The Human Factor: Designing Research Experiences for Real People

Maria Twigge

Co-Creating the Future of Survey Participant Exper...

At the recent ASC International Conference, I had the pleasure of running a workshop about the chall...


Paul Hudson

    Creating research experiences for real people is integral to enhancing the value of research for businesses and organisations. Through this participant-centric research design, businesses and clients gain a thorough and accurate understanding of real people and the human factors that determine their behaviours – a classic example of why participant-centric research design is sorely needed can be seen in the British Airways focus groups, which led the brand to stock flight fridges with fruit and salad (items that participants expressed a preference for in the focus groups) but when it came to it, in-flight participants wanted to indulge in chocolatey treats to boost their energy levels on a long journey.

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    Through participant-centric research design, businesses and clients gain a thorough and accurate understanding of real people through quality data and insights.

    Creating the right questions and accounting for the context in which they are posed in, are the two key factors for successful research. Treat your participants’ time as precious, and see every question and moment you have with them as a golden opportunity for insight; this can be achieved through reframing the concept of the research process as a collaborative experience, by protecting the volume of questions that get posed to ensure positive experiences for participants and real added value to your insights:

    1. What you need to know vs. what participants can tell you

    Consider not just what you need to know, but what the audience is able to tell you too; for example, if you want to understand purchase intent, have you given the respondent enough information and context to judge whether they would buy or not? If you would like to benchmark the NPS of your product or service, does this measure make sense in the context of the experience that you are discussing?

    A classically bad example of NPS is the recent application across patient experience in the NHS – a complete contextual failure. In the context of that emergency admission to A&E with your child’s broken foot, can the patient-participant really judge whether they would ‘recommend the service to a friend’ on a ten-point scale?

    Every question posed to participants needs to be easy to respond to, and make simple sense in the context in which it is being asked.

    2. Ask the right questions

    Be aware of biases – both respondent and researcher! There are so many biases to consider and you can’t spot them all alone; a collaborative approach can help spot where your questions have veered off because you are tightly focused on the outcomes you will get. So ask a colleague (not always the same one and ideally not one who is part of the project) to review ruthlessly from an outsider view.

    When I say ‘bias’, I don’t mean bias as in a ‘leading’ question when you are trying to be objective; I mean human bias in the responses you might get from your people – are they going to give you a socially desirable response or are you forcing them to choose an option without consideration of the full set of responses? There is a nice overview of the basics to consider in question design here

    3. Meaningful answers demand a genuine connection

    Abandon your ambition to be neutral and universal in favour of really making a connection with your research participants; have fun, make a joke, put them at ease and discover so much more whilst creating an experience that your participants feel is worthwhile engaging in too.

    It is our job as agencies to create a deep understanding of the audience through research. People are risky and unreliable and we can only account for these human discrepancies if we protect space for them in our research, so strip out the corporate speak and leave space for imagination and creativity and space for free response and discussion in your group, interview or survey, escaping the urge to treat real people like predictable machines and accepting that the analysis will take some skill and expert interpretation and you can’t always run off the stats without this collaborative input.

    There are a great many benefits of a human-focused design which can be seen within the engagement rates in your surveys. When a research experience is designed with the participants in mind, a much more enjoyable experience is created, which will encourage them to engage more with the tasks available to them and work to provide the researcher with many more valuable insights that they would have been lacking otherwise.

    4. Take into account consumer behaviour

    We don’t like to admit it, but actually most of our behaviour is a formed habit, most of our decisions are impulsive, and a lot of what we do we find really hard to articulate. All-in-all, the best predictor of future behaviour is past behaviour, unless you are looking at:

    1. An infrequent behaviour
    2. A new context to the decision
    3. An extinguished behaviour that’s been corrected by negative feedback

    So, evaluate every research objective and be sure to ask your humans the right questions based on your understanding of how habitual the behaviour is and whether factors have changed enough to really turn that intent into action and also look at passive data sources e.g. data from wearable tech that can deep dive those habits and social media for a new opportunity.

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    We don't like to admit it, but most of our behaviour is formed out of habit, most of our decisions are impulsive, and a lot of what we do we find really hard to articulate.

    5. Make it easy to respond

    Make it easy; How often have you had a headline on a slide that has ‘ease’ contained in it. I would bet that this is the most common insight that we see coming out of market research studies with a whole host of recommendations of how this applies in different contexts, but this is a really important consideration within the research experience too. Often times we are guilty of focusing way too much on what we want to know and not enough on what a participant is able to consider. We have learned so much from behavioural science, for this and more top tips take a look here.

    6. Find answers from existing data

    Do your homework; there has never been more data available for our perusal, to develop your hypotheses before you go to your audience for exploration. And if you design a research experience in which you ask questions that have already been answered your participants are wasting precious interactions on more duplication; here are two of my favourite data sources for background desk research are the profiling data that is freely available on YouGov and the ONS stats and datasets.

    Research for Real People

    Too many research experiences are designed to answer a narrowly defined question and assumes too much of unpredictable human behaviour. Designing research for real people means considering the context that they are operating in and respecting their time so they collaborate with us and give us the true golden insights.

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