SUCESS STORY
Improving Call Center Operations with ML
EXECUTIVE SUMMARY
Automating incident classification significantly improves operations in a Call Center scenario. Algorithms learn from historical data and classify in real-time the best resolution group for each incident. Our algorithms show an 80% of accuracy ratio.
“Every single point we rise in the Visit Avoidance KPI implies a savings in the of a hundred thousands euros in saving in the service and improves the Perception of Quality of Service of our Customers.”
Olivier Gómez COO Ricoh Europe
CHALLENGES
The European Operations Service Direction goals for this project were:
- Increasing the Remote Solution rate.
- Minimizing the On-site Technical Support costs.
- Improving Customer Satisfaction.
HOW SOLUTIONS HELPED
Our dispatching bot help Ricoh to:
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- Automatize the dispatching process 24x 7 avoiding the need of make several works shifts for the job.
- Maintain and the quality of the decision like an expert can do.
- Dedicate workforce to others to more added value tasks.
RESULTS, RETURN ON INVESTMENT AND FUTURE PLANS
As results worked in Spain, Ricoh UK is just now working with the same solution for their Technical Service, and they are increasing their Remote Support Team efficiency in 30,5% .
Since the Dispatching Bot Implementation, our AI based classification tool, the Remote Incident Solving is increasing in a monthly basis more than 4 points.
The Machine Learning Model continues learning when retraining with new data.
