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Microsoft Financial Services United States

John Hancock

Customer Service Automation

At the onset of the COVID-19 pandemic, John Hancock's customer contact centers—like other customer contact centers around the world—saw a spike in traffic and the company sought ways to ensure their customers continued to get the answers they needed, when they needed them.

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"Introducing conversational AI via a virtual assistant has helped us take a bold step forward in our digitization efforts and our goal of providing outstanding customer experiences," says Folger.

Reported impact

Business outcome

"Introducing conversational AI via a virtual assistant has helped us take a bold step forward in our digitization efforts and our goal of providing outstanding customer experiences," says Folger.

  • Cost Reduction
  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

At the onset of the COVID-19 pandemic, many companies' customer contact centers were overwhelmed due to shutdowns and resource constraints. At the onset of the COVID-19 pandemic, John Hancock's customer contact centers—like other customer contact centers around the world—saw a spike in traffic and the company sought ways to ensure their customers continued to get the answers they needed, when they needed them. With its mission to give customers the confidence to make the right decisions, John Hancock dedicated itself to adopting a sustainable solution—for its customers and its call center representatives. The implementation centers on Azure AI Bot Service, Microsoft Teams, Azure to support customer service automation workflows.

Solution architecture

3 components · 2 layers
  1. Compute
    • Azure Provides the underlying cloud infrastructure, identity, and managed services for the solution.
  2. Serving
    • Azure AI Bot Service Hosts the conversational bot experience used by service teams and end users.
    • Microsoft Teams Acts as the collaboration surface for prompts, meetings, and shared knowledge.

Architecture clues

  • "In March 2020, the COVID-19 pandemic significantly affected all types of contact center operations," says Prince Perapadan
  • John Hancock supports call center teams with Microsoft conversational AI tools
  • With its mission to give customers the confidence to make the right decisions, John Hancock dedicated itself to adopting a sustainable solution—for its customers and its call cente...

Evidence from the source

"In March 2020, the COVID-19 pandemic significantly affected all types of contact center operations," says Prince Perapadan, Director Enterprise IT Lead-AI Cognitive Chatbot Platform owner at John Hancock.
"Introducing conversational AI via a virtual assistant has helped us take a bold step forward in our digitization efforts and our goal of providing outstanding customer experiences," says Folger.
At the onset of the COVID-19 pandemic, John Hancock's customer contact centers—like other customer contact centers around the world—saw a spike in traffic and the company sought ways to ensure their customers continued t...
At the onset of the COVID-19 pandemic, many companies' customer contact centers were overwhelmed due to shutdowns and resource constraints.
Transparency Evidence & methodology 61/100 reference value · 85% 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 value61/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth15/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence85%
  • 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
    4 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity6/10
    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. Microsoft

    John Hancock customer story

    First-party
    https://www.microsoft.com/en/customers/story/1642618423217607453-manulife-john-hancock-insurance-azure
    Source type
    Vendor-published customer story
    Published
    Jun 5, 2023
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

  • Published on source page Jun 5, 2023 · Microsoft · First-party
    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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