What is Text Analysis?
Text analysis is a useful and convenient tool used for quantifying and transforming responses to open text survey questions into actionable insights.
By running a text analysis on survey response data, researchers can easily comb through open text responses and group them into categories. This enables them to build more detailed reports on their data, which allows for more powerful, informative insights as well as better communication of their findings.
In a recent article we discussed how it has become best practice to use open text fields and questions sparingly.
But it’s also important to recognize that there are instances in which open text fields and open text questions can be used effectively, and yield response data that can inform business decisions.
When to Use Text Analysis
Below are some instances in which text analysis can benefit researchers immensely.
While organizing and analyzing customer feedback data.
Over the years we’ve made plenty of cases for how important it is for organizations to up their customer experience (CX) game by consistently measuring their Net Promoter Scores (NPS).
NPS is the result of asking customers how likely they are to recommend a product and service.
As useful as this score is, a numerical rating alone won’t give you the information needed to then take action that will improve CX at a large scale.
To get a deeper level understanding of how customers are feeling about your product or service, providing them an opportunity to write out their feedback is where text analysis comes in handy.
By including an open text field where survey respondents can provide details and context for their feedback, and then running text analysis on these responses, researchers can get extremely granular with their insights and identify trends in the experiences that their customers are having.
When “other, specify” question types are used.
If your survey questions are well designed, there should be an appropriate response for each survey taker for all required questions.
To achieve this, oftentimes an “other-specify” open text field is required. This is the option that they will choose if none of the other answer options apply to them. With an “other, specify” option respondents will be able to provide contextual explanations of why the provided options did not apply to them.
In the example below, the survey question asks what additional features would make customers more satisfied with a product. The survey designer has included an “other, specify” textbox for respondents to provide additional features to the ones provided in the existing answer options.
By using text analysis to analyze the responses that have been input into the “other, specify” textbox, the researcher can conveniently summarize and report on the responses.
As responses are collected in this “other, specify” field, later versions of the survey could be updated to include the most popular answers that have been provided by respondents.
This strategy allows researchers to continually increase the effectiveness of their ongoing surveys, and gather data that may have never been uncovered otherwise.
What Survey Question Types Are Compatible with Text Analysis?
All open text fields in Alchemer surveys are available for bucketing in our Open Text Analysis tool.
The following survey question types are compatible with text analysis:
- Textbox List
- Questions with Other Textboxes
- Textbox Grid
- File Upload
- Textbox and Essay questions in Custom Groups, Contact Forms, and Customer Tables
- Question Comments
To learn how to navigate open text analysis, bucket responses, and report on findings in Alchemer, check out our documentation on open text analysis.