Makesy improves customer service self-service and response times with Kustomer
Makesy's customer service team was hampered by a disorganized previous CRM (Gorgias) with no visibility into agent availability, requiring agents to manually select messages, manually send bulk emails, and lacking the brand-voice customization and tagging clarity the team needed.
Gorgias, Makesy's previous CRM, had a confusing tagging system that made it impossible to accurately determine why customers were reaching out, and offered no insight into agent availability or scheduling.
After adopting Kustomer, the conversational assistant resolved 48 tickets in the first week without agent involvement, growing to 71 within three months.
Makesy's agents are no longer overwhelmed and the team has received higher customer reviews.
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Frequently asked questions
What did this team achieve with this AI workflow?
After adopting Kustomer, the conversational assistant resolved 48 tickets in the first week without agent involvement, growing to 71 within three months.
What tools did this team use?
Kustomer, Knowledge Base, conversational assistant.
What results were reported?
Tickets auto-resolved (first week post-launch): 48; Tickets auto-resolved (within three months): 71; Self-service capability: Improved self-service capabilities; Overall response times: Decreased overall response times (source-reported, not independently verified).
What failed first in this deployment?
Gorgias, Makesy's previous CRM, had a confusing tagging system that made it impossible to accurately determine why customers were reaching out, and offered no insight into agent availability or scheduling.
How is this customer support AI workflow structured?
Auto-route to agent inbox → Ticket limit enforcement → Conversational assistant self-service → Review-driven feedback loop.