iPOTT improving validity of research


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Market research is one area where mistakes can prove expensive both financially and strategically - financially because it incurs cost and strategically since wrong research questions could generate skewed results. The time in product life cycle when market research is conducted is extremely important as it decides the nature of research questions adopted. Is it during ideation phase, introduction phase, growing markets, mature market stage/ commodity stage or declining phase?

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iPOTT improving validity of research

  1. 1. 6/2/2012 iPOTT Getting you there… Improving Validity of market research As discussed in our previous issue, Market Research involvesGo Goal problem definition, developing a research methodology or an approach to the problem defined, research design, collectionSet, Get, Go… of data from participants, data extraction for analysis and finally reporting.To visit this blog Click here. A good research practice is to collect secondary data andiPOTT being an end to end analyze it completely before analyzing primary research data.provider of innovative and cost This is because primary data addresses the issue at hand,effective services in the areas of unlike secondary data which is used to analyze all the otherknowledge management, sales ‘related’ issues to the problem under concern. To be moreenablement and consulting offers precise, secondary data is mostly related to backgrounda unique and unbiased platform information and can only add to or support the informationfor software product companies that is later generated from primary research.worldwide to reach their targetmarkets Having realized the importance of conducting primary research, it is now critical to understand the nature of primary research to use to achieve an objective. It is therefore www.ipott.om necessary to define the approach towards problem. The info@ipott.com approach adopted may be formulation of research questions, hypothesizing and developing theoretical frameworks or models. This is then tested by developing appropriate research methodology which could be either ‘analytical and quantitative’ or ‘exploratory and qualitative’. A quantitative analysis is not as error prone as qualitative research due to its dependence on numerical values and statistical analysis. The only bias issue with quantitative analysis could be when the sample chosen is erroneous and is not reflective of the population characteristics. The method of obtaining data may be through surveys, experimentation and observation.
  2. 2. A qualitative analysis is extremely beneficial in understandinggroup dynamics and the trends that are emerging in evolvingmarkets. It is important to gain an insight into the changingneeds of people by actually speaking to groups. This could beachieved through focus groups, case studies, in-depthinterviews and word associations. However bias could begenerated in every phase of discourse starting from the wayfocus groups are conducted to the way information isanalyzed.How can this bias and ‘generalisability’ issue be avoided?Studies indicate that best practice in conducting such aresearch is by applying intellectual vigor right from the pointof sampling to applying techniques to analyze non-numericaldata. In practice, it is hard to achieve the ideal sample,because research may sometimes involve hard-to-reachpopulation. But one must try to have a well-selected anddiversified sample to add to validity of data. It has been foundthat mutual trust between researcher and participant enablesa constructive conversation which is helpful in eliciting moreaccurate data. Social theories can be used to provideexplanatory framework and claim that the outcome ofresearch must be applicable to a range of other social groups.If there is a deviation from the social theory and thesecondary research, then the validity of data elicited isquestionable.Studies have indicated that the best way to avoid theresearcher induced bias is by having holistic description andengaging in corroboration through triangulation. According toDenzin, triangulation is of four types data, investigator,methodological and theory triangulation. It is a provenmethod of obtaining data from 2 or 3 different sources to testthe accuracy and validity of data. The overall idea is toovercome intrinsic biases associated with single theory, singlemethod and single user.