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Apr 04, 2022 | 3 Mins read
Prioritizing Tickets with User Sentiment and Business Impact

Clearly, ticket prioritization matters. Get it right, and customers emerge from the interaction feeling positive about you and your product. Prioritize poorly, and you risk customer churn. But deciding which customer support tickets to solve first isn't as easy as it may seem. The approaches companies take vary as much as the companies themselves. Here are the most common prioritization approaches:

  1. First-in, First-out (FIFO) — The simplest approach is to respond to tickets in the order they were submitted. 

  2. Customer-defined — Companies that pursue this approach typically include a field on their submission form asking customers to rate the severity of their issue on a scale from "minor" to "urgent". 

  3. Issue-defined — An issue-defined approach allows support teams to classify tickets into categories: Pre-sales, General, Service Outage, Troubleshooting, and Billing, for example. 

  4. Service-level agreement-defined — Customer contracts often include language defining how—and how quickly—their support requests are managed. 

Let's look at a scenario with two customers of a SaaS company that have an average annual contract value (ACV) of $310K per customer.



Using the FIFO method, should a ticket submitted by the $100K customer before a ticket submitted by the $420K customer receive top priority? Take those same two companies and shift the priority assessment to customer-defined. Maybe the $100K customer defines their issue as “urgent” while the $420K customer defines their issue as “minor”. Does urgent always trump minor? What if we switch to issue-defined prioritization? Should a service outage-related ticket from the smaller customer outweigh a troubleshooting ticket from the larger? What if the smaller company writes hostile requests? Do they get priority over another company with whom your team’s interactions are calm and polite? And finally, what happens if both customers submit similar tickets on the same day, but the smaller company has a 12-hour response requirement via their SLA, while the bigger company mandates a 24-hour response? 

 Customer Support agents try to reconcile conflicts like these all the time. But what if customer support teams could augment prioritization across these dimensions with case sentiment and business impact?  

 User sentiment differs from customer satisfaction. Customer satisfaction is typically a post-interaction, self-reported metric most commonly collected in a survey. User sentiment reflects a natural language processing (NLP) analysis of the language and tone used when filing the case initially. For example, a case submitted with language like “need this fixed now” or “still can’t log in” shows frustration and anger and should factor into ticket prioritization. 

 Likewise, IrisAgent’s integration with CRMs like Salesforce puts each customer’s ACV at an agent's fingertips. Adding business impact to a support ticket helps agents account for the effect on the company’s bottom line when prioritizing open cases in real-time. In the image below, IrisAgent adds ACV to other, more customary metrics like wait time, case activity, and how individual agents interpret each case’s priority. Teams can customize these dimensions to meet their requirements.


The prioritization decision becomes much less binary when you add sentiment and revenue; it’s not which customer is first, which customer complains the loudest, which issue is more difficult to resolve, or the timeframe in which they expect a response. It all boils down to which customer–were they to churn–would have the most negative impact on the company’s business?

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