Rest assured that your survey data is safe and secure with Snap Surveys
On April 7th, a new web server vulnerability named HeartBleed was made public, which affects up to 66% of all secured web services. This makes it possible for an attacker to gain confidential information on web traffic. You can rest assured that your data is safe and secure with Snap Surveys.
Because of the types of systems Snap Surveys uses to provide our web services, none of our services are (or have ever been) vulnerable to this attack.
We’re proud to be one of the few organizations compliant with ISO27001, the highest possible standard for information security. View more information on Snap Surveys security.
Further information on the HeartBleed bug can be found at http://heartbleed.com.
When designing online surveys, take into consideration information accuracy
Some online survey questions yield more accurate results than others. Survey respondents can accurately answer straightforward demographic questions about their gender and age, however, when it comes to attitudes and opinions on a particular subject, some respondents may not produce a clear answer.
Attitude and opinion questions should be phrased in a way that best represents how survey respondents think and speak about a particular subject. In some cases, certain online survey questions need to be skipped when they do not apply to a respondent’s experiences or they are irrelevant to a respondent. Continue reading
Learn how to band quantity variables for analysis using Snap Survey Software
If you have a quantity question in your survey, you may want to split the results into bands for easy analysis of results. For example, you may wish to split ages or salaries into ranges.
There is a quick way to do this in Snap Survey Software using numeric variables. Numeric variables are a type of derived variable (i.e. they contain information that is derived from responses).
Quantity data provides a continuous set of values. Because of this, it is difficult to find out how values are distributed, as every response could be different. If you want to see what ranges responses fall into, you have to group the responses together. You can choose how to group your responses, though it is best to group them into equal size bands to see how the responses are distributed. You need to choose how wide the bands are to make sure that you don’t miss any important spikes or dips in results (which might average out over a wide band).
Learn how to use filters to analyze respondent data using Snap Survey Software
Snap Survey Software provides the function of filters that users can use to limit the data that is displayed or analyzed. You can filter data so that:
- it only includes the respondents you want (for example, creating a pie-chart showing the sports preferences of Canadian men between the ages of 25 and 35)
- it does not include the people you don’t want (for example, excludes all men who like ice hockey)
- it only includes people who have done things on a certain date or time (for example, watched ice hockey in November)
Filters allow you to limit the data you view. You can use the filter function when analyzing data by filtering it by respondents’ answers to one or more of the questions. You can also filter data by respondents who did or did not reply to certain questions, for example, you can select all respondents who wrote a comment.
How-to: Join surveys using Snap Survey Software
Last week, we discussed how to merge surveys. Today, we discuss how-to join surveys. ‘Joining’ is the process of connecting data cases together from different surveys to form a longer case using survey software. There are many situations that may call for joining surveys, for example:
- Any survey, which refers to relatively static data held externally. For example, in a survey of restaurants in a fast food chain, it would be possible to have details of store size, location, and manager etc. held in a survey which is referenced by a “mystery shopper” survey. Continue reading
What is Gap Analysis in Snap Survey Software?
Advanced survey software solutions provide the capabilities to conduct Gap Analysis. Gap Analysis shows the difference between how important attributes are to your survey respondents and how satisfied respondents are with those attributes. Gap Analysis is a useful way to compare the results from your satisfaction survey questions and importance survey questions, and allows for easy interpretation.
By comparing satisfaction and importance scores on your chart, you can use gap analysis to identify priorities for improvement.
Gap Analysis indicates that if the satisfaction bar is shorter than the importance bar, the company may be experiencing an issue! Below is an example of a Gap Analysis chart. Continue reading
Demographics are characteristics of a population. Characteristics such as race, ethnicity, gender, age, education, profession, occupation, income level, and marital status, are all typical examples of demographics that are used in surveys.
When designing a survey, the research needs to assess who to survey and how to breakdown overall survey response data into meaningful groups of respondents. Both assessments are based on demographic considerations. Continue reading