MavenMagnet’s Approach to Market Research Sampling
Historically great effort is put in getting the right sample for market research. A few thousand set-top boxes define the rating of every television show, an exit poll of 1000 voters define who’s going to win a general election and four groups of 15 people define the positioning statement of your favorite products. When millions of people view television, vote in an election and use a particular product, the onus on these select few to collectively make a definitive statement to the general public is gigantic. And that in turn defines the importance of sampling in market research.
When we use social media for market research, one of the great luxuries and benefits is the availability of large amount of data to tap into to draw insights. But on the flip side, it also brings with itself complexity of dealing with large amount of da-ta. Talking about sampling, couple of important things are the sample size and the recruitment process to form the sample.
The sample size for drawing insights in social media is usually much larger as com-pared to what traditional market research uses for the same purpose. But what is the right size? Is it a few thousands? Tens of thousands? More? This is a very inter-esting question, but before answering this, we should touch a bit on the recruitment process.
While traditional market research focuses more on the people participating in the research, we focus more on the information people are sharing. We use this infor-mation to find out what are their viewpoints and opinions. We also consider the people behind the opinions to account for the impact they are creating, but that is done in context to the conversation they are having. This way we make sure that the sample we have gathered is completely random, as it should be in a good market research study.
We do not define the size of sample in our study but let the study results define it. We keep collecting the data and keep analyzing it till patterns start to emerge and clusters start to appear. After doing this for considerable amount of data, the patterns get solidified, themes become clear and insights are apparent. This process of extracting insights from data is just beautiful and the insights are credible as well as actionable to help you make great business decisions.