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ServiceNow Telecommunications Philippines

PLDT

Customer Service Automation

PLDT and Smart were limited by legacy VPN-dependent systems and disconnected service processes that slowed mobile access, customer response times, and employee referrals.

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$1.52M Revenue generated via employee referrals
$400K Value of churn prevented
50% Improvement in average response time
ServiceNow enables us to capitalize on our group’s ecosystem and contribute $1.52 million in new revenue

Reported impact

Business outcome

PLDT improved average response time by 50%, generated about US$1.52 million in new revenue through referrals, and prevented about US$400,000 in churn while lifting employee satisfaction.

  • Customer Experience
  • Productivity Improvement
  • Revenue Growth

Solution

PLDT and Smart were limited by legacy VPN-dependent systems and disconnected service processes that slowed mobile access, customer response times, and employee referrals. PLDT implemented a ServiceNow-centered stack built around Customer Service Management Pro, Workflow Data Fabric, App Engine, and Automation Engine. Key components included Customer Service Management Pro adds advanced automation for customer support; Workflow Data Fabric connects operational data and automation context; App Engine builds custom workflow apps; Automation Engine automates cross-system tasks. Requests enter through Virtual Agent before Customer Service Management Pro, Workflow Data Fabric, App Engine, and Automation Engine routes or fulfills the work. Updates then flow back to agents, account teams, or customers through the same connected experience. Running customer support and case management on one data model reduced manual handoffs and made expansion easier.

Data flow

Requests enter through Virtual Agent before Customer Service Management Pro, Workflow Data Fabric, App Engine, and Automation Engine routes or fulfills the work. Updates then flow back to agents, account teams, or customers through the same connected experience.

Solution architecture

5 components · 2 layers
  1. Serving
    • Virtual Agent Handles conversational self-service and ticket deflection for users.
  2. Orchestration
    • Customer Service Management Pro Adds advanced customer-service workflows, automation, and agent tooling for support operations.
    • Workflow Data Fabric Connects operational data across systems and powers automation with shared context.
    • App Engine Supports custom workflow and application development for business processes.
    • Automation Engine Automates repetitive tasks and cross-system workflow actions.

Architecture clues

  • Workflow Data Fabric is used as the shared context layer across multiple systems and workflows.

Evidence from the source

Grace says: “ServiceNow provides end-to-end visibility for employees to quickly respond to customers about problem resolution
Maximizing return on investment Unlike legacy on-premise systems that rely on VPN, PLDT and Smart have built a mobile app using the low-code ServiceNow App Engine and Workflow Data Fabric, enabling employees to access the portal anywhere, anytime
With the ServiceNow AI Platform , PLDT and Smart not only improved collaboration across teams, but also enabled more employees, including non- frontliners, to escalate customer concerns
“With lockdowns limiting staff to work remotely during the pandemic, it was not possible for different teams to collaborate on a request using their legacy on-premise systems
“With the ServiceNow AI Platform, our employees are empowered to deliver faster and better customer service and bring benefits to PLDT’s bottom line.” Share this story App Engine Customer Details Customer PLDT, Inc
Transparency Evidence & methodology 95/100 reference value · 79% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

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 clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    3 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence79%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. ServiceNow

    PLDT customer story

    First-party
    https://www.servicenow.com/customers/pldt.html
    Source type
    Vendor-published 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

  • First archived May 23, 2023 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.
    Open date source
  • Sitemap last modified Jul 30, 2026 · ServiceNow · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    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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