i.e. which business decision is most important for the organization, what type of information is required to facilitate that, where are the sources of information (have a look at this data to decision value chain)
  • Present the solution not the finding: An eye-catching dashboard is worth a million words, but a jaw dropping solution is worth a promotion. It is about time; we (the data analysts) come out of our shells and start proposing business relevant solutions. Solutions about people, processes or the product. 
  • Simplicity: Simplicity is the key. No matter how complicated the data is and how difficult the solution selling is. If your presentation is not simple enough then you haven’t done your job well. Cut through the chase, get to the point. And get to it as fast as you can. Continue reading