Customer experience: how will generative AI strengthen emotion?

The greatest risk with AI is not embracing the technology and thinking that 'this does not apply to us'. AI will empower brands to deliver value and purpose more efficiently across the entire value chain and throughout the customer journey. However, it is crucial to first understand and pinpoint where and how AI can make a significant difference. 

Why such a rapid evolution?

Automation is not new in the field of customer experience, the first chatbots emerged decades ago, telephony has evolved significantly since the introduction of Interactive Voice Response (IVR) systems in the 1980s, and the partial automated processing of emails and mail has been effectively implemented in Customer Relationship Management (CRM) systems for over a decade.

However, Generative Artificial Intelligence (Gen AI), which is distinguished by its ability to create content, images, sounds or videos from data or instructions, is growing rapidly in companies for several reasons.

• Technological advances, particularly in deep learning and natural language processing, have been significant.
• The availability of massive quantities of data encourages companies to refine their operations, enhancing processes and decision-making.
• The rapid evolution of usage patterns: Today's increasingly connected and well-informed customers demand quick, personalized, and efficient services.
• The potential for automation, efficiency, and customization in customer relationships is substantial, and the implementation can be quick and simple.
• There is a significant wave of investment underway, evident in startup fundraising, transformation programs within large corporations, efforts to attract talent, and acquisitions by major tech companies. Notably, nearly three out of four business leaders are prioritizing AI to enhance their customer experience strategies.

What benefits does generative AI bring to the customer experience?

Generative AI can bring many benefits for the customer experience, including:

• Improve the customer's autonomy. Generative AI can provide faster, more relevant, more personalized responses, 24/7, using chatbots, voice assistants, proactive notifications or personalized contextual help. Generative AI can thus allow customers to solve their simple questions in self-care, which improves their satisfaction and confidence.
• Predict behaviors. Generative AI can analyze various and quantity data, such as their purchase histories, interactions, feedbacks, profiles, etc., to predict their needs, expectations, intentions or behavioral trends. Generative AI can thus anticipate customer requests, offer them personalized offers, retain them or win them back.
• Personalize customer journeys. Generative AI makes it possible to adapt interactions by analyzing customer data, providing personalized recommendations, contextualizing communications (content, style, tone,...) and adapting interfaces on applications (layout, color, etc.).
• Support employees. Generative AI can integrate AI into customer services to route calls, generate scripts, identify actions to be taken or provide additional information. Generative AI can thus facilitate the work of advisors, make them more efficient, more efficient and more satisfied.
• Improve overall performance. Generative AI can automate repetitive tasks, generate proposals for improvement for services and teams, hot or cold, using optimization, recommendation, scoring or segmentation algorithms. Generative AI can thus have an impact on the conversion rate, turnover, profitability or quality of service.

What are the priority use cases?

To date, the following are the primary applications in customer relations, listed in order of priority based on outcome:

USE CASE 1: Streamline customer interactions.

Generative AI can streamline customer interactions by generating qualification questions and recording responses through forms, chatbots, or voice assistants. For example, it can intelligently query customers to determine their needs, urgency, satisfaction, or emotional state, capturing these responses directly into a CRM or information system. This approach not only saves time but also enriches the database, providing valuable insights to enhance customer engagement strategies.

USE CASE 2: The context-aware personalized assistant

Via a virtual assistant, personalized webpage, or real-time tutorial, customers can resolve their issues independently. Generative AI can generate a web page or instructional video to assist customers in installing, using, or troubleshooting a product or service. It leverages tailored images, text, sound, and animations to provide clear and effective guidance.

USE CASE 3: Analysis of customer feedback

Through the analysis of unstructured data such as social media posts, customer reviews and emails, AI Generative makes it possible to analyze large volumes of conversation histories or customer reviews to feed the processes of continuous improvement.

USE CASE 4: The customer advisor's coach

Generative AI facilitates knowledge acquisition by generating real-time prompts and training advisors through voice recognition, speech synthesis, and natural language processing systems. For instance, it can monitor conversations between advisors and customers, suggest responses, offer rephrasing options, propose upselling opportunities, and assess communication quality.

USE CASE 5: Proactive notifications 

Generative AI can pinpoint at-risk customers—those experiencing technical issues, dissatisfaction, pending terminations, or unresolved claims—and proactively engage them to reassure, guide, resolve issues, and maintain their loyalty. For instance, it can send SMS messages, emails, or push notifications to update customers on their request status, propose alternative solutions, extend special offers, or ask for their feedback.