What It Really Means to Gather Online Qual at Scale
In the Market Research world, the terms “big data” and “mass quant” are all too familiar; it is regularly referred to amongst the industry and also commonly used in practice. Mass qual, however, is much less commonly heard of or spoken about, and even less regularly put into practice. I’d even go as far to say the term scares people away, and is something a lot of research professionals actively avoid due to its’ perceived complications and resource consumption. However, in a growing digital age, we are beginning to see increased capability in the world of research which allows us to start to take advantage of qualitative research on a much larger scale.
Currently, the main views of mass qualitative data are that it:
Takes up a lot of time and resource, especially to moderate and analyse
Once you get past a certain number of respondents you begin to gather the same findings and thus the process becomes relatively pointless
The problem here is that we are all looking and talking about “mass qual” in the same way we do with any kind of traditional small-scale qualitative research study, but there are many differences between the two – especially if you want to make a success of gathering online qual at scale.
So, what exactly is mass qual, how does it differ from the traditional qual we are familiar with using, and is it really that useful? Well, for one, yes – it is definitely useful, it just depends what you want to know! Mass qual allows you to explore and create discussions about wider topic-areas, which will help unpick numerous insights; from specific consumer behaviours, needs that are not being met, desires, etc. that you had never thought about before.
Often, with mass qual we would expect the over-arching objective to be particularly different to that we would see in a traditional small-scale qualitative study. By this, I mean the objectives would be less focused in comparison to small-scale qualitative research, and perhaps look to understand a wider topic area at a top-level. Therefore, the objective is more likely to be explorative, which could help guide further research at a more in-depth level, or even just allow you to understand many different behaviours, opinions and attitudes towards multiple topics at a lower-cost level.
The difference between the mass qual approach and the traditional small-scale approach is that we would consider using rather different research methods that would accommodate larger quantities of comments and allow us to better meet these more ‘top-level’ objectives set out. This would be methods such as forum discussions, sentiment-tagged heatmaps, and question boards, that allow time for as many participants as you want to think before giving more in-depth answers to your questions. Other methods like qual-focussed surveys are brilliant too for simplicity’s sake, but it’s easy to get swept up in the quant-focussed analysis and miss out on the rich qual insights up for grabs.
Online research communities are a great way to conduct mass qual in a successful way; online research communities can consist of 1000 people or more and allow you to pose questions and create topical discussions through blogs, polls, etc. It is useful when wanting to explore specific topics and understand people’s behaviours and/or opinions on a broader scale, that can then be used to compliment and help define a more focused and smaller scale qual study to understand the behaviours in more depth. The larger scale community discussions allow you to pinpoint key areas to discuss in more detail and therefore reduces waste of time and resources, as less in-depth analysis is required.
Although I have spoken about the positives of mass qual, it is important to highlight that this is not the approach we should be using for everything. As always, it is important to pick the correct research methods for the business’ needs, but I think we also need to highlight the benefits of mass qual to encourage people to be open to considering using it:
When conducting mass qual there are a few key things to remember:
Don’t over-complicate things – keep it broad, keep it simple; the more complicated, the more time it takes to sieve through everything
Don’t over analyse! Remember, mass qual isn’t the same as a traditional small-scale study so we don’t want to follow the same approach; we want to understand things from a wider point of view and thus an overview is a generally more preferred approach (however this does still depend on the objective, so It may differ!)
Consider using other means to compliment dedicated research community findings – Social media sites such as Facebook, Twitter, LinkedIn, etc. are often great sources of information. With customers and consumers mingling together on one huge platform, it’s easy for brands to interact with people and vice versa; thus, insights can be gathered through the use of social media polls/questions/competitions or even organically though the customer service-side of social media management.
Context is key – finding that all-important balance between understanding the whole picture but not losing sight of the details is key, as both contextual points of view will allow researchers to generate accurate and valuable insights. To find out more about context and mass qual, check out our whitepaper.
Find the right tools for your project – the requirements of each research project will be unique, and so the right combination of tools is a must in order to do your project justice. For instance, some will require the use of social media such as policy changes or branding ideas, but others like new product development or marketing refinement will need the sole focus of a dedicated research panel.
There’s no one right way to conduct mass qual research, but hopefully these guides will act as a good starting point to getting you on your way. The one danger of collating any big data, whether qual or quant, is that you’ll end up conducting the same research and generate the same insights over again. One way in which to keep track of the resources and effort you’re spending, is to make one big data bank accessible to all. Using this bank as a first port of call before conducting research will ensure that any research done is definitely needed, and no resources go to waste.
Maisie utilises her strong project management and research skills to conduct large-scale international research projects. She has an in-depth understanding of consumer behaviour and her competitive nature ensures she always gets the best insight for our clients. You can follow Maisie on Twitter.