How Generative AI Is Transforming Customer Service?

Philippe Rostand is a Senior Consultant at Converteo, primarily involved in e-commerce and generative AI projects within the retail sector. With over twenty projects to his credit, he has the opportunity to work with our clients on strategic framing projects as well as on more operational support.

Key Takeaways:

• Customer service is a key differentiator in a context where customers are increasingly demanding.
• Generative AI is emerging as a solution capable of both improving the quality and speed of interactions.
• This technology also allows companies to shift from a reactive to a proactive approach in managing their customer service.

In an era where 79% of customers who have had a negative experience with a brand are ready to turn to competitors, customer service becomes a crucial factor for commercial differentiation.

At every stage of their journey, customers demand impeccable experiences and quick responses to their inquiries.

According to a Salesforce study, 64% of French customers prefer to purchase from companies that can meet their needs in real-time.

The advent of artificial intelligence (AI) and chatbots has also revolutionized the handling of certain interactions by allowing companies to offer continuous service to their customers.

This article will explore how Generative AI is enhancing customer service experiences today.

Key Challenges for Customer Service

A Customer Service Today That Is Often Impersonal and Mainly Reactive

80% of customers have interacted with a chatbot at some stage of their customer experience. One of the main challenges faced by these tools is the difficulty in providing relevant, natural, and personalized responses.

Indeed, chatbots generally rely on rule-based systems or traditional machine learning models. However, most of these systems have not yet achieved sufficient technological maturity.

To address these shortcomings, most companies also provide human agents to their customers. However, their numbers are often limited, and they consequently play a mainly reactive role: they intervene once a problem has arisen and following a customer request.

Slow Waiting and Processing Times

Waiting times are a common and significant concern for companies that care about delivering a good customer experience.

These delays can be partly explained by the high volume of requests, which often resemble each other, as well as the considerable time agents spend searching for and summarizing the necessary information to provide the expected assistance.

Generative AI currently has the potential to address some of the irritants listed above. A study conducted by MIT x Genesys even indicates that, by 2024, 90% of customer service managers expect to be assisted by generative AI solutions to improve their customer knowledge.

A Proactive and More Efficient Customer Service with Generative AI

Improving the Quality of Responses Provided to Customers

Generative AI models can handle complex requests more effectively through a nuanced understanding of intent and context. Integrating these models into existing chatbots or callbots allows for a deeper understanding of customer inquiries and the automated provision of more tailored and personalized responses. This ultimately leads to increased customer satisfaction and a reduction in agent intervention.

For example, Cdiscount has tackled this issue by collaborating with iAdvize. Their goal is to enable their chatbot to respond in natural language to any question posed by a prospect. Initial tests of this feature are already promising. On one hand, it enhances customer relationships with a satisfaction rate of 70%, which is three times higher than that of previous chatbots. On the other hand, it prioritizes the involvement of advisors in higher-value tasks.

Increasing Call Center Agents’ Capabilities

Generative AI models can assist agents in handling customer requests more effectively. They facilitate real-time understanding of requests, allowing for better prioritization of issues that truly require human intervention. Conversational assistants can enhance agent productivity by over 14%.

Bouygues Telecom is among the innovators utilizing Generative AI through their callbots. To date, the results reveal significant value for the company, with the customer autonomy rate rising from 60% to 90% for simple calls/needs.

Client Data Synthesis

Generative AI models also enhance the retrieval and analysis of customer data, including conversation histories, queries, emotional states, and customer feedback. This enables customer service teams to extract key information and identify recurring issues.

For instance, Qualtrics offers a solution that automates post-call summaries. Generative AI allows Qualtrics to synthesize the content of previous calls and create a clear history of the customer relationship. The promise for businesses is substantial: improving both customer and employee experience while achieving a 10% reduction in overall contact center costs.

Due to this technology, companies will be able to transition from a primarily reactive customer service model to a proactive one. 

The various use cases enabled by generative AI have the potential to significantly transform customer service roles. Companies that choose to implement such solutions will be able to enhance their operational efficiency and customer experience.

The full potential of generative AI can only be realized if it is tailored to the specific context in which it is implemented. Feel free to contact us to deploy this new technology securely within your organization. 

Contributors:

• Mathilde Lassalle: Data and Business Consulting Consultant
• Selima Bejaoui: Data and Business Consulting Consultant
• Mehdi Fenjiro: Senior Manager, Data and Business Consulting
• Charles Letaillieur: Senior Manager, Data Technologies
• Laurent Gourion: Manager, Data and Business Consulting