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IBM Energy United Kingdom

E.ON UK Solutions

Customer Service Automation

E.ON needed a scalable and flexible replacement for a legacy contact center so it could support growing green-energy demand without disrupting customer service.

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1,000 agents
120,000 calls monthly
22 million homes and businesses
70,000 live chats

Reported impact

Business outcome

The project replaced the contact-center platform in under a year, now supports 120,000 monthly calls plus hundreds of thousands of emails and 70,000 live chats, and reduced costs through pay-as-you-grow SaaS licensing while improving wait times and first-time resolution.

  • Cost Reduction
  • Customer Experience
  • Scalability

Solution

E.ON worked with IBM Consulting to replace a legacy contact-center stack with an omnichannel platform built on Amazon Connect in the AWS Cloud. IBM began with IBM Garage workshops, then used BizDevOps squads working in two- to three-week sprints to configure the platform across five specialist business units without disrupting service. The implementation connected voice, email, mobile and web channels for more than 1,000 agents and layered in AI-powered capabilities such as voice analysis, speech-to-text conversion and sentiment scoring. IBM Consulting also trained agents through hands-on practice before go-live and migrated units sequentially onto the platform. The architecture is less about a single AI model than about a scalable contact-center operating platform that uses cloud-native services and AI analysis to route, handle and assess large volumes of customer interactions.

Data flow

Customer voice, email, mobile and web interactions enter Amazon Connect on AWS, AI voice analysis and speech-to-text help route them to the right agent, and managers review sentiment-scored call data while agents handle the resulting omnichannel workload.

Solution architecture

4 components · 3 layers
  1. Compute
    • AWS Cloud Hosts the cloud infrastructure underpinning the new contact-center environment.
  2. Serving
    • Amazon Connect Serves as the omnichannel contact-center platform used by agents across E.ON's business units.
  3. Orchestration
    • IBM Consulting Services for AWS Cloud Configured and delivered the new contact-center platform across the different business units.
    • IBM Garage Provided the workshop and agile delivery framework used to align stakeholders and iterate functionality.

Architecture clues

  • AI-powered voice analysis and sentiment scoring were layered into the contact-center workflow.
  • The platform uses pay-as-you-grow SaaS licensing rather than the legacy commercial model.
  • The rollout migrated five business units sequentially to minimize service disruption.

Evidence from the source

"AI voice analysis sends them to the right agent"
"Today, 1,000 agents handle 120,000 calls monthly using the Amazon Connect"
"Working as one team, E.ON and IBM Consulting took less than [a year] to replace an outdated contact center solution"
"sentiment analysis scores customer satisfaction with the engagement"
"the team sequentially migrated five business units onto the platform"
Transparency Evidence & methodology 90/100 reference value · 89% 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 confidence89%
  • 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 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. IBM

    E.ON UK Solutions customer story

    First-party
    https://www.ibm.com/case-studies/eon-uk-solutions
    Source type
    Vendor-published customer story
    Published
    May 14, 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

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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