Numbers or Letters: The Case for Qualitative Data
You’ve been tasked with developing several recommendations for campaign or product improvements. Quick! Where do you turn first? Often, the default is to focus on quantitative information in your analysis – clicks, impressions, KPIs – numbers that can be easily presented in a graph and can quickly illustrate performance. However, it’s critical not to fall into the numbers trap while forgetting that numbers often need a little help in order to present the whole story. That’s where qualitative data (letters) come in!
Key Benefits of Qualitative Data
Qualitative data – non-numerical data found in surveys, social media platforms, interviews, focus groups, and visuals – provides many benefits and insights for marketing use. First, it is a flexible data source in that it can be gathered with much less structure than is typical of numerical data, for example through unstructured interviews. Moreover, through careful selection of a targeted group of consumers, an interview can help ensure that feedback will be relevant and actionable.
Second, and perhaps more importantly, are the incredibly rich and detailed nuggets of information that can be gleaned from qualitative data-gathering. Consumer opinions and feedback can be highly nuanced and complex, and are often much deeper than what could be obtained from a few simple data points. Harnessing that deeper level of information can provide for myriad ways in which you can refine your brand or product in order to be responsive to that feedback, such as adjusting a price point or modifying a campaign message. These don’t necessarily have to be large changes, but through qualitative approaches, you are able to directly tap into the mind of the consumer and identify even small tweaks that can have a great impact on your project.
Limitations of Qualitative Data
With all that said, there are certainly limitations to qualitative data. Chief among these is that it is generally not possible to project findings from qualitative data analysis out to a larger population. Given the small and highly-targeted samples that are typically used in qualitative methods, it is unlikely that that sample is completely representative of your larger population.
Additionally, qualitative data can sometimes be difficult and time-consuming to roll-up into smaller, more easily digestible messages. For example, every consumer is an individual and, as such, there may be different viewpoints within their responses that you will have to weigh and decide on which you will devote more energy to responding.
Each type of data is extremely valuable and serves a purpose but, ultimately, neither can provide a complete picture independently. Yes, it can sometimes be more labor-intensive to develop and analyze a survey, interview, or focus group as opposed to simply querying data from a database; however, overlaying qualitative data with what you pull from those databases can provide necessary context, helping to illuminate holes in the percentages and volumes, and ensure that your analysis is as complete as possible.
[This post originally appeared on Asking Smarter Questions and is republished with permission.]
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