1. / Engineering Giant Gets 95% Accuracy in Customer Service Automation
Overview

With over 11,000 employees and a worldwide footprint, the customer delivers factories, machinery, services, and expertise to the global cement and mineral industries. As a result, they have considerably large helpdesk operations that could greatly benefit from optimization.

The customer wanted Apexon to build a text mining model to predict the category of helpdesk tickets from the email subject line. Additionally, the customer required us to build bots for specific helpdesk divisions including IT services, application support, and self-help portals.

Problem

Given the scale of the client’s operations and the vast number of helpdesk tickets generated on a daily basis, Apexon faced a set of very specific challenges:

  • Creating NLP-powered chatbots that supported multiple languages
  • Mapping several potential resolution pathways and integration automation features to support them
  • Successfully delivering a POC within a 6-week timeframe
Solution

By leveraging our expertise in R and Microsoft Bot Framework, Apexon was able to automate large portions of the helpdesk function, including the following tasks:

  • Problem identification from ticket details as shared by the customer
  • Dispatching acknowledgment to the user on the task being processed
  • Auto-resolution of each ticket to the mandated extent
  • Ticket and task completion notifications to the user
  • Ticket status updates in the IT helpdesk application (TopDesk)
Impact

By using 12 resolution bots coupled with a master and trigger bot within a cognitive application, Apexon was able to dramatically improve helpdesk efficiency.

  • Over 500 helpdesk tickets resolved by bots, representing 40% of the overall ticket volume
  • 90% of ticket assignments handled via SaaS RPA and touchless automation, with 95% accuracy
  • Headcount deployment reduced by up to 40%
  • Improved CSAT scores across every service line

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