Reported impact
Business outcome
Nexon raised customer satisfaction to 96%, made onboarding dramatically faster, and improved agent productivity by about 14% by automating routine support work.
- Customer Experience
- Productivity Improvement
ServiceNowSoftware / SaaSCustomer Service AutomationAI and Machine LearningData AnalyticsData PlatformCustomer ExperienceProductivity ImprovementUndated ServiceNowSN#1f8476Software / SaaSAsia PacificNexon was working across fragmented service tools that limited visibility, slowed onboarding and support, and made it harder for agents to deliver proactive customer care.98% Faster onboarding for new customersModified · Jul 30, 20265Customer Service AutomationCustomer Service Management · Knowledge Base · Predictive Intelligence0 2026-07-30 5
Nexon Asia Pacific
Customer Service Automation
Nexon was working across fragmented service tools that limited visibility, slowed onboarding and support, and made it harder for agents to deliver proactive customer care.
98% Faster onboarding for new customers
AI helps IT agents be ~14% more productive
Nexon Asia Pacific elevates CSAT score to 96% with unified AI experience
~14% Raise in agent productivity
Solution
Nexon was working across fragmented service tools that limited visibility, slowed onboarding and support, and made it harder for agents to deliver proactive customer care. Nexon Asia Pacific implemented a ServiceNow-centered stack built around ServiceNow AI Platform, Customer Service Management, Virtual Agent, and Predictive Intelligence. Key components included ServiceNow AI Platform provides the common workflow and AI layer; Customer Service Management manages customer-support cases and self-service; Virtual Agent handles conversational self-service; Predictive Intelligence classifies and routes work. Requests enter through Virtual Agent, are classified or summarized by Predictive Intelligence, and uses context from Knowledge Base before ServiceNow AI Platform and Customer Service Management routes or fulfills the work. Updates then flow back to agents, account teams, or customers through the same connected experience.
Data flow
Requests enter through Virtual Agent, are classified or summarized by Predictive Intelligence, and uses context from Knowledge Base before ServiceNow AI Platform and Customer Service Management routes or fulfills the work. Updates then flow back to agents, account teams, or customers through the same connected experience.
Solution architecture
- Compute
- Predictive Intelligence Classifies, routes, and prioritizes work using machine-learning models.
- Storage
- Knowledge Base Stores reusable knowledge content that search and assistants reference during support.
- Serving
- Virtual Agent Handles conversational self-service and ticket deflection for users.
- Orchestration
- ServiceNow AI Platform Acts as the common workflow and AI platform that unifies service data, automation, and user experiences.
- Customer Service Management Coordinates customer-support cases, self-service, and agent work on one platform.
Architecture clues
- Knowledge content is reused as a source for self-service or AI-assisted answers.
Evidence from the source
By consolidating fragmented tools into the ServiceNow AI Platform , Nexon now has a fully integrated, scalable, and secure platform to track service performance and improve resolution times
Now Assist for Customer Service Management that helps Nexon elevate its CSAT score to 96%, using a unified AI experience
Shayne adds: “By having a unified view of call history and agents’ interactions via Agent Assist in Service Operations Workspace, we have accelerated ticket assignment and resolution time by another 10%.” Beyond faster resolutions, the improved efficiency puts the internal IT service desk in a position to be proactive rather than reactive
With over 6,000 monthly tickets, scaling without compromising its high-touch customer care model had become complex and costly
“This frees up time to handle more complex requests, and has led to a 13.8% increase in agent productivity
Transparency Evidence & methodology
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
How scores are calculated
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Customer reference value95/100
- Problem clarity20/20Measures whether the customer's operational problem is specific enough to compare.
- Implementation depth20/25Rewards named components, data flow, integrations, and architecture detail.
- Outcome specificity20/20Measures whether the reported benefit is concrete rather than a generic claim.
- Quantified impact25/254 metrics describe measurable impact.
- Deployment scale10/10Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence79%
- Source authority20/25The main evidence is an official vendor-published customer story.
- Claim traceability21/2510 of 12 key fields link to a named source.
- Direct evidence20/205 direct source quotes retained.
- Date provenance0/10The publication date has no documented provenance.
- Source transparency8/101 source reference document publisher, URL, authority, retrieval, and supported fields.
- Implementation specificity10/10Rewards source-backed components, data flow, quantified impact, and a specific outcome.
Traceability
Sources & provenance
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
- https://www.servicenow.com/customers/nexon.htmlServiceNowFirst-party
Nexon Asia Pacific customer story
Supports- Customer
- Business problem
- Solution
- Products
- Solution components
- Data flow
- Integrations
- technical area
- use case category
- Business outcome
- outcome category
- Metrics
- Architecture
- evidence quotes
Date evidence
- Sitemap last modified Jul 30, 2026 · ServiceNow · Publisher metadata Publisher-reported modification timestamp; not a publication date.Open date source
- Unverified extracted date Jul 30, 2026 · ServiceNow · Unknown Legacy extracted date without source-page confirmation.Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.
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