How Should Social Media Be Used In Market Research?
Tuesday, January 24, 2012
There is a lot of debate about how to use social media content in market research and in which category it fits: Quantitative or Qualitative research?
The massive amount of content generated by social media and the proliferation of sentiment analysis tools attempting to quantify it, give the impression that it can be considered quantitative research and thus quantitative analysis methods (e.g. t-testing, regression, etc.) can be applied to it. However, the issues of data accuracy and representativeness have not been solved yet.
Anybody who has done coding of open-ended questions in surveys knows how difficult this is. Finding categories to classify the answers is a very subjective process. To attain some level of objectivity and find categories or codes that accurately reflect the content in these questions, we often need several iterations and different coders to achieve consensus.
In social media, as in surveys, more often than not, people write incomplete and grammatically incorrect sentences, and use irony, sarcasm or humor to convey their meaning. In social media it is even more difficult to discern what people are talking about, as there are no survey questions to filter the information by.
Unfortunately, there is not a good text analytic tool yet that can interpret language nuances as well as a human coder. Sentiment analysis tools still need to be fed with codes and definitions of positive and negative content defined by someone in order to count and classify content.
Linked to data quality is the problem of representativeness of opinions. From customer satisfaction research, we know that people, who decide to provide feedback, are either very happy or very unhappy with the issue they give feedback about. Those who are in the middle often don’t bother to comment.
The level of category involvement also affects representativeness. Not all products command enough attention to be topic of conversation in social media, unless there is something that surprises or annoys the public (e.g. banks imposing debit card fees).
Then there is the issue of how we separate unpaid opinions from unpaid opinions, which are becoming more common.
For the moment, until better text analytic tools allowing more accurate data cleaning and other tools that would help identify who is behind the opinions, are available, I think social media content should be considered as a tool in the qualitative research arsenal to explore and sometimes dig deeper in certain issues. Among its applications, social media content can be used to explore:
- Likes and dislikes about a product, brand or company
- Language used to talk about needs, expectations, barriers
- Problems with products, customer services that need a quick response
- Topics of interest within a product category
- Perceptions about a brand and its competitors
Social media content can be a source of rich insights, but we should be aware of its limitations and do not equal access to large amounts of text to quantitative research.