COR: Survey Effectiveness Metric

What is COR

COR (Completion Rate) is the percentage of respondents who complete a survey from start to finish. It is a key performance indicator that helps assess how engaging and accessible the survey is for participants, as well as the quality of the sample selection. A high COR indicates that most participants found the survey interesting and understandable enough to complete, while a low COR may signal issues with survey design, length, or question complexity.

What is COR used for

COR is used for several key purposes:

1. Assessing survey quality. A high COR indicates the survey was engaging and clear for respondents, allowing them to complete it easily. This helps evaluate the survey’s structure, length, and question complexity.
2. Improving survey design. By analyzing COR, researchers can identify problematic questions or design flaws and make adjustments to increase completion rates in future surveys.
3. Enhancing data representativeness. A high COR ensures that survey data are more complete and representative of the target group, improving accuracy and reliability.
4. Optimizing costs and time. Surveys with high COR tend to be more cost-effective since fewer additional participants are needed to reach required data volumes.
5. Analyzing dropout reasons. Understanding why respondents drop out helps improve engagement and retention in future studies.
6. Improving respondent interaction. COR analysis can reveal which survey aspects are most and least appealing, guiding better communication strategies with the target audience.

How is COR calculated

COR is calculated as the ratio of respondents who completed the survey to those who started it, expressed as a percentage. The formula is:

COR = (Number of respondents who completed the survey / Number of respondents who started the survey) × 100%

Where:

• Number of respondents who completed the survey is the count of participants who answered all questions and reached the survey’s end.
• Number of respondents who started the survey is the total number who began answering questions, including those who dropped out.

For example, if 200 people started the survey but only 150 completed it, then:

COR = (150 / 200) × 100% = 75%

This means 75% of starters finished the survey. A high COR suggests good engagement and interest, while a low COR may indicate issues with survey design, length, or complexity.

General methodology to improve COR

Key approaches to increase COR include:

1. Define clear survey objectives and know your target audience to craft clear, relevant questions. Optimize survey length to avoid respondent fatigue.
2. Conduct pilot testing with a small group to identify and fix design or comprehension issues.
3. Ensure technical accessibility across devices and platforms; use engagement tools like progress bars; clearly communicate anonymity and confidentiality.
4. Monitor COR regularly and be ready to adjust the survey during data collection based on feedback and interim results.
5. Analyze both main survey results and COR to assess effectiveness and improve future survey designs.

What is a normal COR value?

Normal COR varies greatly depending on survey topic, length, complexity, format, distribution method, and target audience. Typically, COR ranges from 20–30% for broad online surveys to 80–90% for short, well-targeted surveys with highly engaged participants.

In research and marketing, a COR above 50–60% is generally considered good. Well-designed, targeted surveys may achieve even higher rates.

Note that low COR may be acceptable in contexts like very long or complex surveys, where only the most motivated respondents complete the survey. In such cases, focus not only on increasing COR but also on data quality and representativeness.

How to improve COR

Strategies to improve COR include:

1. Keep surveys concise by including only essential questions.
2. Use simple, clear language to avoid confusing respondents.
3. Start with easy and engaging questions to motivate continuation.
4. Use branching logic to avoid irrelevant questions and tailor the survey experience.
5. Optimize surveys for mobile devices, as many respondents use phones or tablets.
6. Include a progress bar to show respondents how much is left.
7. Assure respondents of anonymity and confidentiality.
8. Offer small incentives or prizes to encourage completion, especially for longer surveys.
9. Pilot test the survey to find and fix potential issues lowering COR.
10. Target the survey to interested groups to improve completion likelihood.
11. Explain survey purpose, importance, and how results will be used to motivate participation and completion.

Implementing these tactics can improve COR and enhance data quality through higher engagement and respondent motivation.