To deliver crucial service metrics and build a true resolution system of record, service organizations need to begin capturing and harnessing “how” issues are resolved-the diagnostic that exists in your data and expert ecosystems. However, it is complex and spread out across numerous sources, including people and systems.
In complex customer service environments that support large catalogs of mission-critical products, service silos are inevitable. Call center support, Field Service, Engineering, Customer Success, Communities, and Self-service - all have different systems, data, and expertise. Technical accuracy is higher in Engineering, while significant tribal knowledge exists within Service.
Despite investments in search, CRMs, and data integration, these siloes, which have existed for decades, continue to proliferate. They negatively impact service by restricting the flow of knowledge between teams, which increases resolution time and escalation costs, steepens the learning curve for new service team members, and impacts customer satisfaction and renewals.
It is time for a new approach. Advances in AI and Natural Language Processing (NLP) technology make it possible to solve the silo problem by taking a diagnostic-centric approach to knowledge capture and sharing.
In this webinar, experts from Neuron7 will explain how taking a diagnostic-centric approach works, and how it quickly improves service metrics across all tiers of service. The webinar will cover:
- Why search and integration efforts have failed to solve the silo problem for decades.
- Are industry-best service metrics achievable in a siloed environment? (Spoiler: yes)
- A diagnosis-centric approach to knowledge capture & sharing across all service tiers – and Engineering.
- Creating knowledge (resolution paths) that Service & Engineering agree on.
- How AI & Natural Language Processing (NLP) enable the new approach.
Register now to learn from industry experts how you can enable the future of high-tech.