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Why market research and web analytics are complementary

Why market research and web analytics are complementary

Why market research and web analytics are complementary and should be treated as such

Written by Marieke Eskes – February 7, 2018

Hidden messages behind numbers

Since my childhood I was fascinated by puzzling; the fascination for numbers which can bring you so much more than you see at first glance.  One of my hobbies is still solving those Japanese puzzles.  The numbers at the start of the axes represent the connecting blocks that should be colored.  So, number 15 at the horizontal top row means that 15 connecting blocks should be colored. However, you do not know exactly where the 15 blocks are located.  And that is where the puzzling comes in. Finding the story behind numbers is the red line in my career path.

My journey

During high school, mathematics and economics were some of my best subjects. Though, after graduating high school, my idealism made me go and study International Development; my goal was to find out how to make the world a better place.  However, during my studies I was again drawn to numbers and followed courses like statistics and economics.  This made me decide to start working in market research.  A discipline where my fascination for numbers and statistics could be combined with my interest for observing human behavior.

Market research

Market research tries to answer questions like ‘why do clients behave like they do?’ and ‘what do they think of my product or my advertisement? The difficulty with market research is that market researchers always work with a sample, which is only a part of the total population.  Market researchers are almost never able to collect data concerning the whole population. Simply, because it is time consuming and because not everyone in the population is able or wants to join research.  Because research studies only a small part of the population, the art of market research is to find correlations between variables which can be generalized to the total population. And therefore, a sample is needed which is a good representation of the whole population.  Because market researchers are working with just a small representation of the population they are always conscious about which part of their population they are observing and which part of the population they are not studying.  To correct for this, they use weighting methods.  Assume a particular research aims to grab the political opinion of the whole Dutch population however, the sample contains 2 times more women than men.  A logical consequence is that the votes of men should have a larger weight in the calculations.



Those experiences with sample data, statistical analysis and weighting could be very useful for web analytics as well. Simply, because if predictions or models based on web data are made, all those three things apply.  You need to know, based on which population predictions are being made, what sample do you use and should weighting be applied to be able to make good predictions and models.

More to offer

Besides the experience of doing statistical analysis, applying weighting and using sample data, market research can offer web analytics something else.  Market research can offer context to behavior which is measured by web analytics.  Web analytics provides answers to questions like: what do customers/potential customers do online?  Which customer journey do they follow? Where does the journey start and where does it end?  Market research can provide context to this behavior; why are customers acting like they do and what is the explanation of the choices they make during their journey.  It can provide a deeper understanding of customers’ behavior.


In a lot of businesses, market research and web analytics are two completely different departments within the company.  Both departments have their own scope and their own projects and their own questions to answer.  But they aim at the same goal; improving the understanding of their client.

OnMarc tries to bring those two disciplines together by making data integration possible with third parties who collect data through market research. Visitors of a website are asked for their opinion on particular services on the website or on other offline services.  This makes it possible to combine market research and web analytics endless because questions on what customers do and why they follow their path can both be answered.

So, there is a lot of potential to combine these two disciplines.  They can strengthen each other, provide each other with information and create a complete picture of their customer.  I see it as my own challenge but also as one of OnMarcs challenges to bring these worlds together.

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