Reported impact
Business outcome
smart Europe improved case accuracy and resolution speed while making it easier for agents to deliver personalized support as online vehicle sales interactions increased.
- Customer Experience
- Productivity Improvement
IBMAutomotiveCustomer Service AutomationContact CenterGenerative AI / LLMCustomer ExperienceProductivity Improvement2024 IBMIBM#0f62feAutomotiveEuropesmart Europe needed to automate case handling in its customer engagement center because Salesforce-based workflows were manual, inconsistent and too slow for its direct-to-consumer sales and after-sales model.3 times faster resolution time for recurring issuesAug 20, 20246Customer Service AutomationIBM Cloud · IBM Watson Discovery · IBM watsonx.ai0 2024-08-20 6
smart Europe
Customer Service Automation
smart Europe needed to automate case handling in its customer engagement center because Salesforce-based workflows were manual, inconsistent and too slow for its direct-to-consumer sales and after-sales model.
3 times faster resolution time for recurring issues
30% improvement in the accuracy of case categorization and prioritization
60% increase in first contact resolution
97% agent acceptance rate
Solution
smart Europe, IBM Consulting and IBM Client Engineering built a generative-AI customer-service MVP inside Salesforce. IBM watsonx.ai runs on IBM Cloud and processes incoming tickets before any human action, automatically summarizing, categorizing and prioritizing cases. IBM Watson Discovery resolves standard queries directly so answers remain consistent and on brand, while a Salesforce UI component shows agents the system-generated decisions and recommended next steps. The design converts customer inquiries into structured support actions early in the lifecycle, reducing manual triage and improving routing quality. Because the solution is compatible with Salesforce, ServiceNow, Adobe and additional use cases, it can be scaled beyond the first deployment into other regions and departments. The architecture therefore improves the immediate customer-service workflow while also creating a reusable automation pattern for smart Europe’s broader D2C operating model.
Data flow
Customer cases enter Salesforce, are processed by watsonx.ai for summary and prioritization, routed to Watson Discovery for standard-question resolution where possible, and then returned to agents through a Salesforce UI for follow-up.
Solution architecture
- Compute
- IBM watsonx.ai Automates summarization, categorization and prioritization of incoming customer cases.
- IBM Cloud Provides the runtime environment for the ticket-processing solution.
- Serving
- IBM Watson Discovery Answers standard customer queries automatically and provides consistent knowledge retrieval.
- Salesforce Hosts the customer-case workflow and the UI component that surfaces AI-generated decisions to agents.
Architecture clues
- Built as a Salesforce-embedded MVP for a D2C business model
- Can be extended across languages and departments
- Processes tickets before any human action
Evidence from the source
The MVP demonstrated: 30% improvement in the accuracy of case categorization and prioritization.
The system answers and automatically resolves standard queries using IBM Watson® Discovery.
The team integrated IBM® watsonx.ai® Salesforce to automatically prioritize and classify incoming customer cases and provide streamlined response support.
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 value100/100
- Problem clarity20/20Measures whether the customer's operational problem is specific enough to compare.
- Implementation depth25/25Rewards 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 confidence84%
- 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 evidence15/203 direct source quotes retained.
- Date provenance10/10The publication date comes from the source page or publisher.
- 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.ibm.com/case-studies/smart-europeIBMFirst-party
smart Europe 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
- Publication date
Date evidence
- Published on source page Aug 20, 2024 · IBM · First-partyOpen 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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