Lebara

Bringing Empathy into Customer Service Experience

Lebara embarked on an ambitious project to redefine the capabilities of its conversational chatbot assistant. The aim was not just to automate customer interactions but to revolutionise them with the power of LLMs (Large Language Models) and AI/ML. For this initiative we were supported by OneReach, a US-based pioneer in conversational design platforms, whose low-code/no-code approach enabled us to concentrate on delivering unparalleled customer experiences.

Role

Group Head of Product Design

Teams involved

‣ Product Design
‣ Product Management
‣ Engineering
‣ Customer Service

Timeline

Sep. 2022 ⇢ Jun. 2023

1. The Challenge

Lack of Empathy & Erosion of Customer Trust

For too long, conversational chatbot assistants were seen more as cost-saving tools rather than truly customer-centric solutions. Their primary function seemed to be trapping customers in automated processes to reduce customer service calls and costs.

This approach often led to frustration and dissatisfaction, eroding trust in digital assistants. Recognising this gap, we were determined to create a solution that genuinely focused on user needs, providing real and significant assistance to our customers.

By prioritising the user experience, we aimed to restore and enhance the faith of our customers in digital assistance, making it a preferred point of contact for their service needs.

2. The Vision

From Service Bureau to Product Ecosystem

Our goal was to develop an Omnichannel solution capable of responding to any input (voice, text), through any channel (phone, email, WhatsApp, chatbot, etc.), and in multiple languages (English, Dutch, French, and others).

This solution would offer a level of precision and speed that could sometimes even surpass human capabilities. It was a bold vision that required a significant amount of preparation, learning, and gathering of technical requirements, including insights from customers who had lost faith in chatbots and virtual assistants.

To achieve this, we embraced a collaborative and iterative approach, bringing together a multidisciplinary team specialised in AI, Product design, Conversational Design, and Customer Service. Our aim was to create a seamless and intuitive user experience, one that feels natural and engaging, breaking away from the rigid and impersonal interactions often associated with traditional chatbots.

2. The Strategy

Our strategy centered around creating a customer-first solution. We decided to leverage the latest in LLMs and AI technology to provide a service that could adapt to various customer needs. The strategy also included a roadmap for integrating the virtual assistant across all customer touchpoints to ensure a consistent and seamless user experience.

The strategic phase also involved identifying key partnerships and technologies that would be crucial in achieving our goals. We engaged with OneReach, a leading Conversational AI solution and forged a partnership to ensure our solution was built on a foundation of cutting-edge technology. This allowed us to leverage external expertise, ensuring that our solution was not only innovative but also scalable and sustainable.

Planning

The planning phase was foundational in setting the course for our project. It involved defining clear objectives, setting timelines, and allocating resources. Key stakeholders from various departments, including IT, customer service, and marketing, were brought together to align on the project’s goals. This phase also included identifying the KPIs that would help us measure the success of our virtual assistant.

In addition to setting the project’s course, our planning phase involved meticulous risk assessment and contingency planning. We established a clear communication plan to ensure all team members were continuously aligned. Regular check-ins and agile methodologies were adopted to allow for flexibility and adaptability as the project progressed.

Research

In the research phase, we conducted extensive market analysis and customer surveys to understand the needs and preferences of our user base. We also studied current trends in AI and chatbot technology. Insights from this research helped us in crafting a solution that was not only technologically advanced but also deeply resonant with our customers’ expectations.

We also conducted in-depth competitor analysis and technical feasibility studies. This comprehensive approach allowed us to anticipate market trends and position our virtual assistant as a leader in the field of customer service technology, setting a new benchmark in the industry.

Design

The design phase involved creating a new user interface and experience for the virtual assistant. The Product Design team, along with Product Manager, AI engineers and Customer Service teams, worked on crafting an interface that was intuitive, engaging, and easy to navigate. We focused on ensuring that the assistant could handle queries in a conversational, empathetic manner, making the interaction as human-like as possible.

During the design phase, we also conducted a series of user testing sessions to validate our designs. These sessions provided invaluable feedback directly from potential users, enabling us to refine our user interface and experience to better meet customer needs. This user-centered design approach was pivotal in creating a virtual assistant that resonated well with our users.

Optimisation

Optimisation was an ongoing process. As we developed the assistant, we continuously tested and refined its capabilities. This involved tweaking the AI algorithms for better understanding and response accuracy, improving the user interface based on user feedback, and ensuring the system’s scalability and security.

The optimisation phase was characterised by a strong focus on data-driven decision-making. By analysing user interactions and feedback, we were able to make informed adjustments to our AI algorithms and user interface.

1. The Impact

Increased Service Efficiency, Improved Customer Satisfaction

Lebara’s implementation of the AI-based digital assistant using LLMs has led to remarkable improvements in customer service efficiency and satisfaction.

Increased Customer Satisfaction

Within the first three months post-launch, Lebara’s average Trustpilot score rose from 4.1 to 4.4.

Reduced Customer Service Calls

28% reduction in calls to customer service specialists within one year from launch

Significant Cost/Call Reduction

The reduction in calls resulted in a cost reduction of 5 million pounds annually across all markets.

Improved Time-to-Market

The time required to develop new conversational flows decreased by 40%, thanks to a more efficient platform.

5. Final reflections

Leadership Lesson

TBD

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