Tuesday, September 6, 2016

Thoughts On Market Research Data Integration Approaches

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

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 
strategy.

Parts of this entry were originally published under “A waste of time and money” on Research Live.com.

Blueocean Market 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 www.blueoceanmi.com.

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