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Paper Title

A SEMANTIC INTEGRATION FRAMEWORK FOR CONSOLIDATING UNSTRUCTURED FEEDBACK IN SALESFORCE KNOWLEDGE BASES

Authors

SB Vinay
SB Vinay

Keywords

  • Semantic Integration
  • Salesforce Knowledge Base
  • Unstructured Feedback
  • Ontology
  • Text Mining
  • NLP

Article Type

Research Article

Journal

International Journal of Customer Relationship Marketing and Management

Issue

Volume : 1 | Issue : 1 | Page No : 1-6

Published On

November, 2023

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Abstract

In modern customer service ecosystems, particularly within platforms like Salesforce, massive volumes of unstructured feedback—from emails, chat transcripts, surveys, and social media—remain underutilized due to semantic inconsistencies. This paper introduces a Semantic Integration Framework (SIF) aimed at harmonizing unstructured feedback into coherent, structured knowledge for Salesforce Knowledge Bases (SKBs). Leveraging ontology-driven natural language processing (NLP) and feedback classification, the framework supports real-time enhancement of customer service decision-making and self-service article generation. Experiments indicate a 35% improvement in retrieval precision and 25% enhancement in agent productivity when using semantically integrated knowledge versus traditional keyword-tagged repositories.

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