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Vodafone

Customer Service Automation · Enterprise Knowledge Search

Vodafone wanted to improve customer experience for complex service interactions by making its virtual assistant better at understanding nuanced enquiries and by reducing repetitive work for care agents so they could resolve harder issues faster without passing customers around.

13 countries
15 different languages
50% improvement in first-time resolution of critical customer journey’s such as complex billing inquiries
customer call times have been reduced by at least one minute on average

Reported impact

Business outcome

Vodafone reports better first-time resolution for complex enquiries, shorter customer call times, improved response accuracy and customer satisfaction, less repetitive work for agents, broader employee skills, and the ability to reuse the approach across multiple markets.

  • Cost Reduction
  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

Vodafone built two customer-care AI services, SuperTOBi and SuperAgent, as part of its customer experience programme using Microsoft’s generative AI stack. SuperTOBi extends Vodafone’s existing TOBi virtual assistant with Microsoft Azure OpenAI Service so it can interpret more complex customer enquiries, respond in a more natural way, and personalize responses across Vodafone’s multilingual service footprint. When TOBi cannot resolve an issue, it hands the interaction to a human agent together with a conversation summary, preserving context for the next step. SuperAgent then supports the agent by locating detailed answers from Vodafone’s knowledge base and by checking call and online chat transcripts to identify missing information or training needs. Vodafone also says both solutions operate under its AI Framework, which governs ethical, unbiased, explainable AI use as rollout expands across call centres and markets.

Data flow

Customer questions enter SuperTOBi, which uses Microsoft Azure OpenAI Service to interpret and answer them in natural language. If the bot cannot resolve an issue, it passes a summary of the conversation to a human agent. SuperAgent then retrieves relevant material from the Vodafone-wide knowledge database and checks call or online chat transcripts so the agent can resolve the case faster and with more context.

Solution architecture

5 components · 4 layers
  1. Compute
    • Microsoft Azure OpenAI Service Provides the generative AI capabilities that improve TOBi’s understanding and response quality for complex enquiries.
  2. Storage
    • Vodafone-wide knowledge database Supplies the detailed internal information that SuperAgent searches to answer technical and service questions.
  3. Serving
    • SuperTOBi Vodafone’s GenAI-enhanced virtual assistant handles customer enquiries, personalizes responses, and escalates unresolved issues with context to a human agent.
    • SuperAgent Agent-assist service helps customer care employees find the right information quickly and handle more complex or cross-domain queries.
  4. Governance
    • AI Framework Provides governance for ethical, unbiased, and explainable use of AI and machine learning in the customer experience solutions.

Architecture clues

  • Designed for reuse across multiple markets from a single development effort
  • Supports multilingual service operations across 13 countries and 15 languages
  • Tested extensively at one Vodafone call centre before broader rollout
  • Uses conversation summarization to transfer unresolved cases from bot to human agent

Evidence from the source

“Initial tests of SuperTOBi show an 50% improvement in first-time resolution of critical customer journey’s such as complex billing inquiries, as well as greater accuracy of responses overall.”
“It helps agents solve more complicated problems by quickly locating the relevant information from the Vodafone-wide knowledge database.”
“Now with Microsoft Azure OpenAI, TOBi can better understand, and respond faster, to complex customer enquiries while providing them with a more personalised experience.”
“SuperAgent can more quickly check call and online chat transcripts to determine whether additional training or information is required.”
“TOBi sends a summary of its customer conversation to the agent, so they can jump right in.”
“TOBi, Vodafone’s existing virtual assistant which is already handling nearly 45 million customer questions per month in 13 countries using 15 different languages.”
“by leveraging Microsoft’s GenAI capabilities, customer call times have been reduced by at least one minute on average”
Transparency Evidence & methodology 90/100 reference value · 94% 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 value90/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    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 impact15/25
    1 metric describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence94%
  • Source authority25/25
    The deployment is described by the adopting organization or a government source.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    7 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 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. Vodafone

    Vodafone customer story

    First-party
    https://www.vodafone.com/news/newsroom/technology/vodafone-supercharging-customer-experience-with-microsoft-s-gen-ai-tools
    Source type
    Customer-published story
    Published
    May 23, 2024
    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 May 23, 2024 · Vodafone · 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.