Squirro Service Insights

Insights for Proactive Incident Management

Maximise service data to deliver a truly excellent customer experience

Squirro Service Insights is a data-based insight tool that will transform any IT Service Management landscape, unifying data across enterprise systems to improve mean time to resolution and prevent issues from escalating.

Reduce service management costs and improve helpdesk ticket resolution with Squirro Service Insights

The ability to offer a superior customer experience is highly valued in the modern enterprise, yet many firms’ IT Service Management landscape is costly, inefficient and incapable of effectively utilising the data it holds to improve service levels. Organisations only know about issues when they occur, and they are then taking too long to resolve. This leads to service levels falling and customer churn increasing.

Squirro Service Insights provides all the insight required for any organisation to significantly improve its service levels. It uses data to identify trends and anomalies, automate service ticket clustering, recommend solutions (based both on context and previous issues) and to predict potential future issues. This improves service at a reduced cost and allocates resources more effectively.

Squirro Service Insights integrates seamlessly with all main enterprise applications, such as CRM and Service, using structured and unstructured data to improve the overall customer experience. Its AI-based cognitive catalyst detection means it can anticipate incidents and issues before they happen, and based on analysis of previous incidents, recommend the likely solutions.

Its use of machine learning means Squirro Service Insights gets smarter the more data that is analysed, and overall is becoming an essential tool for organisations committed to transforming their IT Service Management landscape. Squirro Service Insights users have benefited from 30% reductions in cut time to resolution and 15% reductions in support costs.


1. Incident Prevention

Preventing incidents before they even occur should be a major priority for any organisation. Squirro Service Insights’ anomaly detection means that they can do just that, identifying trends and patterns that signify not only that an incident will take place, but give intelligence on the type of incident it is likely to be and how best to address it.

2. Incident Automation

The sheer volume of incidents and tickets in the average enterprise can be overwhelming, but Squirro makes this whole process much easier and more efficient. Taking insight from data on previous incidents, it can offer highly accurate resolution recommendations, using automated ticket routing which allows better allocation of services resourcing and encourages self-service on certain incidents.

3. Incident Analysis

The ability for an enterprise to learn from incidents is priceless, and Squirro makes this possible by delving deep into incident data to analyse why an incident occurred and what could be done to prevent it in future. This contextual analysis that looks at many factors, allows an enterprise to adopt a more proactive approach to IT Service Management and improve service levels to customers.

4. Service Data Unification

With mergers and acquisitions, modern enterprises often operate multiple service solutions, placing a strain on IT Service resources, personnel and effectiveness. Squirro Service Insights will seamlessly connect multiple service solutions such as ServiceNow, Salesforce Service Cloud and BMC Remedy, collating and deploying data from all and delivering deeper insight and vastly improved service as a result.


Customer dissatisfaction at time taken to address issues

Unsure whether key clients have been affected by an incident

Unable to locate major incidents

Lack of insight as to what caused a major incident


Automated service ticket clustering and assignment to best available agent

Automated flagging of all systems with an increased number of tickets, across client base

Contextual analysis of locations, applications and text descriptions to allow easy identification of incidents

AI-based analysis of major incidents / machine learning to better understand cause and solution


Net meantime to resolution reduction of 30%, improved service levels to customers

360-degree view of which clients are impacted by which incident

Proactively find incidents that may become major issues

Understanding of what is responsible for major incidents and recommendations as to how best to address them


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Customer Service Case Study


Service Insights Case Study

Service Insights Solution Brief