What started as a digital experience rebuild for a Lebara, a European MVNO, turned into an AI transformation in customer service delivery, with around 1.4 million automated interactions, resolution up 19 points, and a foundation ready for generative AI.
━ Delivered Result ━
Key Outcomes Between 2022-2024
Customer interactions via agent & chat channels
Year-on-year growth in agent/chat usage
Containment rate — approximately doubled
Resolution rate up by approximately 19 percentage points
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Reduction in overall customer service costs despite an increase in customer base
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Reduced pressure on contact centre operations, freeing agents for higher-value interactions
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Improved scalability across multilingual European markets
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Foundation in place for AI- and LLM-enabled customer engagement at scale
About the Engagement
Lebara is a mobile virtual network operator serving customers across the United Kingdom, France, Germany, Denmark, and the Netherlands, with a customer base spread across multiple languages and service contexts. In 2022, Lebara engaged M.M. on a digital transformation programme to reimagine its digital customer experience across web and mobile.
The engagement ran on M.M.’s Teams as a Service (TaaS) model: an embedded specialist team providing the digital, technical, and transformation capability needed to support Lebara’s wider modernisation agenda.
While reviewing the end-to-end customer journey, the team identified the contact centre (and specifically the existing chatbot) as a high-impact area that could materially improve the customer experience and reduce operational pressure through AI adoption. That observation reshaped the programme beyond the initial web and mobile rebuild.
“MM operated as an extension of our team, bringing the right mix of architecture, digital delivery, and customer experience capability. Their Teams as a Service model gave us access to specialist expertise at the right time and helped us transform our chatbot into a high performing customer-service capability.” – Chris Miles, Group Head of Conversational Products, Lebara.
The Challenge
Lebara’s existing chatbot supported basic automation, but it had been built on a Microsoft Bot Framework / low-code style setup and was largely flow-based, with scripted decision trees and limited language understanding underneath them.
From a customer experience perspective, the bot only supported basic interactions, significantly limiting the total number of deflections.
From an operational perspective, the limitations went deeper:
- The chatbot was treated mainly as a contact centre cost-saving tool.
- Customer service teams could not easily update or optimise bot journeys themselves.
- Multilingual support across European markets was difficult to manage on the existing platform.
- Even small changes required developer involvement, slowing down business responsiveness.
- The platform offered no clear path to AI-enabled customer service.
Lebara required a more scalable foundation that could carry multilingual, AI-enabled customer service at the volume and pace a fast-growing regional MVNO requires.
The Solution: An Embedded TaaS Team That Looked Beyond The Original Brief
M.M. provided the specialist digital, technical, and transformation capability the programme needed through a dedicated extended team.
The pivotal moment came when M.M.’s Technical Architect surfaced the platform’s limitations and turned them into a structured recommendation: the existing setup could be upgraded to provide connected customer experiences and localised support.
The dedicated team:
- Reviewed the existing chatbot architecture, operating model, and platform limitations in detail.
- Identified scalability, multilingual, and maintainability constraints, and made the business and technical case for change.
- Engaged customer service and business stakeholders to align on the customer experience opportunity.
- Prepared a detailed technical and business recommendation for a new platform direction.
- Supported the MVNO’s RFP process to evaluate alternative conversational AI platforms.
- Enabled the transition to a more scalable platform, with focus on measurable outcomes — containment, deflection, resolution, and customer experience.
The client decided to adopt a OneReach.ai, which offered a stronger foundation for multilingual customer service automation and future generative AI integration. M.M.’s dedicated team proceeded to build the AI agent using the platform.
Lebara’s Customer Service Gains From AI
By 2024, the AI agent and chat channels had become a meaningful part of Lebara’s customer service operating model and a core part of how customers were served at scale.
The headline numbers from Lebara’s new digital customer experience include:
- Approximately 1.4 million customer interactions handled through agent and chat channels.
- Around 62% year-on-year growth in bot/chat usage.
- A significant increase in agent adoption and channel mix overall.
- Containment rate approximately doubled — a meaningful lift in the share of queries resolved without human escalation.
- Resolution rate up by approximately 19 percentage points.
- Improved deflection from traditional contact centre channels, and reduced pressure on contact centre operations.
- Reduction in overall customer service costs, despite an increase in customer base.
- Localised support across multilingual European markets.
- A platform foundation ready to extend into AI- and LLM-enabled customer engagement.
That is the practical value of an experienced, dedicated team extension. Our multi-disciplinary team spent time inside the client’s product and operations, uncovered opportunities to increase the scope – and had the standing to raise it, build the case, and help reshape the programme around it.
In Lebara’s case, that meant uncovering a service automation opportunity that may have remained hidden inside the contact centre environment.
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