Unlocking the Power of Generative AI in Marketing & Customer Experience

Generative AI is already profoundly influencing Marketing and Customer Experience practices and methodologies, delivering substantial benefits to clients, corporations, and employees alike.

Generative AI has already been integrated into numerous companies as a tool to enhance internal processes and employee activities. This significantly benefits clients by providing seamless, omnichannel, and highly personalized experiences, culminating in a more gratifying customer journey.

Marketing

• AI-Driven Creative Design & Rapid Prototyping
• Virtual Product Optimization Through AI Simulations​
• Crafting Hyper-Personalized Content at Scale​
• Tailoring Messages and Offers with Precision
• Automated Generation of Customized Performance Reports​

Customer Experience

• Dynamic Customer Segmentation Powered by AI​
• Automated, Context-Aware Customer Responses​
• AI-Driven Analysis of Customer Dissatisfaction Root Causes​

1/ We highlight the most implemented AI use cases across our benchmarked companies:

• 54% have deployed a voicebot that generates personalized answers either based on FAQs or with personalized answers tailored to specific customers
• 40% have deployed a chatbot capable of generating personalized responses using FAQs or a knowledge base
• 33% leverage generative AI to design and dynamically adapt user interfaces (UI) optimized based on user preferences and best ergonomic practices

2/ We identify the three fastest-growing generative AI use cases by our clients:

• 43% are implementing the call summary generation, to automatically transcribe, analyze, and summarize key points from a customer call
• 25% are working to generate automatic reports to identify dissatisfaction causes and recommendations for corrective actions
• 21% are developing “augmented advisor” features to analyze live conversations and provide advisors with contextual recommendations  

We offer a step-by-step methodology with an in-depth analysis to ensure the end-to-end implementation of these use cases, with recommendations on the most relevant market tools and the prerequisites:

• Data prerequisites to ensure the deployment of generative AI use cases
• Technical prerequisites on the implementation environment to facilitate the integration of generative AI use cases

During the initial framing of your project:

• Conduct a rapid assessment of your data maturity level, existing processes, and associated technical environment, along with a feasibility study on the relevance of implementing the proposed use case
• Define your target operational model for knowledge management and collaboratively develop the project roadmap: organization, processes, tools, and governance at both local and central levels

During the design phase:

• Design customer journeys impacted by the generative AI use case to be implemented
• Specify business requirements and map the affected functional and application domains
• Provide technical specifications and map the applications and data impacted
• Select the optimal solution to address your business needs and organizational and technical constraints

Throughout the execution and implementation of the use case:

• Manage the deployment of the tool and operational model dedicated to the generative AI use case
• Conduct change management to ensure adoption and the value generated by the newly implemented model

Contact us to receive the detailed presentation of our study!