Why response rate is important

Improve Response Rates. Commonly associated with survey methods, response rates refer to the percentage of eligible sample units e. Ensuring that you take measures to achieve your target sample size i. Workforce Powerful insights to help you create the best employee experience.

What is a good survey response rate? What is a survey response rate? A survey response rate is defined as the percentage of the total number of completed survey responses out of the respective total number of survey respondents For example, a study conducted to understand from potential respondents how useful an online tool is and what existing features do they like and what features they would like to see added to the tool.

Calculating your survey response rate Therefore, a survey response rate is calculated as the number of people that took and completed a survey divided by the sample that the survey was sent out to.

Two major factors that dictate the importance of online survey response rates are: Research objective: The end result of the research via the survey dictates what is an acceptable survey response rate.

If the purpose of the study is to project results to a larger population like with product feedback, awareness or usage trends, etc. Data analysis: If the survey collects a lower response rate, the data that is collected and analyzed cannot be considered as representative of the general population.

Generally, minimum samples are required to determine significance and lesser responses hamper the ability to conduct significance testing or even statistical analysis. Free survey templates to increase responses Factors that influence survey response rates Multiple factors like the target audience, the survey objective, incentives offered, level of personalization, etc.

The factors that can improve your survey response rates are: Survey design: Before the survey is conducted, the end objective of the survey has to be clearly chalked out and hence the survey design is very important. This helps plan each milestone of the survey and there is no ambiguity on the data analysis.

Some of the basic metrics to keep in mind are: Survey questions: Survey questions have to be easy to understand even easier to respond. This can help in collecting multiple and genuine responses. Survey length: The survey length has a major impact on the survey response. If the survey is too long, the respondent loses interest. If they were to even complete the survey, there is a risk of uninterested responses which dilutes the validity of the survey responses and analysis.

Survey logic: Survey logic is an important aspect of the survey process. If the logic is erratic or the questions are disjointed, there is a high risk of a survey dropout. Respondent demographics: The range of potential respondents for a survey is derived from a sampling method. A sample provides the best potential respondents for a survey on the basis of the respondent demographics. This may be a mix of customers or respondents that are aware of the organization conducting the survey.

The survey can also be sent out to an opt-in sample for a certain topic. Surveys that are sent out to B2B respondents and surveys sent out to B2C respondents also have different response rates.

Lastly, some demographics of people generally have a higher response rate to surveys than some other demographics. If this is indeed the case, then perhaps the current generation of physicians will be more receptive to completing a web survey than their predecessors. The purpose of this cross-sectional, mixed-mode study is to examine how the mode of survey administration affects the physician response rate. A list of 14, licensed, Minnesota physicians was obtained from the Minnesota Board of Medical Practice.

From this list, a random sample of physicians was selected. Of those selected, The remaining Physicians in the latter group were randomly assigned to one of four mode groups: mail-only, mail-web, web-mail, and web-only.

There were physicians in each group. Of these, physicians participated in the survey, yielding an unweighted response rate of Figure 1 depicts the crossover design used in this study.

All the mail contacts included a cover letter that was printed on the University of Minnesota, Twin Cities letterhead. The letter explained the purpose of the study, why they were selected, and the voluntary, confidential nature of their participation. It was accompanied by a copy of their assigned survey booklet and a business reply envelope. At the end of data collection, the surveys were given to Northwest Keypunch, Inc.

Upon return of the surveys and receipt of the database, the primary author randomly spot-checked the data to ensure its accuracy. For all web surveys, the body of the email included information that was similar to what was included in the mailed cover letters.

It was merged with the database from Northwest Keypunch, Inc. Initially, physicians in the web-mail group were informed of the survey via email. At first, non-responders were sent an email reminder, which included a link to the survey. Physicians who did not respond to that email were randomly assigned to one of two groups—a reminder letter or survey packet group. Those in the reminder group were mailed a reminder letter containing a personalized, survey link, which they were asked to type into their internet browser.

Meanwhile, those in the survey packet group were mailed a cover letter, survey booklet, and business reply envelope. Later, non-responders in both groups were sent a survey packet. Non-responders in the mail-only and mail-web groups received up to two additional contacts. In contrast, non-responders in the web-mail and web-only groups received up to three additional contacts. When physicians returned the survey, refused to participate, or were deemed ineligible, all subsequent contact with them ceased.

Informed consent was implied if physicians completed and returned the survey. Written and verbal consent was not obtained. By mode, response rates were computed by tallying the number of completes and dividing it by the number of eligible cases in accordance with the RR1 guidelines outlined by the American Association for Public Opinion Research [ 26 ]. Data from the original sampling frame was used to compare the practice area and location of responders and non-responders within each group.

A p -value of 0. For the mode experiment, the overall response rate was Table 1 presents the response rates by mode. However, these results were not statistically significant. Table 2 compares the practice area of responders and non-responders by mode. Across all modes, the majority of responders were specialists. The proportion of responders who were specialists ranged from Across all modes, there were not any statistically significant differences in the practice area of responders and non-responders.

Table 3 compares the practice location of responders and non-responders by mode. Regardless of mode, the majority of them practice in an urban area. There were not any statistically significant differences in practice location amongst the two groups.

There were not any statistically significant differences in the response rate across modes. The higher response rate for the web-mail group was unexpected, but consistent with prior research [ 19 ]. However, the finding that the overall response rate was lowest for the web-only group was expected.

Amongst physicians the response rate for mailed surveys tend to be greater than it is for web surveys [ 3 , 7 , 11 , 15 , 17 , 29 ]. There could be numerous reasons for this. Also, the volume of emails that some physicians receive may force them to skim their inboxes and only respond to the most important emails. It was not possible to determine if physicians deleted the email invitations without opening them or if they were diverted by spam filters.

In a study comparing mail and web surveys, Leece and colleagues [ 15 ] found that surgeons who are members of the Orthopaedic Trauma Association are more apt to respond to mail surveys than web surveys. And, in a study of various specialists, Cunningham and colleagues [ 30 ] found that the response rate to their web survey varied by specialty. The response rate was Taken together, these findings suggest that perhaps researchers should be using different modes when studying different groups of specialists.

Prior research suggests that individuals are more apt to respond to survey on topics that are important or of interest to them [ 31 , 32 ]. Compared to generalists, specialists are apt to treat patients with multiple health conditions or that require intensive, complex medical care. Due to the complexities of care, the best laid plans for the optimal delivery of care may not pan out, leading to a medical error or series of errors.

The saliency of disclosure for specialists may have prompted some of them to complete the survey. While patients treated by generalists can also experience a medical error, the issue may be less salient for them. Additionally, the disclosure of adverse events and medical errors is a sensitive topic for many physicians. About the Author. Gerald Bramm is the President of Bramm Research, a firm that conducts marketing research assignments primarily for associations, business publications and B2B companies.

He has worked on hundreds of projects both in Canada and the U. To learn more, visit the Bramm Research website www.