NOTE: Text Analytics is available for Engagement, Manager Effectiveness, Lifecycle (onboarding/exit) and Team Effectiveness surveys only. It is not available for Individual Effectiveness surveys.
Text Analytics is a set of tools backed by smart algorithms designed to help you get maximum insight from written feedback. You will find Text Analytics in the Comments Report, via the link in the reporting navigation. It:
- automatically classifies every comment into one or more of seventeen pre-defined high-level themes (like ‘leadership’, ‘work-life’ or ‘salary’ – see the full list)
- analyzes responses for sentiment (‘positive’, ‘negative’ or ‘neutral’)
- provides topic, sentiment, rating and question filters that allow you to slice and dice comments into the most useful subset
- visualizes all the comments in a bubble chart that gives you a bird’s-eye view of what people are saying and how they’re feeling
How to read the Topic Sentiment chart:
This chart combines topic and sentiment analysis to give you an immediately digestible view of all the comments in your survey.
The further to the right of the chart a topic appears, the more positive it is, and more negative topics appear on the left. Neutral or polarized topics sit closer to the center of the chart. The biggest bubbles represent the largest groups of comments, and the average sentiment line shows you whether, overall, comments in your survey are more positive or negative.
Hovering over any topic bubble will give you a quick view of the sentiment breakdown for the topic – particularly helpful in the case of more neutrally-positioned topics – along with the overall number of comments in that set.
The percentages shown on the bubbles represent the proportion of comments that this bubble represents.
How to use Comment Filters:
We have four additional ways to filter comments: by question, by topic, by sentiment and by rating. You can combine these filters to further narrow the comments in a set – for example, you might like to see negative comments left on positively-rated questions, or just the comments about ‘Salary’ in response to a specific question.
You can also apply standard demographic filters.
The Text Analytics report can be exported in CSV or Excel format. The Excel export contains a summary sheet in addition to a sheet of all comments and their classifications. Both CSV and Excel exports respect the currently applied demographic and comment filters.
Frequently Asked Questions:
Who can see this report?
The access to the Text Analytics report is the same as for the Comments report. If you allow comments access, then Text Analytics will be enabled as well.
Our algorithm is trained on over half a million pieces of employee feedback to recognize this set of common topics.
- Career: Career progress and development
- Salary: Compensation and benefits
- Learning & Development: Learning and development
- Collaboration: Inter and intra team collaboration
- Autonomy: Autonomy as individuals or team in making decisions
- Company Performance: General company performance
- Products & Services: Related to products and services offered by the company
- Innovation: Innovation / general improvements in products/services
- Communication: Management and general organizational communication
- Systems & Resources: Internal systems. processes and resources
- Environment: Aspects related to the workplace environment and facilities
- Feedback: Performance reviews and general feedback
- Recognition: Role and work recognition
- Leadership: Related to senior leaders and management in general
- Manager: Manager-specific comments
- Work Life: Work life balance
- Feeling Good: Short comments expressing positive sentiment
- No comment: Comments that are synonyms for ‘no comment’.
Can I reclassify comments that seem to have the wrong sentiment or topic attached to them?
Not yet, but this is something we want to enable soon.
Can I create my own custom topics?
Not at this time.
Are there benchmarks to help me understand whether my results are 'normal'?
We don't have benchmarks in the platform yet, but this article documents some of our findings including which topics are popular in which industries and regions, which topics people talk most negatively about, and which topics people talk most positively about, in general.
This feature is being gradually rolled out to customers, prioritising those with open or recently-closed surveys. Please contact firstname.lastname@example.org if you want to be among our first Text Analytics users.