AI & CX
Vodafone AI Chatbot
Outcomes
The context
Vodafone's customer care teams handled enormous volumes of repetitive queries. The business invested €1.2m to leverage emerging AI capability — and needed someone to turn that investment into a product customers would actually choose to use.
The problem
Customers abandoned self-service because it felt like a dead end. Containment without satisfaction just hides failure — the goal was resolution customers preferred.
What I did
- Modernised a traditional team to agile ways of working.
- Built the product vision and roadmap bridging business objectives with AI capability.
- Wrote user stories and specifications through cross-functional collaboration.
- Established a voice-of-the-customer programme pre- and post-launch whose insights were adopted by multiple departments.
- Coordinated a dedicated design/development test team to ensure seamless API integration.
- Presented monthly to C-suite executives.
Key decisions & trade-offs
- Prioritised the highest-volume, highest-frustration query types first rather than the technically easiest.
- Held deployment dates by cutting scope, never quality.
- Measured success on customer outcomes (NPS, retention) rather than deflection alone.
Results
€800k annual savings in year one, NPS up 20%, retention doubled from 40% to 80%, and 70% query containment — recognised with the 2023 Innovation of the Year Award at the Irish Loyalty & CX Awards.
What I'd do differently
2026 postscript: built today, I'd design this on LLM foundations rather than intent-tree architecture — richer conversational repair, retrieval over knowledge bases, and evaluation loops instead of hand-tuned flows. The product discipline — voice of customer, containment with satisfaction, C-suite transparency — would stay exactly the same.