The (not so) Hidden Maze: APIs and Pre-Screeners
In Market Research, aggregating and managing traffic plays a pivotal role in connecting researchers with respondents. However, the seamless process is only seemingly so, and there is a lot of friction between the delivery and the source.
In many cases, the obstacle is the ‘respondent time’ taken for pre-screeners. Pre-screeners negatively influence the respondent experience poorly shaping the journey from initial engagement to participation.
Pre-screeners are questions designed to filter respondents based on specific criteria predetermined by researchers. These criteria can encompass demographic information, consumer behaviors, or other relevant attributes depending on the nature of the research study.
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1.?????????? Initial Engagement:
Respondents are drawn to participate in research studies through various channels such as alerts, emails, online ads, gaming apps, etc. At this stage, they are presented with basic information about the study.
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2.?????????? Pre-Screening Process:
Respondents then provide information to determine their eligibility for the study. Questions can range from demographics (e.g. Age and Gender) to queries about purchasing habits or brand preferences.
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3.?????????? Evaluation and Disqualification:
Based on the responses, respondents may be either qualified or disqualified from participating in the study.
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4.?????????? Qualified Participation:
Qualified respondents who successfully pass the pre-screening proceed to engage with the main survey or research activity.
The Impact on Respondent Experience
While pre-screeners serve a crucial purpose in ensuring that researchers obtain relevant data, they also have consequences that negatively impact respondent experience:
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?Respondents may feel frustrated if they invest time in completing pre-screening questions only to be disqualified from the study. ?
?2. Perceived Exclusivity
Pre-screeners create a perception of exclusivity, wherein only a select group of individuals are deemed eligible to participate. This can deter them from engaging with future research.
?Worse, respondents may be incentivized to lie and try again.
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3. Lack of Transparency
The pre-screening process may not be clearly communicated to respondents upfront, leading to confusion or misunderstanding. ?
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Improving the Pre-Screening Process
While we are not researchers, we also can suggest a few good practices to enhance the respondent experience and mitigate the negative effects of pre-screeners:
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We can streamline the pre-screening process by minimizing the number of questions and focusing on essential criteria relevant to the research objectives.
?2.Feedback Mechanisms:
Provide appropriate feedback to disqualified respondents whenever possible, offering insights into why they were not eligible and demonstrating respect for their time and effort.
?3. Incentives:
We should treat the incentives towards respondent time, and not respondent qualification.?
?Ultimately, we need to treat respondents like…. the humans they are (in most cases ??).
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10 个月Vignesh, what strategies can you implement to overcome pre-screening barriers and foster diversity in participant pools?
Re: solution #3: totally agree this is key. Some sample suppliers have been trying to do what you suggest and incentivize based on time spent / questions answered (whether ‘qualified’ or not), but a/ many tools lack the basic capability of returning respondent-level information about how much time/how many answers were answered in each session. - b/ very often, the prescreening experience is actually a series of prescreening experiences jumping from one platform to another (and repeating some of the same questions). A fixed DQ incentive is not okay when disqualifying could take between 5 seconds and 25 minutes… There is no excuse for this to still happen with the technology available today. And btw, why do we even ‘send respondents’ to a survey ‘link’ on another website when we could be calling question(naire)s via APIs and displaying them natively inside the publisher/panel’s app/website?
Director, Partnerships & Supply at Quest Mindshare
1 年Good post Vignesh Krishnan - a lot of valid points there. Respondents are the life blood of the industry, human respondents that is ?? so we do need to be mindful of how the user experience is and the incentives for the respondents time.
??IIEX ?Nobody loves surveys as much as I do ? Data Fairy ?No buzzwords allowed?? Quirk's Award & Insight250 Winner
1 年You know I agree with all the points mentioned above. We don't often discuss Feedback Mechanisms. Based on the hundreds of posts I've read on social media (maybe thousands? ??), participants tend to think that they are being disqualified because of the last question they answered. When that question pertains to ethnicity, age, income, or gender, it makes people feel bad about themselves and can lead them to lie in the future because they believe they don't fit the "right" demographics. It does raise the question of whether or not we should be more transparent about disqualifications. At the same time, there are downsides to disclosing too much. Do we really want to say we're looking for household income over 75K and prove them right? Will fraudsters attempt to return and answer differently? Ultimately, we need better targeting—the good old profiling kind, not pre-screening.
ResTech | MarTech | Advisor | Investor | Mentor | Board Member | Fractional CXO
1 年Worth pointing out. It sounds obvious and common sense for anyone from outside the industry. UX and usability has to have a seat at the table and is equally important long term as the validity of the research. This will ultimately create better data as our respondent pool will be greater and more representative if we don′t mistreat the poor respondents that are willingly taking surveys.