Falling levels of respondent engagement is a big deal. Not all respondents toil diligently though large grid questions nor reflect deeply upon bank after bank of attitudinal agreement statements, asked by anonymous brands. Here is one way to solve the problem.
Customer research, unlike pure market research, is less vulnerable. Here, light touch questionnaires befit a desirable two-way dialogue. It is a formal opportunity to share experiences and nudge their chosen brands toward greater relevance, responsiveness and value. Nevertheless, patience with long, wandering questionnaires that try to cover all the bases, wears thin.
Despite best efforts, there is a limit to how absorbing questionnaires can be. There remains an irreconcilable disconnect among rigorous questionnaires designed to tease out insight, the metrics a business requires and what respondents are prepared to offer. Ultimately, research needs to be on respondents’ own terms or data quality suffers. With faulty information, organisations lose touch then flag and fail.
Open-ended questioning, on the other hand, allows respondents to do exactly what they are co-opted for – to have their say and to do so without restraint. This is the holy covenant, which is frequently broken. Freedom to express views is buried, reserved for the ‘anything else?’ – a researcher’s catchall gambit.
Open-ended questioning is rarely prominent. Practised respondents acknowledge this and as a result, typically offer one-word responses. Some, already in the throes of disbelief and frustration, bash their keyboard in outright rebellion.
To be fair, until recently, no one really knew what to do with text, save for word counts. Pretty word clouds were nice to have but hardly insightful and so hurriedly discarded in favour of the easily quantifiable.
It is now time to embrace next generation Natural Language Processing (NLP) – which allows for deeper analyses at scale by identifying patterns of words. It is agile enough to operate alongside research objectives and stakeholder expectation. It filters out noise, adds numerical structure, draws relationships and lays the bedrock for sophisticated modelling. The data is rich. With subtleties retained, it always surprises.
The internet is flooded with spontaneous, volunteered feedback: winding commentaries, praise, complaints and reviews with detail to challenge War and Peace. Sharing experiences is a big thing right now and researchers are missing out. Under the right conditions, customers are anything but cagey. Rants are golden.
This zeitgeist begs us to replace 35 minutes of questionnaire monotony to make the most of respondents’ attention and intention. The economics of sample management also encourage this.
Don’t bother with, ‘So what did you think about this advert?’ Rather, ‘What do you think the brand was trying to convey in this campaign?’ Similarly, ‘If you were the branch manager, how would you go about improving things on your first day?’
Many brilliant research programmes have already embraced this and are benefiting from compact and frequent, earnest, to-the-point questioning. Once the covenant is restored, so too does an attention span for a few grid questions.
Let’s also not lose sight that data points, no matter how rich and interesting, must be reliable and inform business metrics, otherwise they are merely anecdotal. Text needs to be controlled for verbosity and calibrated. We desperately need to recruit more NLP experts to work with unstructured data with the same relish and fluency that our statisticians reserve for grids and banks.
In doing so, the public perception of surveys is rehabilitated by forcing questionnaires into step with a sharing society that is willing to answer the mission-critical questions that big data will be forever sorely incapable of posing. This is a society that places a greater importance on their time, data and opinion and that demands personalised, unfettered relationships with brands.
Before we can achieve this, we must revisit our own bizarre predilections about survey research, chief of which is the unconscionable risk of surrendering wholesale control of results to respondents. Perish the thought.
I am a marketing scientist with 24 years of experience working with sales, media spend, customer, web & survey data. I help brands and insight agencies around the world get the most out of data, by combining traditional statistics with the latest innovations in data science. Follow me on Linkedin for more of this sort of thing.
