SOLUTIONS | Engagement
Level-Up Employee Engagement
Keep your people engaged through pulse and lifecycle surveys. Automatically pull data right from your survey tools into a database, streamling your analytics and reducing the time needed to convert insights into action! Powered by Snaplogic, the most powerful Integration Platform as a Service (iPaaS) technology on the market!
Engagement | Dashboard #1
Survey Data: Natural Language Processing (NLP)
This dashboard pulls the results from NLP models so the user can track near real-time sentiment changes and flag potentially problematic responses. Note that this sample is just the tip of the iceberg! Additional functionality can incorporate data from a variety of other sources, like your business operations datastore, enabling:
- Diversity and Inclusion comparisons, including statistical analysis
- Correlation of sentiment and monetized employee output
- Predictive modeling (e.g., retention probability, insider threat, employee performance)
SENTIMENT SCORE OVER TIME: The top timeline shows how sentiment scores change each quarter. Note that while the lowest sentiment score was logged during the outset of Covid-19, a negative trend had already started. So, disruption and stress related to the virus is not the only factor driving the organizational sentiment score down.
WORD CLOUD: At a glance, we can see the most common words in our response data. Note that the most popular words are about people and communication.
PULSE 2 (2020): The sentiment strengths show that the majority of responses for our most recent survey falls into a "good" category (green), some middling "neutral" (grey), and a minority in the "bad" (yellow). We should consider investigating response data for items in the "Fear" response area. This employee population might be feeling the results of a recent change, like a re-organization or Covid-19, and would benefit from additional support.
FLAGGED WORDS: Flagged words help identify potentially problematic reponses. While Lynette Roberts is just using hyperbolic language, Frank Emerson would benefit from direct outreach and intervention as the responses suggest gender bias may be at work. Likewise, Robert Luis may benefit from learning about medical accommodations.
Engagement | alternative word cloud
Survey Data: Word Cloud Alternative
This visualization allows a user to click through a hierarchy to see how different words are related to different sentiments. Click into any wedge to see subordinate data underneath and see relative frequency of each word.
Chart Legend:
- Center ring = highest level sentiment: good, bad, neutral
- Second ring = second level sentiment: positive, trust, fear, etc.
- Third ring = the words from the survey itself
Note: Clicking the white center of the circle will zoom the view back up one level per click!