Leading high tech organizations are competing against each other to increase market share while dealing with slim operating margins, high capital expenditures, shorter product life-cycles and global supply chain management.
They are increasingly aware of the need to differentiate themselves by offering quality products at a reasonable cost with excellent technical support and customer service. Yet as products become more complex and market competition increases, organizations are concerned that organizational efficiency and support costs will consume already thinning profit margins.
One major software company identified technical support as a key competitive differentiator but struggled to close support calls quickly because staff had trouble finding the information they needed. As a result, incidents that should have been closed with a single call were extended.
By leveraging the power of Semaphore’s ontology management, auto-classification and semantic enhancement services, documentation, manuals, knowledge-base entries and support history information spread throughout the enterprise were unified under a single vocabulary. The model was leveraged and combined with Natural Language Processing, entity, fact and relationship extraction to enrich each asset with precise and consistent metadata, which identified the relevant products, topics, solutions and documentation customer support required to quickly respond to customer queries. Today technical support closes more incidents during the first call, customer satisfaction has increased and technical support costs are reduced.
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