The commissioning, set-up and recruiting process of market research projects is one of the areas arguably ripe for automation. You could simply include your credit card information, pick a testing tool, buy a sample and off you go instead of having to enquire via a website, speak to an account manager, lift a PO, have a set up call, etc. If required, sample purchases could be connected to external research platforms and agile testing could be carried out quickly. Sounds awesome! Theoretically...
At the beginning of the study, a little time spent will mean a lot of time and money) saved in the long run. Taking a few minutes to chat to the sample and/or analysis tools supporting research experts enables you to benefit from their knowledge of it. And this increased degree of understanding can lead to greater precision in the selection of the sample and a technique of the instrument that ensures that goals are met.
Design and Set-up
Automation will assist to varying degrees when it comes to setting up the research tasks, whether programming a survey, developing a focus group subject guide or preparing a diary report. Bite size, off-the-peg study tasks allow smaller tasks to be easily deployed. By eliminating the 'blank sheet of paper' syndrome, survey models complement the design process. In the meantime, innovative and visual resources such as brainstorms and smartboards provide an immersive, user-friendly means of collecting collective input without the need for hundreds of configuration choices to be tweaked.
The agile implementation of research activities is made possible by a variety of resources built individually to holistically fulfill every research objective. Only make sure that the resources with the features most appropriate for your needs are selected. Again, this is where the research provider's un-automated guidance can be helpful.
It's tempting to think of analysis as the primary opportunity for automation of market research. This is definitely true of many simple quantitative knowledge activities, such as cleaning databases, combining datasets, and recoding variables. Such functions have already, indeed been automated. A trained researcher, however, is still expected to make decisions about how the data is interpreted, what is relevant and what is not.
The automated qual data processing is also lagging behind that of quant because it is much harder to accomplish language and emotion analysis. You will also hear businesses saying that they have qual research, which then turns out to be nothing more than a frequency count of words expressed in a word. Even if software can help you categorize and detect patterns within your data, it still takes a researcher to draw out the most outstanding points with an understanding of the lives of consumers in context, business processes and market climate.
You can automate a lot of the research analysis process, but you the researcher, still have to judge what is relevant. What's great (for purposes of work retention!) is that the true insight meaning lies in this innately human role.
On the face of it, items such as Wordsmith, a 'Natural Language Generation Engine' that helps you to translate knowledge into a natural-sounding text seem to be a way to get the PowerPoint presentation written for you when time is short. The long-hoped 'write report' button that you can press and wander off to make a cup of tea, however, is still not quite there. Although Wordsmith has no doubt value for translating market data and such as into reports, in terms of writing a template, adding in merge codes, and defining alternate text to be used depending on the results being merged in, it still takes quite a bit of up-front effort. Most of all, human feedback is also required to determine what is important enough to be included in the first place and to ensure that this is conveyed in the most relevant and engaging way to stakeholders.
There are a lot of resources at present that can assist in providing your report material, but the magic' build report 'button on your keyboard is still a long way off.
Autonomy is one of the major drivers of automation - consumers want more power and faster turn-around times and DIY is a big trend here. Hypothetically, the automation of market research goes a few steps further than DIY, making it not only faster, but also simpler. In truth, the reality of today at least, that's not the case.
The actionable perspective, moving from the process of setting up and running market research activities to the basic purpose of the study itself, gives us even more pause for thought. No one particularly needs market analysis 'outputs'. What they want is input from the back of these outputs on what their brand can do. And that's not something you'll get any time soon from a bot. There is still the need for a crack team of research experts to be on hand, even with the most sophisticated automation.