Loop Earplugs achieves 357% ROI and 25 FTE workload automation with Ada AI agent Aura
Loop Earplugs' rapid growth created overwhelming customer support demands—first response times stretched to 5–6 days during peak periods, ticket backlogs surged past 1,000, and scaling their BPO was resource-intensive with constant training, frequent hiring cycles, and high turnover.
Loop's prior support model—a BPO team combined with a scripted chatbot—could not handle the complexity and volume of incoming customer inquiries, especially during peak sales periods.
After launching Aura, Loop achieved a 357% return on investment, improved first response times by 194.52% to a maximum of 2 hours, and had Aura handle the workload equivalent of 25 full-time employees.
Even as sales grew 400% over two years, human-agent ticket volume fell by 33% and CSAT reached 80%.
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Frequently asked questions
What did this team achieve with this AI workflow?
After launching Aura, Loop achieved a 357% return on investment, improved first response times by 194.52% to a maximum of 2 hours, and had Aura handle the workload equivalent of 25 full-time employees.
What tools did this team use?
Ada, Aura, Ada Academy.
What results were reported?
Return on investment: 357%; FTE workload equivalent managed by AI agent: 25 FTE; CSAT: 80%; Improvement in first response time: 194.52% (source-reported, not independently verified).
What failed first in this deployment?
Loop's prior support model—a BPO team combined with a scripted chatbot—could not handle the complexity and volume of incoming customer inquiries, especially during peak sales periods.
How is this customer support AI workflow structured?
Customer inquiry submitted → Aura AI resolves inquiry → Invoice retrieval → Human agent escalation.