Data quality – we here in the Bunker are fanatics about it. Without data quality control, the results of a 1,000-complete telephone survey becomes nothing more than noise. Worse still, it is noise that might serve as the basis for a costly decision for people who trust the erroneous findings.
There are a number of measures that research analysts can undertake to help ensure quality in telephone surveys. It starts with careful survey script writing. Rooting confusing and poorly worded questions out of a survey before it is administered will go a long way toward avoiding mistakes by callers and misinterpretation by respondents. It goes without saying that thorough training of callers is key. Beyond that, much of it comes down to scrupulously monitoring data that comes in and working with the call center supervisor to address issues as they arise. The ability to do this easily is a key advantage to having a call center that is at the same site as the other research staff.
Of course even with the best scripts, the best training program and the most conscientious daily monitoring of data, the biggest factors in data quality for telephone surveys are the callers themselves and the expectations that are placed on them. Callers need to be clear communicators, obviously. But they also need to be engaging on the phone, and trustworthy. Engaging not only because positive energy will persuade respondents to participate in the survey, but also because it will fight fatigue on the part of the respondent. Engaged respondents are less likely to drop out early and more likely to provide good, open-ended verbatims. Trustworthiness is also important. Callers need to be objective – they shouldn’t be tempted to coach respondents to answer a certain way. Close supervision and monitoring can mitigate those issues, but the best solution is to eliminate the underlying cause.
Callers may be tempted to fudge data or cut corners when too much emphasis is placed on hitting quotas. It’s easy for them and their supervisors to lose sight of the fact that the amount of data collected is irrelevant if it’s bad. The key is to create a culture of quality over quantity in the call center. Impress upon the callers that the data they collect will be scrutinized, analyzed and be used by people to make very important decisions. Train them to point out issues with the administration of the survey if and when they arise. Above all else, show them that the organization cares about quality rather than just quantitative metrics of their performance. Addressing that issue at the point of data collection will lead to better analysis and insights down the road.