Lead processing ·

Superhuman scales marketing and support operations with Zapier automation

The problem

Superhuman's marketing team manually synced leads from LinkedIn with errors and handled opt-out requests tediously, while the small support team lost hours to copy-pasting between tools and manually logging dev escalations.

Workflow diagram · grounded in source
1
Lead arrives from platform
trigger
“sync leads from platforms like LinkedIn”
2
Data enrichment and routing
integration
“automated lead routing, enriching data and managing sync limits with features like time delays and queues”
3
Opt-out detection and processing
integration
“built a Zap to detect and process email opt-out requests automatically”
4
Support agent tags conversation
trigger
“Support agents can tag conversations in Intercom to instantly log key details”
5
Dev escalation and notification
output
“trigger dev escalations, and notify engineering—no manual steps required”
Reported outcome

Automation cut lead sync errors by 87% and improved plan efficiency by 31%; each support agent now saves an hour a day, reclaiming six hours of daily productivity across the team, while Superhuman maintains over 90% CSAT.

Reported metrics
Lead sync errors87%
Plan efficiency31%
Support agent time saved per dayan hour a day
Daily productivity reclaimed across teamsix hours
Show all 5 reported metrics
lead sync errors87%
plan efficiency31%
support agent time saved per dayan hour a day
daily productivity reclaimed across teamsix hours
CSATover 90%
Reported stack
ZapierLinkedInIntercom
Source
https://zapier.com/customer-stories/superhuman
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Automation cut lead sync errors by 87% and improved plan efficiency by 31%; each support agent now saves an hour a day, reclaiming six hours of daily productivity across the team, while Superhuman maintains over 90% C…

What tools did this team use?

Zapier, LinkedIn, Intercom.

What results were reported?

Lead sync errors: 87%; Plan efficiency: 31%; Support agent time saved per day: an hour a day; Daily productivity reclaimed across team: six hours (source-reported, not independently verified).

How is this lead processing AI workflow structured?

Lead arrives from platform → Data enrichment and routing → Opt-out detection and processing → Support agent tags conversation → Dev escalation and notification.