Feedback and Form Data Sentiment

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In addition to the Sentiment Overview analytics, the platform also provides more concentrated views of the sentiment within the business. Specifically, those with access to the analytics area can choose to view sentiment relating only to Forms, including individual forms, Goal Comments, Diary Notes and Performance Management Issues.

The value of this is that as the system administrator, you can really narrow down where the positive or negative sentiment is originating from. Is it the Goals that are causing negative sentiment? Is one particular form generating negative sentiment? Is positive sentiment being created through the use of diary notes for recognition?

Whatever the answers may be, your ability to identify the cause of sentiment will allow you to act on this information to provide a motivated and productive workforce.

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What are the value of Sentiment Forms?

There is a large number of form templates pre-loaded on your intelliHR platform and no limit to the number of forms that you can choose to add to capture an extremely wide variety of data on a range of topics. The purpose of 'Sentiment - Forms' is to provide an overview of the positive and negative sentiment analysis of form text data over time.

Keywords are gathered from completed employee forms. These are then weighted by significance and frequency so you can identify trending themes across your business. Although it may not be surprising if certain forms generate more negative sentiment than others. Whereas some forms; for example, those relating to achievements, may produce more positive sentiment. There may be discrepancies between what you would expect to find and what is actually the case.

The forms you employ on your platform should be drivers of greater employee engagement and to ensure this employees will need to understand the 'why?' - What value does the employee get out of completing the form? Both the tone of the questions and implications of the potential responses can affect the sentiment reported when completing the form. Thus it is sentiment which is the key indicator of a successful form design and will help you gain sight over the important data you require or perhaps if your data is being disadvantaged due to issues with the form design.

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Using the Feedback and Form Data Sentiment in Analytics

1. Reporting Period: Choose the period you wish to report on using the calendar at the top right of the screen.

2. Cross-filtering: You can cross filter your data to provide more specific insight into the sentiment related to performance management issues.

• Average Sentiment Score by Month: presents the average sentiment, as recorded in forms, over the past year by default upon opening the report. Keywords gathered from completed employee forms completed are weighted by significance and frequency so you can identify trending themes across your business.
• Form Design: The name of the form where the sentiment originated. This is particularly useful to identify if specific forms are causing particularly positive or negative sentiment.
• Form Category: The category of the form where the sentiment originated. This can be a valuable tool providing insight over the sentiment generated by different form categories. For example, if compliance or performance forms consistently produce negative sentiment this may be an opportunity for the business to improve via strategic intervention.
• Sentiment Score Distribution: The distribution of sentiment across all the responses gathered from completed forms.
• Business Unit / Supervisor / Pay Grade / Gender /Work Type / Tenure: using any of these cross filters will let you investigate specific groups within your organisation to see if positive or negative sentiment is directly correlated with employees meeting the criteria identified by your use of filters. If sentiment in any of these areas is significantly more positive or negative than average these anomalies can then be investigated further.
• Row Data: The row data provides every instance of data generated by the sentiment in the forms over your specified time period. The strength of the row data is that each row links back to the original comment where the sentiment originated allowing you to pinpoint the exact sentence that created the sentence.

Example - Deep Dive into Sentiment:

By cross-filtering in the Feedback and Form Data Sentiment analytics it's possible to pinpoint both specific issues and trends within your business.

In the video it's possible to see how in this area of analytics we can instantly see that the Check-In form has been generating significant negative sentiment recently. We can also see that the majority of this negative sentiment is originating from the Customer Success Team.

Through filtering: first, which form the sentiment is originating from and, second, cross filtering this with the business unit the sentiment has come from the analytics suggest there may be an issue in that specific business unit this month.

Using the row data we can then view the comments that created the negative sentiment and can clearly see there is an issue with the WIFI in the office where this business unit is located.

What could have become a significant issue with an impact on employee happiness and also customer relations can now be resolved quickly as the business now has the actionable insight necessary to take steps to resolve the issue.

Tip: For a reminder of how to filter in analytics please see How to use filters in Analytics. For a more in depth look at how to get the most out of your form designs please refer to the article How can I get the most out of my Form Designs. In addition, please contact our customer success team who will be happy to help you with your form designs.