Give your service ecosystem an AI check-up

NPS, CES, CSAT — these are some of the metrics that businesses use to measure customer experience (CX). Customer complaint volume, customer churn rate, and even social media chatter—these are all good indicators of how your brand is rated by customers.


How does your service organization contribute to CX? What if you could apply the power of artificial intelligence to better understand how your service and support operations are influencing your CX numbers?

With Bruviti Smart Audit, you can identify how the interplay of your people, processes, and workflows are shaping your

customers’ experiences. By examining all your service records and applying big data analytics, a Bruviti Smart Audit can highlight where your service operations (including contact center, dispatch center, field service, and parts) are performing well—and where they are falling short.

Bruviti expertise provides valuable insights

With a machine-learning model that’s been trained using millions of service transactions, Bruviti Smart Audit knows what to look for. After examining your service records, applying natural-language processing and Bruviti’s industry-leading AI, Bruviti Smart Audit develops a detailed understanding of your entire service ecosystem.

Bruviti Smart Audit assesses the day-to-day operations, customer interactions, and team interactions that are flowing among your departments to reveal crucial insights such as:


  • The performance of call-center agents and field-service technicians.
  • The most prevalent service issues associated with each type of equipment.
  • Which service issues are being resolved successfully, and why.
  • Which issues are causing repeat truck rolls.
  • Why some technicians are taking longer or requiring more parts to resolve certain types of problems than others.
  • Which types of problems contact center agents will troubleshoot more successfully if provided targeted training or enhancements to the knowledgebase?




How it works

Bruviti’s Smart Audit engine ingests data from a wide variety of sources within the service organization. It understands the complete lifecycle of a service incident — from the initial customer call through to completion when the service technician closes the call. In addition to the structured data fields such as dates, times, call categories, and so on, the engine also ingests data from free-text fields such as agent notes, technician comments, and customer feedback, and then extracts intelligence from them. This is then collated and presented in easy-to-understand service dashboards.