Survey analytics and filters

Great people analytics can help HR admins, managers, and executives to make informed decisions about your employees or workforce. Especially in bigger companies, filtering survey results becomes more important. With the new survey analytics, you can now use combinable filters that are applied after visibility filters and before further processing (e.g., segmentation) of results.

You can read more on how to interpret and work with the results here.

Filtering Logic

You can filter the list, heatmap, or comments by different parameters and also combine these filters. To prevent individual respondents from being identified with a combination of different filters, Leapsome will dynamically increase the anonymity threshold you have set once you apply more than one demographic filter (such as 'department' or 'manager'). This is also explained in the tool if you hover over the small triangle on the top right side of the survey results. 

In the heatmap, the filtering logic works as follows: If you filter for two or more of the same filter (e.g. two teams) Leapsome will apply an OR logic, meaning that it will show people who are either in Team 1 or in Team 2. If you combine different filters, e.g. a team and an office location, it will apply an AND logic. This means you would only see the answers that came from people who are in e.g. Team 1 and work in the London office. 

Filter and segmentation options

You can filter...

...the list 

• by survey round
• by question
• by category
• by team 
• by manager 
• by user level
• by office location
• by gender
• by age
• by user (if the survey is non-anonymous)
• by custom attributes

...the comments

• by team 
• by manager
• by survey round
• by sentiment
• by question
• by user level
• by gender
• by age
• by office location
• by conversation status
• by comment topic
• by user (if the survey is non-anonymous)
• by custom attributes

...the heatmap

• by team
• by manager
• by survey round
• by question
• by category
• by level
• by gender
• by age
• by office location
• by user (if the survey is non-anonymous)
• by custom attributes

You can also segment the heatmap

• by team
• by manager
• by performance quantile of the respondent (which takes the latest manager score of a review and groups survey respondents into quantiles)
• by tenure
• by office location
• by level
• by gender
• by age
• by custom attributes

For both list and heatmap you have the further option to sort the results by question, by category, or by total score across all questions for a specific group, location, or round for instance.