Customer Service Automation · IT Operations Automation
ROSSMANN store managers had to leave the sales floor, call headquarters, and work issues through siloed HR, IT, and store-operations systems, turning each support case into a slow manual handoff.
Reported impact
ROSSMANN cut AI-handled case work from nine minutes of human labor to under five seconds, reached 98% routing accuracy, reduced labor costs by 50%, and projected €20-30 million in annual operating savings as more stores come onto the platform.
ROSSMANN consolidated store support on ServiceNow by building a mobile experience on Retail Operations and then layering AI Agents over the case workflow. Every store associate can open the app, submit an issue by text or voice in their own language, attach photos, and follow status without phoning headquarters or switching channels. For damaged deliveries, the AI agent inspects the image, identifies the product, asks for missing information such as delivery date, and pulls guidance from the knowledge base before preparing a complete case for the right team. Simpler requests, including login issues, can be handled end to end by the AI agent itself. That architecture replaced separate HR, IT, and store-operations support paths with one digital backbone that classifies, prioritizes, routes, and closes work in seconds instead of minutes.
A store associate submits a text, voice, or photo report through Retail Operations. AI Agents classify the issue, ask for missing details, and use the knowledge base to prepare or resolve the case before routing any remaining work to the correct headquarters team.
A single manual case averaged nine minutes of human labor across departments.
Accuracy in routing tickets to the right teams has now climbed to 98%
The AI agent scans the image, identifies the product, and classifies the issue
What could once take up to nine minutes of back-and-forth now takes less than five seconds.
the equivalent of €20-30 million annually.
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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