SaaS Case Study
A leading UK-based live chat SaaS provider partnered with Outsource Consultants to reduce rising CX costs while maintaining premium service expectations.
The results: $1.1M in labor savings, 98% CSAT maintained, and a fully self-funded AI deployment with no new budget approvals.
Results
- $1.1M
- Total Labor Savings
- 98%
- CSAT Maintained
- 90%
- QA Compliance
- 60
- Agents Supporting Live Chat Operations
Client:
Live Chat SaaS Provider
Industry:
SaaS
Deliverables:
The Challenge
The client, a UK-based live chat SaaS provider, faced rising CX operating costs while attempting to scale its support operation. At the same time, the organization needed to maintain premium customer experience standards.
The case study states that the client required a way to improve efficiency and scalability without introducing additional budget or capital approvals.
The Approach
Outsource Consultants led a phased transformation. In Phase 1, the client transitioned to a mid-market BPO and implemented tighter QA workflows. Staffing was reduced from 100 to 60 agents while maintaining service performance.
The labor and QA optimizations unlocked $1.1M in savings. In Phase 2, those savings fully funded the deployment of an AI chat solution using Natural Language Understanding to automate routine inquiries and reduce agent distractions.
The Outcome
The phased model delivered measurable operational and quality outcomes. The client maintained 98% CSAT and achieved 90% QA compliance following the changes.
Automation increased concurrent chat handling capacity and supported improved first contact resolution by allowing agents to focus on more complex issues. The AI investment required no new budget or capital approvals, as it was fully funded by Phase 1 labor savings.
Results:
- $1.1M labor savings unlocked
- 98% CSAT maintained
- 90% QA compliance
- AI deployment fully self-funded
FAQs
- How did the client fund AI without a new budget?
AI was introduced only after labor and QA efficiencies unlocked savings. Those Phase 1 savings fully funded the technology investment, eliminating the need for new approvals.
- What changed in Phase 1 before AI was introduced?
The client transitioned to a mid-market BPO and tightened QA workflows. Staffing was reduced from 100 to 60 agents while maintaining CSAT performance.
- Is this phased model applicable to other SaaS teams?
Yes. The approach is designed for organizations that want to reduce risk by funding CX technology improvements through operational savings rather than new spend.
- What’s the next step if I want to explore a self-funded CX model?
A CX Strategy Call helps assess whether labor optimization could unlock savings that fund AI or CX improvements without increasing budget exposure.
