Engage ANALYTICS

advanced analytics for actionable insights

Advanced, drill-down survey analytics dashboard that will allow you to filter, compare, and analyze employee feedback and survey results across time, business units, and demographics.

Translate employee feedback into insights

Understand the trends in employee engagement from the biggest picture to the smallest detail:

• Employee feedback and survey results are mapped to business units according to the organizational structure as captured or defined when setting up the survey;
  
  
• Convenient print/PDF-ready summary reports of survey results, including top/bottom scoring survey questions and scores per demographic;
  
  
• Deep-dive into the survey results by setting filters for any combination of demographics, business units and engagement levels, e.g.  all Male respondents in the 21 - 26 age group (demographics) who work in either the Finance or Marketing departments (business units) and who fall in the Disengaged group (engagement level).

Target the issues that drive change

Compare, segment, and analyze the survey results in a number of different ways:

• Side-by-side comparisons of survey question scores per survey dataset, business unit, and demographic;
  
  
• Compare against previous surveys or against survey results imported from other survey platforms, or against benchmark data to see how your organization stacks up;
  
  
• Full confidentiality and anonymity for all survey respondents – no survey results will be displayed for any business unit with less than 4 responses;
  
  
• Generate advanced color-coded heatmaps – based on the survey scores per business unit - for any combination of survey constructs and survey questions, and add a demographic filter to display the survey results according to selected demographic attributes.

Add depth, context, and understanding

Use the powerful text analytics function to gain insights into the meaning of open-ended and free-format (qualitative) comments:
  

• Filter qualitative (open-ended) survey responses and comments according to business units, demographics and/or engagement levels;
  
  
• Apply Natural Language Processing (NLP) techniques to identify the common topics, themes and sentiments (emotional tone);
  
  
• List or sort open-ended comments according to their relevancy or sentiment scores, and do keyword searches within topics;
  
  
• View keywords in a word cloud or sorted according to keyword frequency, and do advanced keyword searches with partial or exact matching.