Customer service satisfaction scores are a valuable tool to evaluate and improve customer experience, and here's when support teams play a crucial role. They shape customer experiences by influencing customer satisfaction levels. By understanding these concepts from the customer support spectrum, improve customer happiness will be a mere consequence of support excellence, and we'll show you how to centralize it, measure it, and take action in Jira.
According to the Harvard Business Review, 80% of companies use customer satisfaction scores to analyze customer experience and improve it. But why wait for the results of satisfaction surveys to improve support if you can do it faster than that?
In the landscape of IT Service Management (ITSM) and Enterprise Service Management (ESM), support teams serve as frontline ambassadors, wielding a considerable influence over the mood and satisfaction levels of customers. Over years of immersion in these environments, we've come to appreciate the role that support teams play in shaping user experiences. It's within these interactions that the transformative potential of support teams truly shines, as they navigate through the spectrum of user emotions, from frustration to resolution.
Picture this: A user reaches out to the support team, engulfed in a storm of emotions—anger, frustration, urgency. Their productivity is halted by an unresolved issue, they seek comfort in the hands of the support team. This moment is crucial, where the support team holds the power to not just resolve technical glitches but also to uplift the user's mood, turning a potentially negative experience into a positive one.
So, how can support teams effectively make use of their influence to enhance customer mood? Here are some considerations:
By embracing these principles, support teams can harness their power to not just troubleshoot technical issues but also uplift the spirits of customers. Each interaction becomes an opportunity to transform frustration into satisfaction, anxiety into assurance, and urgency into calm.
We firmly advocate for a novel approach to measure service management effectiveness through Emotional Level Agreements (ELAs). Can companies establish KPIs to measure how support teams are enhancing customers' moods? We believe they can. It requires equipping support teams (including agents, service managers, etc.) with tools to comprehend and consistently analyze customer feelings and emotions. Furthermore, centralizing this analysis within a system such as Jira, ensures objective results devoid of biases or personal inclinations.
Let’s check the following graph:
Gomood's "Customer Mood" report allows us to measure customers' sentiments and emotions in Jira Service Management.
With this information at hand, agents match customer sentiments and emotions in real-time, empowering them to take appropriate actions accordingly to improve and impact the customer’s mood.
Now, let's check this other graph:
Gomood's "Dissatisfied customers conversion" report allows us to see the overall customer sentiment across the support tickets lifecycle.
What's there to see?
As a service manager, this information allows you to measure if you are meeting the ELA defined with your clients or simply check if you are improving the mood of users and customers.
These charts, along with several others, are included in Gomood: The winning app of the latest Atlassian Codegeist competition, which, based on artificial intelligence capabilities, provides a set of insights to analyze and improve customer mood.
As you can see, tracking customer sentiment across the support tickets lifecycle helps offer the best possible customer experience for your products and/or services. If you use Jira Service Management (JSM) for this end, you better take advantage of Gomood.
Gomood is a new app for JSM, available in the Atlassian Marketplace, that uses artificial intelligence to identify customer happiness.
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