Employee Engagement & Feedback

AI summarizes employee feedback from surveys, reviews, and meetings so HR and managers can spot themes and act on them.

Business impact

• Survey participation rate — Sojern reported that participation rose to nearly 100 percent after using Glint.
• Employee engagement during meetings — Access Holdings said staff engagement during meetings increased by about 25 percent.
• Employee engagement during calls — Humana reported a 63-percent increase in employee engagement during calls.
• Customer satisfaction — Humana reported a 28-percent increase in customer satisfaction alongside real-time coaching.

Data requirements

• Employee survey responses (text) — Used to measure engagement and collect concerns or improvement ideas.
• Performance-review comments (text) — Used to synthesize themes and create manager-specific action plans.
• Meeting chats and emails (text) — Used to summarize internal communication and surface action items.
• Call audio and conversational cues (audio) — Used to detect tone changes and overlaps for real-time coaching.

AI methods and techniques

• Natural language processing — Used to analyze employee comments and extract themes from open-text feedback.
• Machine learning — Used in predictive alerts and pattern detection across employee data.
• Predictive models — Used to flag employee populations at risk of attrition or lower performance.
• Summarization — Used to condense performance-review feedback, meetings, chats, and emails into usable summaries.
• Conversational cue detection — Used to detect tone changes and overlaps in live calls and trigger coaching prompts.

Industries

Real-world evidence

4 documented case studies on record.

Companies using this: DoorDash, Sojern, Humana Inc., Access Holdings Plc.