Employee Engagement Analytics
Employee Engagement Analytics
Employee Engagement Analytics
Leena AI's engagement survey product collected large volumes of employee feedback, but HR leaders had no reliable way to turn it into action. I led end-to-end design for an analytics and action-planning platform that closed that gap.
Leena AI's engagement survey product collected large volumes of employee feedback, but HR leaders had no reliable way to turn it into action. I led end-to-end design for an analytics and action-planning platform that closed that gap.
ROLE
Lead Product Designer
DURTION
4 months · Shipped to production
RESULTS
+50% dashboard adoption among HRBPs
+35% faster manager action-plan creation
Highlights
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why this mattered
Organizations were investing heavily in engagement surveys — but that investment was producing data, not change.
HRBPs couldn't spot trends fast enough to act before sentiment shifted.
Managers struggled to read what their own teams were signaling.
Leadership had no org-wide visibility into where problems were forming.
The result: a quiet trust deficit. Employees gave honest feedback expecting it to matter — and largely felt it didn't.
Organizations were investing heavily in engagement surveys — but that investment was producing data, not change.
HRBPs couldn't spot trends fast enough to act before sentiment shifted.
Managers struggled to read what their own teams were signaling.
Leadership had no org-wide visibility into where problems were forming.
The result: a quiet trust deficit. Employees gave honest feedback expecting it to matter — and largely felt it didn't.
The Problem
Every stakeholder needed something different from the same data:
Stakeholder | Core Need |
|---|---|
Employees | Trust that feedback leads somewhere |
Managers | Insight into their team, not just a score |
HRBPs | Org-wide trends, without manual cross-referencing |
Leadership | Strategic visibility without digging |
The real gap was between data availability and actionability — teams could see what happened, but rarely why, and almost never what to do next.
"I want actionable insights, not just metrics." — Manager "Employees want proof that their voice matters." — Research synthesis
Every stakeholder needed something different from the same data:
Stakeholder | Core Need |
|---|---|
Employees | Trust that feedback leads somewhere |
Managers | Insight into their team, not just a score |
HRBPs | Org-wide trends, without manual cross-referencing |
Leadership | Strategic visibility without digging |
The real gap was between data availability and actionability — teams could see what happened, but rarely why, and almost never what to do next.
"I want actionable insights, not just metrics." — Manager "Employees want proof that their voice matters." — Research synthesis
Research Summary
Combined stakeholder interviews, affinity mapping workshops, and existing survey-response analysis to map needs across all four groups, then clustered findings into major themes — crowded dashboards, no clear action path, inconsistent KPIs — and defined role-based access so each audience saw only what served them.
Biggest insight: the blocker wasn't a missing feature — every stakeholder needed a different lens on the same underlying data.
Benchmarked against Culture Amp, Qualtrics, and other engagement-analytics tools to separate table-stakes patterns from real differentiation.
Combined stakeholder interviews, affinity mapping workshops, and existing survey-response analysis to map needs across all four groups, then clustered findings into major themes — crowded dashboards, no clear action path, inconsistent KPIs — and defined role-based access so each audience saw only what served them.
Biggest insight: the blocker wasn't a missing feature — every stakeholder needed a different lens on the same underlying data.
Benchmarked against Culture Amp, Qualtrics, and other engagement-analytics tools to separate table-stakes patterns from real differentiation.
From Insights to Interface
Four features, each solving one part of the actionability gap:
Overview Dashboard — replaced scattered manual exports with one filterable view (tenure, department, location), so HRBPs spot trends without cross-referencing.
Topic Analysis — surfaced sentiment from open-text responses, turning buried feedback into a scannable signal.
Action Plan Generator — one-click, AI-suggested plans tied to the specific concern — closing the loop on "what do we do next."
Agentic AI Assistant — helps employees complete surveys and discover outcomes from their own past feedback, giving them visible proof their input leads somewhere.
Design principles throughout: simplicity & clarity, visual consistency, action-first — guidance never buried behind a click.
Four features, each solving one part of the actionability gap:
Overview Dashboard — replaced scattered manual exports with one filterable view (tenure, department, location), so HRBPs spot trends without cross-referencing.
Topic Analysis — surfaced sentiment from open-text responses, turning buried feedback into a scannable signal.
Action Plan Generator — one-click, AI-suggested plans tied to the specific concern — closing the loop on "what do we do next."
Agentic AI Assistant — helps employees complete surveys and discover outcomes from their own past feedback, giving them visible proof their input leads somewhere.
Design principles throughout: simplicity & clarity, visual consistency, action-first — guidance never buried behind a click.
Testing the Assumptions
Moderated testing with HRBPs and managers.
Summaries and one-click actions landed well; charts felt overwhelming and AI explanations read too robotic. Fixed by simplifying chart hierarchy, tightening microcopy, and adding plain "why" context next to every AI-surfaced insight.
Moderated testing with HRBPs and managers.
Summaries and one-click actions landed well; charts felt overwhelming and AI explanations read too robotic. Fixed by simplifying chart hierarchy, tightening microcopy, and adding plain "why" context next to every AI-surfaced insight.
Results & Impact
Metric | Improvement |
|---|---|
Dashboard adoption (HRBPs) | +50% |
Manager action-plan rate | +35% faster adoption |
Employee trust signal [ASK: confirm exact metric name/source] | +40% uplift |
Metric | Improvement |
|---|---|
Dashboard adoption (HRBPs) | +50% |
Manager action-plan rate | +35% faster adoption |
Employee trust signal [ASK: confirm exact metric name/source] | +40% uplift |
Retrospective
Splitting "insight" needs from "action" needs as two separate research tracks from day one — instead of discovering the split mid-project — would have gotten us to the Action Plan feature faster; it ended up being the most-used part of the product.
The harder lesson: visibility and trust pull in opposite directions. Leadership wanted org-wide sentiment visibility; employees needed confidence that granular feedback wouldn't surface their name. In a platform sitting between an individual and their employer, privacy isn't a feature to add later — it has to shape the data model from day one.
Splitting "insight" needs from "action" needs as two separate research tracks from day one — instead of discovering the split mid-project — would have gotten us to the Action Plan feature faster; it ended up being the most-used part of the product.
The harder lesson: visibility and trust pull in opposite directions. Leadership wanted org-wide sentiment visibility; employees needed confidence that granular feedback wouldn't surface their name. In a platform sitting between an individual and their employer, privacy isn't a feature to add later — it has to shape the data model from day one.