Thoughts On Market Research Data Integration Approaches

By: Mike Page,
Blueocean Market Intelligence Vice President – Client Development and

How does the MR industry keep pace with the overall business
intelligence market in terms of developing an integrative approach? While you
could argue that it is a different discipline, it is still the voice of the
consumer within a business, so the data should be simpler to integrate and use.
A better way to think about this is to think about the flow
of information from one channel to the other ‘ specifically from MR to business
intelligence or vice versa. At the Data Matters conference Martin Hayward made
a very important point. He said: ‘We work from what you did outwards to why you
did it.’ Most market research works from questions about why you do things and
try to predict what you will do. Surely within this there is an optimal model
that will help you ask only the most pertinent questions in the most pertinent
way and not waste effort on information that is better sourced elsewhere.
Here are some examples of how an integrative approach can be
more efficient and help to realize the savings that so many people believe are
out there.
Savings from
redundant research

Organize different research under the same platform to
achieve synergy. By combining various product/concept test research, you are
often able to answer new business questions and eliminate funding superfluous
research. Synergy is obtained through combining data: a) from different time
periods (trending) or b) across product/brands/concepts/ business units.
Better insights from
linking different sources of research data

Additional synergy can be captured from across product
linkages as well as trending. As a case in point let’s use chocolate. Across
the board men associate chocolate with comfort; whereas women associate it with
indulgence, which has great implications for how you communicate with them. 
While an individual study may provide the same information about a specific
concept (e.g., a white chocolate with a bitter orange flavor), we would not
know that, in general for women, chocolates are tied to indulgence. With
respect to trending, only by linking and creating a trend line for appeal, will
we know that chocolate has, over the years, consistently lost appeal among men
but not among women.
Research redundancy

We can also think in terms of research redundancy. If we
asked a question within a category ‘ such as customer satisfaction or new
product development ‘ we are building a picture of the consumer that can be
looked at across the surveys, we conduct. For example, how many times have we
ever asked a certain question and how has the context or relevance of that
question changed over time. From our own experience we have databases with over
half a million responses that show no or little change over time. Using this
knowledge in a structured and data-centric way can give us the tools we need to
manage our research process more effectively and ensure we don’t duplicate
efforts in our research or collect information that is perhaps better captured
elsewhere for the sake of it.
Data sharing

There are equally opportunities for data sharing. If many of
the data points that we collect are static, why should data not be shared in a
way that will, while ensuring confidentiality, provide researchers and their
clients with a window on what is genuinely different and what is genuinely
insightful from a research study. For example, if we know that the primary
driver of purchase intent is age, regardless of the product being tested, then
why do we not analyze what we already have to make a better-targeted research
study and avoid duplication of effort?
Linking research data
with other sources of data

For this let’s take an example looking at doctors’
prescription patterns for a new drug. By linking satisfaction and effectiveness
data to prescription data you can provide insights regarding both optimal
quantity of sales calls as well as the quality of messages to a particular
doctor. So if you know that cardiologists tend to write more prescriptions when
the salesperson is able to demonstrate ‘knowledge and competence about the disease
state and product benefits’ whereas the oncologist writes more prescriptions
when the salesperson could show that ‘he/she cared about the physician’s
business practice’. These types of insights lead to better understanding of
what drives volume and share of prescriptions for different drugs.
In conclusion, it is easy to see how an MR strategy that is
not aligned with other business information streams in a seamless way can make
you spend money that you don’t need to. My advice to those who do not believe
this is to conduct an audit to find out where and by what means each piece of
the research puzzle can be best answered, and by what channel, before another
research study is begun.
You’ll be surprised by what you find and how much you can
save with an integrative research 
Parts of this entry
were originally published under ‘A waste of time and money’ on Research

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Intelligence is a global analytics and insights provider that helps
corporations realize a 360-degree view of their customers through data
integration and a multi-disciplinary approach that enables sound, data-driven
business decision. To learn more, visit