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Quant: Not just a numbers game


Being a quantitative researcher isn’t just about graphs and numbers. True, you will see a lot of these along the way, but in the same way that qualitative research requires more than reading transcripts and listening to verbatim, your focus will ultimately be that of any researcher – to tell the story within your data, relate it back to your client’s objectives and understand what it means in relation to their strategy.

What is specific to quantitative research, however, is the methodological approach to gathering the data. By definition, the approach depends on data being quantified, and so methodologies are based around closed question structures – the mainstay of the classic questionnaire!

Now, I know what you might be thinking… ‘lengthy questions… lists and lists of options… matrix grids… Likert scales…’ And you would be right. But before the image of that man brandishing a clipboard takes hold, it’s important to recognise that quantitative research goes beyond ticking boxes.

"Before working in quant, I assumed you needed to be a mathematician to do it. But actually, numbers aren’t the half of it. To be a good at it you will be equally reliant on your understanding of human psychology and the power of your storytelling"
 Alex Jones, Illuminas

In fact, quantitative research is as much about respondent psychology as it is about making sure you are asking the right questions. A good questionnaire makes it easy for respondents to provide answers, but a better one engages with them and encourages them to really think about what they are saying to us – a little detail can go a long way to achieving that.

At the same time, it’s also essential to maintain a holistic view of the overall study because your questions are not just tools for collecting information but also the template for your final analysis. For example, if you know you will need to produce a ranking of preference as part of your story, you need to have the foresight to structure your questions to accommodate the appropriate statistical tests.

Beyond designing the perfect questionnaire, actually getting it in front of respondents provides its own (daily) challenges. Traditionally, face-to-face and telephone (CATI) interviewing have tended to be the industry staple in this regard and liaising with teams of field interviewers over a series of days and weeks throughout projects was common. Today however, the accessibility, speed and capabilities of online and mobile approaches means you’re more likely to be discussing the functionality of a digital questionnaire with the computer programmers as techniques become evermore interactive.

Some agencies specialise in a particular methodology, but at Illuminas the approach is designed around the needs of our clients on a project-by-project basis. This means I have been exposed to a range of quant studies, from finding out the answer to literally one question as part of an omnibus (e.g. “Do you know who this is?”), through measuring customer satisfaction on tracking studies and on to identifying the market for new products in customer segmentation pieces.

But regardless of approach, effective communication skills are essential. Firstly, whether you’re a Research Exec or a Research Manager, you will usually be working as part of a team. Then add client-side researchers, end-clients, suppliers and even other research agencies into the mix and you will soon realise the value clear communication has in producing a smooth and successful project.

One of the things I find most exciting about working with quantitative methodologies is their capacity to be scalable in both remit and reach. For example, a relatively simple online methodology could be used to identify what 25–30 year old males think about the look of a new car. The same methodology could also be used to find out about how it compares to an older model of the car, what the optimum pricing points are, and what impact its advertising campaign could have. And at relatively little expense, it would be possible to get a truly international perspective on all things motoring – be it Accrington or Australia!

And so when it comes to eventually looking at the numbers (see, we’re only just getting to the numbers!), your job won’t be to report everything in bar charts and line graphs but to reduce the volume of data into a comprehendible and engaging story. Complex statistical techniques and graphs can certainly play their part but whether it’s regression analysis or significance testing, a correspondence map or simple pie chart, it will be your job to translate what each means and use it to build your overall narrative.

Having worked in both qualitative and quantitative research I have been able to appreciate the skill in both disciplines. Before working in quant, I assumed you needed to be a mathematician to do it. But actually, numbers aren’t the half of it. To be good at it you will be equally reliant on your understanding of human psychology and the power of your storytelling.

Now, on a scale of 1–10, how much does that surprise you?

Article provided by Alex Jones, Illuminas

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February 2018

Questionnaire Design07.02.18 | MRS, London EC1V 0JR

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Data Privacy in Research08.02.18 | MRS, London EC1V 0JR

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Statistical Methods Masterclass20.02.18 | MRS, London EC1V 0JR

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