Why a Reputable Recruiter Is Essential to the Research Process
When conducting research, it is very important that the population you’re examining ties directly to the product or service that’s under development. If you sampled the wrong user population, the results would guide the design and engineering teams down the wrong path, leading to the development of a product that very few people would use.
When you hire a reputable recruiter to assist with participant sourcing, they use a highly structured, well thought out, and detailed screening process to ensure that they pull the right types of people into the study. The recruiting process is a partnership between the researcher and the recruiter. For example, while a researcher might request participants who have limited smartphone experience, the recruiter might refine that request, focusing on people who don’t own or operate a smartphone on a regular basis and, thus, helping to more specifically define the intended participant. As a result, the participants who are in the study will understand the concept of a smartphone, but won’t own one. It’s such tiny details as these that play a role in acquiring the right people and ensuring your study’s success.
Building the Screener
Typically, a recruiter requires you to develop a participant screener that outlines the types of people you want to recruit. The screener includes information such as age, education, income level, and experience with certain technologies. It is also very important to add behavioral questions such as How many hours per day do you watch television? or How many times a week do you go shopping? A good recruiter examines your screener and asks clarifying questions to further refine it before starting the recruitment process. This includes examining your questions to determine whether some are too strict, making it hard to gather together enough participants, or too loose, resulting in too wide an array of participants.
The screener also includes the incentives participants are to receive for helping with your study, and the recruiter will help you to determine the right amount for the incentive to ensure that you’ll get the people you need. If you provide too small an incentive, people might feel it’s not worth their time to participate. However, if you provide too large an incentive, you’ll find some people simply want to collect the cash and don’t care about helping you refine the design of a new product you’re building.
Locating the Participants
Using Craigslist is definitely an option for recruitment, but most reputable recruiters have an extensive database of participants they can contact at a moment’s notice. Their databases indicate what participants respond well during sessions, deceive or lie to researchers, have been no-shows for sessions, or have been involved in too many studies, so are becoming professional participants. Recruiters’ databases also help identify which participants are very communicative and which tend to provide only superficial data. Some of these databases are extremely impressive and powerful, allowing recruiters to gather high-quality participants with surprising speed.
When necessary, a recruiter might use Craigslist to find participants, but they’ll use a rigorous screening process to ensure the participants truly meet the needs of the researcher. Unfortunately, it’s not uncommon for participants to deceive recruiters and researchers just to be part of a study and collect the incentive. However, recruiter databases can help you to avoid this by tracking these kinds of participants and eliminating them from consideration during future recruitment efforts.
Without recruiters and their participant databases, you’ll often be gambling with your recruiting—significantly increasing the likelihood that you may inadvertently recruit a participant who is interested only in collecting the incentive. When research sessions go to waste because of bad participants, you end up wasting a great many resources, including the researcher’s time, the cost of the incentive, and the opportunity cost of not obtaining good data.
