The marketing research world has long been dominated by quantitative researchers. Quant had the large teams and gave the final reports, but a change is underfoot. Clients are now demanding deeper insights and breakthrough innovations and, thus, the skills of the qualitative researcher are in big demand.
But the qual paradigm has changed, too. It is no longer just in-person focus groups, central location tests (CLTs) and in depth interviews (IDIs). Technology has enabled insights to be delivered at scale. “Mass qual” is one of the new buzz phrases; it represents a new direction that has qualitative researchers drawing much larger sample sizes and even starting to use statistics such as significance testing, where numbers had historically only been part of the quant world.
So what has changed? Online focus group technology has improved and it is a growing segment. Clients are doing fewer in-person focus groups in favor of more and larger groups online in order to reach more consumers faster and cheaper. These new technologies allow larger groups to answer survey questions along with the typical qual interactions. The results generate data tables and the need for data analysis, which is something new for the qualitative researcher.
On the quant side, panel companies have been talking themselves hoarse about the need to change surveys. They are too repetitive, too long, too boring and younger people are increasingly unwilling to do them. In addition, people are not turning on their computers at home as much and instead answering surveys on their mobile phones. This shift places restrictions on survey design and programming. We have an engagement problem – respondents are keen to have their opinions heard, yet they do not find surveys to be enjoyable. Surveys need more than just a facelift; they need to be completely re-thought.
Respondents are keen to have their opinions heard, yet they do not find surveys to be enjoyable. Surveys need more than just a facelift; they need to be completely re-thought
We need to find new ways to interview respondents. Those new ways need to better resemble a two way conversation where we are using technology to listen and ask questions and allowing the respondent to direct the interview. A major and consistent criticism of quantitative research over the years has been that many surveys lead the respondent based on the types of questions asked. Simultaneously, with the growth in self-serve platforms, many surveys are not designed with the professional rigor we had a few years ago.
In the qualitative market, there has long been conflict between the value of observation skills that can lead to deep insights versus the need to ensure that the feelings and behaviors of the few can be generalized to the many. While the new technologies provide the opportunity to efficiently interview much larger samples, there is a concern that some of the observational art is lost in the process.
So, the quant geeks need the outspoken qual folks to help them connect with respondents and the qual people need the quant geeks to teach them how to handle data. It seems like a perfect marriage.
The quant geeks need the outspoken qual folks to help them connect with respondents and the qual people need the quant geeks to teach them how to handle data
The Yin and Yang of Research
Corporate researchers are finding that, while traditional quantitative results are well-trusted within their organizations, executives are pushing to capture the voice of the consumer to back up these findings. Being able to support survey results by integrating consumer quotations directly from related qualitative research lends even more strength to one’s conclusions . . . and garners high visibility for the research department among executives.
Some of the new technologies coming into prominence are neuroscience, facial recognition, sentiment analysis, virtual reality and, of great importance – video technology. Qualitative researchers have had a longer history with these technologies. They were typically pioneered in central location testing facilities and have only recently been extended to the online survey world. Video is a good example of a technology that has been used for decades by qualitative researchers to help them explain consumer issues in their own words. But now, this capability can be added to online surveys and quantitative researchers will find themselves increasingly challenged to analyze this soft data.
Altering the Qual and Quant Paradigms
There is another change underfoot. If we design surveys so that respondents can self-direct and choose from a variety of topics related to a research issue, we might start the research process with a mass qual exercise. Then, based on the results, we can select certain topics to explore in more detail, perhaps through the re-contact of a subset of those respondents. Essentially, first the qual then the quant paradigm is turned on its head.
Time Compression: No Time for “First Qual, Then Quant”
Self-serve research capabilities have expanded the marketing research universe beyond the control of researchers. The rapid growth of online communities over the past decade has helped to create this belief that research can be done very quickly. Many companies operate client communities that can be used to quickly assess product ideas or other topics that can come from a range of departments within the company. Both sides of the qual/quant divide have typically viewed research communities as “quick and dirty” – aka amateur level. However, the rapid growth of communities has shown clients that quick, cost-effective, self-serve research is possible. Clients do not understand why professional researchers have challenges meeting their needs the way that community managers can.
Agile research has been offered as a solution to accelerate the research process through an iterative approach to insights generation. Agile solutions cover everything from one-on-one interviews to large sample, size-short surveys. The key is to use the technology to quickly put brief research topics into the field, then take the findings and return in a week or less with revised topics based on those findings. In an agile research world, there are no qual or quant specialists; there are just researchers working in partnership with their clients to leverage technology for fast, cost-effective research insights.
Of course, not all research issues can be boiled down to the short surveys or quick discussion forums used by community or agile research practitioners. One thing is clear: long, boring surveys need to change because they no longer provide quality data, especially when completed on a mobile device. We do not think the solution is to merely ask fewer questions, either. We think the solution is to re-think the purpose of the survey. We need to set our goals higher. We need to leverage the strengths of both qualitative researchers and quantitative researchers to create large scale insights generation that can leverage technology and automation to enable fast design and interpretation of the data while at the same time making the process enjoyable for the research participant.
We have been testing some new ways to bring a more human element to the research work that we do as marketing researchers. We are particularly impressed by the new capabilities offered by a range of video research technology platforms. Companies such as 20|20, Living Lens, Voxpopme, 24Tru and Big Sofa offer platforms to manage and process video captured for research purposes. These platforms enable the rapid processing of videos to provide filtering of content by topic, demographics or based on how respondents answered close-ended survey questions. This video data can be quickly transcribed and translated and video collages created according to specific user interests.
We have also been exploring the use of video capture as a way to replace open-ended questions on large scale quantitative studies. The respondent input is much more extensive and much richer than typed answers and, we feel, provides a better overall result. However, this type of data requires different skill sets to analyze; it requires the keen eye of a qual researcher.
Studies genuinely benefit from pulling aspects from both quantitative and qualitative fields. Here are some additional examples:
Consumers were asked to evaluate several options of a product and select the most preferred within a quantitative survey; we then asked a small portion of participants to instantly join a live, one-on-one chat to dig deeper into the reasons behind their top selection. We were able to gather quantitative results and instantaneously dig into some of those results on-the-spot rather than only having one or the other or having to wait to collect each piece through re-contacting survey respondents.
The ability to quickly test messaging or creatives is also enhanced by using an online platform where consumers can instantly view content, answer questions and provide feedback, allowing for quick implementation of changes for re-evaluation. Tools like heat-mapping can be used where participants can indicate things they like, don’t like or find confusing within the content, and you can evaluate the strengths and weaknesses of your creatives based on their collective feedback.
If you need to conduct some exploratory research before performing a more in-depth study, online platforms are certainly the most cost-effective method because you spend only a short amount of time discussing things online and then hone the focus of the more formal study based on those results. One such instance involved a company wanting to float some specific ideas past consumers but also wanting consumers to provide their own ideas through a discussion board. This approach helped the company narrow down their ideas to test within a more structured, quantitative research study as well as add in the consumer-driven ideas derived from the discussion board.
So we hope that you can see the necessity of a marriage of quant and qual. While it may not have been love at first sight, perhaps a marriage based on convenience can still be good and be one that will produce a new generation of researchers that possess keen observation skills and data analysis skills in equal measure.