Written by Tasmin Sibbald, Client and Operations Director<\/em><\/p>\n

Last month I wrote about the importance of monadic testing using A\/B testing (the \u2018Split By\u2019 steers), which is at the heart of the robust Vypr methodology.\u00a0 This month I want to explore the role that Qual research can play when peppered into the testing mix.<\/p>\n

At Vypr we are really passionate about ensuring you make informed business decisions based on more than one piece of data and methodology. Our clients can achieve this by using \u2018steer chains\u2019 to do an initial test and then validate your findings using a different methodology.<\/p>\n

So what about the role that \u2018Qual\u2019 research can play?<\/strong><\/p>\n

For those who aren\u2019t from an Insights background, in its most simplest form Quantitative research (known as Quant) is data that is numbers-based, countable, or measurable. Whereas Qualitative data (Qual) relates to opinion using descriptive and emotional language.<\/p>\n

A great example is from one of our lovely clients.<\/strong> They learnt from a Vypr free text steer that for their particular category, consumers wanted the cooking instructions to be as simple as possible (because of the chances of them being under the influence of alcohol while preparing it!). While the most empirical way to have tested the optimum preparation instructions, would have been to use the Split by Image (A\/B testing), the client wouldn\u2019t have gleaned the same richness of data from this steer in isolation. Coupling the Split test with some Qual (the free text) led to this nugget of \u2018gold dust\u2019.<\/strong><\/p>\n

Most Vypr steers are quantitative and provide reliable and robust data, which is in the Vypr DNA. Currently, we have one \u2018Qual\u2019 steer, Free Text (which is soon to be joined by the VyPops steer – moderated video responses to an open question). We also have a hybrid \u2018Qual\u2019\/\u2019Quant\u2019 steer – Sentiment Analysis, which produces qualitative research but at quantitative response levels. Blending Qual with Quant is a good recipe for rich insight, but when should you add this sprinkling of \u2018Qual\u2019 to your research methodology?<\/strong><\/p>\n

1. Use the Free Text steer to inform the options for your Single\/Multi Answer steers.<\/strong><\/p>\n

For example, instead of assuming that you know all the appropriate options for your steer, you can use some of the surprising or more interesting responses from your Free Text steer to understand how representative they are and whether they are worth more exploration. In this way, you are using \u2018Qual\u2019 and turning it into \u2018Quant\u2019 and your options are truly consumer driven.<\/p>\n

2. Use the Free Text to ask a consumer \u2018Why?\u2019 \u2018following on\u2019 from a previous steer.<\/strong><\/p>\n

This is a popular choice, but one that should be used with caution. This will only tell you why consumers think <\/em>they responded in a certain way, which may in reality not be the truth for all responses. <\/em>I am not implying that consumers are lying here, more that when you ask someone \u2018why?\u2019 there is a chance that they will post-rationalise and try to retrofit a rationale which may or may not ring true. The simple truth is that consumers don\u2019t always know why they think what they think. However, you can quantify any potential gold-dust insights here by further testing the finding with a \u2018Quant\u2019 steer such as a Single\/Multi Answer and the Split Bys.<\/p>\n

3. Use the Free text\/Sentiment steer for quotes to bring your presentation to life<\/strong><\/p>\n

Nothing brings your plans to life more than an actual consumer saying something quotable. Not only will this make your plans far more memorable, but they become more credible as well. With the soon-to-be-released VyPops steer you will\u00a0be able to use consumer videos in your presentations too!<\/p>\n

4. Use the Sentiment steer to gain feedback on your products<\/strong><\/p>\n

This can be used at both the concept stage and as a final check pre-launch to ensure you\u2019ve captured some open feedback. This can help you make those final iterations to ensure that your product is as good as it can possibly be. The machine learning software which analyses the responses even summarises the overall sentiment at \u2018Quant\u2019 levels. We would then advise retesting any changes introduced from the \u2018Qual\u2019 with monadic testing, such as the Split Bys.<\/p>\n

I hope that these examples have given you some insight as to how blending \u2018Qual\u2019 and \u2018Quant\u2019 can help you understand your consumers better. They can be a really good starting point in the Strategy stage to understand your category, but also to understand opinions once your product has launched.<\/p>\n

If you’re a Vypr client and require<\/strong>\u00a0any advice or support<\/strong> on which steers to use and when, please don\u2019t hesitate to get in touch with your Client Manager or our Helpdesk using the help icon to the bottom right.<\/p>\n

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Not a Vypr client? Find out more about how Vypr can help you by\u00a0contacting our friendly team<\/a>.<\/strong><\/p>\n

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Tasmin Sibbald, Client and Operations Director<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Written by Tasmin Sibbald, Client and Operations Director Last month I wrote about the importance of monadic testing using A\/B testing (the \u2018Split By\u2019 steers), which is at the heart of the robust Vypr methodology.\u00a0 This month I want to explore the role that Qual research can play when peppered into the testing mix. At […]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-6076","post","type-post","status-publish","format-standard","hentry","category-blog"],"acf":[],"yoast_head":"\n