Showing results for 
Search instead for 
Did you mean: 
Sign up Log in

Earn badges and make progress

You're on your way to the next level! Join the Kudos program to earn points and save your progress.

Deleted user Avatar
Deleted user

Level 1: Seed

25 / 150 points

Next: Root


1 badge earned


Participate in fun challenges

Challenges come and go, but your rewards stay with you. Do more to earn more!


Gift kudos to your peers

What goes around comes around! Share the love by gifting kudos to your peers.


Rise up in the ranks

Keep earning points to reach the top of the leaderboard. It resets every quarter so you always have a chance!


Come for the products,
stay for the community

The Atlassian Community can help you and your team get more value out of Atlassian products and practices.

Atlassian Community about banner
Community Members
Community Events
Community Groups

How to measure customer satisfaction without surveys

Up until now, surveying customers was one of the only ways to understand customer satisfaction. This method of collecting feedback has always been problematic. Surveys can be intrusive, expensive and results often contain elements that are irrelevant, inaccurate or biased.

Furthermore, the global shift to remote work has led to a significant rise in digital communications and it’s causing customers to feel fatigued and burnt out.



In 2020, more than 300 billion emails were sent and received every day, a number that is expected to grow to 320 billion this year.

Now with recent developments in deep learning, sentiment analysis underpinned by AI Natural Language Processing (NLP) allows organisations to collect feedback without surveys - using data they already have!

NLP contextually mines text, identifying and extracting subjective information within conversations that can assist in understanding customer attitudes and their underlying reactions and intentions.

AI Insights for Jira Service Management negates the need for intrusive post incident, email surveys by utilising NLP to track and report customer and agent sentiment in real-time.

Furthermore, real-time feedback opens up new opportunities for action. If dissatisfaction is detected as soon as it appears - before conversations are completed - agents can intervene and prevent escalation and the risk of customers leaving dissatisfied.


Service Management Teams are able to implement CSAT cultures of intervention instead of repair. Detecting trends and patterns that inform dialog strategies, utilising existing data and adjusting conversation patterns accordingly to improve customer satisfaction.

Additionally, organisations can take advantage of opportunities to up-sell and better leverage positive customer interactions when they are detected in real-time.


AI driven CSAT analysis introduces new opportunities for Jira Service Management workflows, allowing service teams to modernize their operations and realise completely new CSAT outcomes. AI Insights for JSM is a unique solution providing real time CSAT detection directly within Jira Service Management issues.

AI Insights is available on the Atlassian Marketplace - if you’re interested to automate your customer success try the app for free, get in touch with us for a demo and make sure to subscribe to hear more about how AI transforms the way we work together.

Are you ready to turbo charge your customer satisfaction with next-gen AI driven, real-time sentiment analysis for Jira Service Management?

1 comment

If Excel reporting is still a requirement for your customer satisfaction analysis besides these modern reports in Jira Service Management, continue reading about Jira Service Management customer satisfaction Excel reports >>>


Log in or Sign up to comment

Atlassian Community Events