customer_support · finance · workflow

PayShepherd cuts response times by 40% and achieves 100% CSAT with Intercom

PayShepherd's existing Jira Service Management platform was overwhelmed by a fast-growing customer base, causing delayed responses, decreased customer satisfaction, poor reporting visibility, manual workflows, and difficulty tracking complex tickets that frequently duplicated effort across agents.

How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Customer contacts via help center or chatbot
Customers initiate support interactions through Intercom's help center and chatbot.
Tools used
IntercomJira Service ManagementFin AI Agent
Outcome

Implementing Intercom delivered a 40% reduction in response times, 100% CSAT in March 2024, a 15% improvement in operational efficiency, a 30% decrease in duplicate tickets, a 20% increase in help center engagement, and 30% of routine support tasks now handled by workflow automations.

What failed first

Jira Service Management lacked robust reporting, required manual workflows, and had no clear mechanism to track complex long-running tickets, resulting in duplicated agent effort and customer frustration.

Results
Time saved40%
Volume20%
Source

https://www.intercom.com/customers/payshepherd

How we source this →

Grounding & classification
Source type: vendor customer story
31 fields verified against source quotes.
chatbotconversational aiknowledge basesupport ticketfailure mode describedhuman review describedmetric backednamed customerproduction runtime claimedtools describedworkflow describedsoftwareautomation ratecustomer satisfactionemployee productivityerror reductionresponse time reductionvendor customer storycustomer supportticket triageautonomous resolutionescalation workflow