One area that many of our clients have questions about is reporting. As in, How do I make meaning out of all this survey data? What types of reports offer the appropriate insight in this case?
It’s no surprise that our relationship managers spend the majority of their day helping clients figure out ways to create meaningful reports. Understandably so, considering that the information contained within these reports is likely the initial motivation for their decision to conduct a survey.
There is no one right way to go about analyzing survey results, but there are a few best practices on how to analyze survey data that can really simplify the entire reporting process.
1. Work Backwards—Plan the Report Before Planning the Questions
We often tell clients to work backwards when planning their survey program. Rather than jumping into question creation, a survey planner should first have an idea of what the final report will offer in terms of useful information. If you are conducting a market demographics research study, and you are interested in knowing what age group is most receptive to an ad message, it is important that your survey ask age (or age range), rather than their date of birth. In the latter case, the same data can be extrapolated, but it creates extra work for you when it comes time for reporting.
Also, if you plan to include statistical information in your report (mean age, mean income, etc.), you want to make sure that your survey questions will elicit numerical responses. Don’t ask a respondent for their annual income with a one line comment box—your data will become very messy with responses like, "$35953.00" and "60000 USD." Again, know what data you want, and what you want to do with it first. Then, ask the questions to fetch this data according to your plans.
2. Use Filters to Drill Down—Segment your Data to Reveal Insight
Segmenting your respondents into targeted groups is a best practice we advocate often. It is just as important, however, to also segment the data when running analyses in order to reveal a deeper level of insight. For instance, your survey results may state that the average satisfaction rating from your entire client base is 4.7 out of 5. Upon further research, however, you might find that the average rating in most states is 4.9 or 5.0, except for the Northwest states, which gave an average rating of 4.1—clearly under company standards.
Without using filters to segment your data, you can overlook vital information that can affect your business. Filters can be used to separate and compare groups of data based on virtually any data point you have already in your database, or those that you might collect in the same survey.
3. Every Good Report Deserves Another—Observe Trends Over Time
No survey is an island. It might sound like extra work, but if you are looking to achieve real business results through your survey initiative, then your plan needs to include conducting the same survey again at a later time. Only by doing so can you observe trends and keep your organization accountable for the metrics you are aiming to manage.
If you are surveying your customers about telephone technical support, you want to ensure that you can pull cross-survey reports that show any progress or decline in feedback ratings. Such information is invaluable in directly managing a team; when such a survey is integrated into a team’s incentive plan, for example, these metrics can be instrumental in motivating employees to work harder and better.
Ongoing surveys that can be analyzed against each other with these cross-survey reports help you track changing opinions and needs so your organization can react efficiently to unexpected downturns, or perhaps increase revenue through new opportunities. Survey data, unfortunately, does have an expiration date, and in a dynamic business world, it is necessary to conduct ongoing surveys and accordingly adjust.
It’s no surprise that our relationship managers spend the majority of their day helping clients figure out ways to create meaningful reports. Understandably so, considering that the information contained within these reports is likely the initial motivation for their decision to conduct a survey.
There is no one right way to go about analyzing survey results, but there are a few best practices on how to analyze survey data that can really simplify the entire reporting process.
1. Work Backwards—Plan the Report Before Planning the Questions
We often tell clients to work backwards when planning their survey program. Rather than jumping into question creation, a survey planner should first have an idea of what the final report will offer in terms of useful information. If you are conducting a market demographics research study, and you are interested in knowing what age group is most receptive to an ad message, it is important that your survey ask age (or age range), rather than their date of birth. In the latter case, the same data can be extrapolated, but it creates extra work for you when it comes time for reporting.
Also, if you plan to include statistical information in your report (mean age, mean income, etc.), you want to make sure that your survey questions will elicit numerical responses. Don’t ask a respondent for their annual income with a one line comment box—your data will become very messy with responses like, "$35953.00" and "60000 USD." Again, know what data you want, and what you want to do with it first. Then, ask the questions to fetch this data according to your plans.
2. Use Filters to Drill Down—Segment your Data to Reveal Insight
Segmenting your respondents into targeted groups is a best practice we advocate often. It is just as important, however, to also segment the data when running analyses in order to reveal a deeper level of insight. For instance, your survey results may state that the average satisfaction rating from your entire client base is 4.7 out of 5. Upon further research, however, you might find that the average rating in most states is 4.9 or 5.0, except for the Northwest states, which gave an average rating of 4.1—clearly under company standards.
Without using filters to segment your data, you can overlook vital information that can affect your business. Filters can be used to separate and compare groups of data based on virtually any data point you have already in your database, or those that you might collect in the same survey.
3. Every Good Report Deserves Another—Observe Trends Over Time
No survey is an island. It might sound like extra work, but if you are looking to achieve real business results through your survey initiative, then your plan needs to include conducting the same survey again at a later time. Only by doing so can you observe trends and keep your organization accountable for the metrics you are aiming to manage.
If you are surveying your customers about telephone technical support, you want to ensure that you can pull cross-survey reports that show any progress or decline in feedback ratings. Such information is invaluable in directly managing a team; when such a survey is integrated into a team’s incentive plan, for example, these metrics can be instrumental in motivating employees to work harder and better.
Ongoing surveys that can be analyzed against each other with these cross-survey reports help you track changing opinions and needs so your organization can react efficiently to unexpected downturns, or perhaps increase revenue through new opportunities. Survey data, unfortunately, does have an expiration date, and in a dynamic business world, it is necessary to conduct ongoing surveys and accordingly adjust.
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