Hr ops · Production

Miro's peer feedback participation jumps from 50% to 93% in eight weeks using Zapier automation and AI-generated summaries

The problem

Miro's engineering peer feedback cycle had only 50% participation (roughly 400 reviews) because the formal HR system was painful: requesters received generic broadcast Slack messages pointing to unfamiliar HR software, reviewers could not see how many reviews they owed, and managers had to manually copy each review into a Google Doc one at a time.

Workflow diagram · grounded in source
1
Personal DM nomination
trigger
“A Zap reads from a Zapier Table, finds each engineer by their Miro email in Slack, and sends a personal DM. Not a broadcast. The message opens a Slack workflow: confirm your manager, select nominees from a dropdown, submit. That's the en…”
2
Scheduled nudges and self-check pull
integration
“Scheduled push messages for people with outstanding reviews, plus a pull mechanism: a pinned workflow in the engineering Slack channel where anyone can check their own status and submit. Google Sheets runs the conditional logic. Zapier P…”
3
AI summary generation
ai_action
“AI generates a summary from the verbatim responses.”
4
HTML email delivery
output
“Everything goes back as a formatted HTML email: summary up top, full feedback below.”
5
Workday batch upload
integration
“a batch upload pushes the data back to Workday. The core HR system never changed.”
6
Live adoption dashboard
feedback_loop
“Nick built a live adoption dashboard alongside the system, showing day-by-day completion rates. If a message wasn't converting, he adjusted in real time.”
7
Gemini Gem onboarding check-in
ai_action
“At week three, a Gemini Gem walks the manager through four expectation-setting questions. At every 30-, 60-, and 90-day milestone, the system resurfaces those original expectations so the manager evaluates progress against what they wrote.”
8
Off-track doorbell escalation
routing
“If a new hire is off track, the manager triggers what Nick calls the "doorbell": the system creates a thread with their People Business Partner, pre-loaded with all 90-day context.”
Reported outcome

Participation rose from 50% to 93% in eight weeks, and reviews grew from roughly 400 to over 1,600.
Each daily nudge lifted participation by roughly 10%.

Reported metrics
Peer feedback participation rate50% to 93%
Reviews submittedroughly 400 to over 1,600
Daily nudge participation liftroughly 10%
Participation rate (alternate quoted figure)43% to 93%
Show all 5 reported metrics
peer feedback participation rate50% to 93%
reviews submittedroughly 400 to over 1,600
daily nudge participation liftroughly 10%
participation rate (alternate quoted figure)43% to 93%
time to build and deploy feedback systemeight weeks
Reported stack
ZapierZapier TableZapier PathsGoogle SheetsSlackWorkdayGemini Gem
Source
https://zapier.com/customer-stories/miro
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Participation rose from 50% to 93% in eight weeks, and reviews grew from roughly 400 to over 1,600.

What tools did this team use?

Zapier, Zapier Table, Zapier Paths, Google Sheets, Slack, Workday, Gemini Gem.

What results were reported?

Peer feedback participation rate: 50% to 93%; Reviews submitted: roughly 400 to over 1,600; Daily nudge participation lift: roughly 10%; Participation rate (alternate quoted figure): 43% to 93% (source-reported, not independently verified).

How is this hr ops AI workflow structured?

Personal DM nomination → Scheduled nudges and self-check pull → AI summary generation → HTML email delivery → Workday batch upload → Live adoption dashboard → Gemini Gem onboarding check-in → Off-track doorbell escalation.

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