In this post, we share three compelling real life use cases that demonstrate the transformative impact of using watsonx and AI in yours business. From optimizing workflows to enhancing data-driven decision-making, these examples highlight how IBM watsonx is at the forefront of shaping the future. The use cases are based on the IBM Client engineering team's projects.
Use Case 1: Automatized Email Response Generation
Client Background: A highway company handles a significant volume of daily calls (300-500) and is overwhelmed by emails, particularly during peak seasons. Typical inquiries include:
- Duration of vignette validity.
- Requirements for a new vignette upon plate change.
- Possibility of a proportional refund for stolen plates.
Current Situation: Manual email responses, which are time-consuming and inefficient.
Solution: Deploy Watsonx.ai to create a Retrieval-Augmented Generation (RAG) solution. This AI system automatically generates email responses to common questions, enhancing customer satisfaction and reducing support center workload.
Pilot Scope: The project focuses on developing and implementing AI-powered automatic email responses to handle common customer inquiries more efficiently.
Use Case 2: Internal Email Classification
Client Background: A government institution with thousands of employees manages an internal help desk that receives numerous inquiries daily, such as:
- Issues with app features (e.g., document signing).
- Email archiving procedures.
- Password resets.
- Equipment malfunctions (e.g., toner issues in copiers).
Current situation: Emails are currently processed manually by staff who categorize and forward them to the appropriate departments. High staff turnover necessitates frequent training.
Solution: Implement an AI-driven email classification and ticketing system using Watsonx.ai and large language models (LLMs) to automate the categorization process, reducing manual workload and increasing efficiency.
Pilot Scope: Classify emails into four categories: Application, Email, User Account, and Equipment. The AI system processes sample emails to learn and accurately categorize future inquiries.
Results: The AI system achieved an impressive 91.48% accuracy in email categorization, demonstrating its effectiveness in reducing the manual burden on help desk staff.
Use Case 3: Marketing Personalization
Client Background: A leading European gas and oil company seeks to expand its business and become a premier retail digital and mobility partner.
Goal: Increase basket size in non-fuel products but find their single marketing strategy ineffective due to low conversion rates.
Solution: Utilize advanced analytics to segment customers based on specific behaviors and generate personalized marketing messages using AI.
Pilot Scope: Generate personalized marketing content for coffee promotions targeting the "Coffee-No-Buyer" segment through email and push notifications.
Implementation:
- Data Analysis: Use k-means clustering to identify key customer features and create subsegments.
- Prompt Engineering: Develop AI prompts for generating persona profiles, marketing emails, and push notifications.
- Integration: Deploy AI-generated content as API endpoints integrated with the client's marketing systems.
If you are interested in getting more details about this use cases, please contact us.