Customer Service Assistant
Business Need​
Empower customer service representatives with an AI assistant that provides instant access to solutions from historical support cases, reducing resolution time and improving consistency in customer interactions.
Solution Overview​
This solution uses Abacus.AI's Custom Chatbot to transform historical case data into an intelligent knowledge base:
Step 1: Ingest Historical Cases
- Data Source: Historical support case data is ingested from Salesforce using our native connector
- Data Structure: Cases include customer descriptions, agent responses, resolution steps, case categories, and outcomes
- Volume: 50,000+ resolved cases spanning 3 years of support history
Step 2: Data Preprocessing
- Python Feature Group: A custom Python feature group preprocesses raw case text to improve quality
- Text Cleaning: Removes formatting artifacts, standardizes terminology, and corrects common typos
- Text Rewriting: Uses an LLM to rewrite messy or unclear case descriptions into clear, concise summaries
- Metadata Extraction: Automatically tags cases with product areas, issue types, and resolution categories
Step 3: Build Custom Chatbot
A Custom Chatbot is configured with:
- Knowledge Base: The preprocessed case history serves as the primary knowledge source
- Response Generation: Synthesizes solutions from multiple relevant cases
- Citation: Provides links to original Salesforce cases for verification
How It's Used in Practice​
Customer service representatives leverage the Chatbot through the UI provided by Abacus.
During Customer Interactions:
- Service representative types a summary into the AI assistant
- Chatbot instantly retrieves 3-5 similar historical cases
- Service representative reviews suggested solutions and resolution steps and relays back to customer.
Example Queries:
- "Customer can't log in after password reset"
- "Billing charge showing twice on account"
- "Product feature not working on mobile app"
- "Request for refund on cancelled subscription"
Continuous Improvement:
- New resolved cases are added to the knowledge base weekly
- Service representative feedback helps refine retrieval relevance
- Common unresolved queries identify knowledge gaps