Let's say you notice a 50% increase in customer support tickets. What would you do?

Assuming the product is Coinbase

Assuming customer support tickets are in the written format and properly tagged

Approach:

1. Verifying if the problem exists
2. Cluster the tickets into different groups
3. Identify the groups and categorize them based on the impact of the tick to effort required to solve it
4. Prioritization of tickets
5. Resolving the issues
6. Finding the reason

Details:

1. Verifying if the problem exists
   1. Performing basic sanity checks like if the beans are taking data and showing the correct data on the dashboard
   2. Is the dashboarding functioning correctly
2. Cluster the tickets into different groups
   1. Each ticket will have a tag and tags can be used for clustering to find the customer support ticket was generated at what instance of the user journey
   2. Later quantifying each cluster on the basis of the similarity of problems eg (Login issue: 20 users, Password recovery: 18 users, etc)
3. Identify the groups and categorize them based on the impact of the tick to effort required to solve it
   1. Each quantified cluster will be mapped on the impact of the tick to effort required to solve it metrix
   2. We will be prioritizing each cluster as per the below order
      1. High Impact Low Effort
      2. High Impact High Effort
      3. Low Impact Low Effort
      4. Low Impact High Effort
      5. (Not where ii and iii are interchangeable) if the Low Impact Low effort are occurred more we will be ranking them as 2
4. Prioritization of tickets
   1. Our high focus will be High Impact Low Effort
      1. This will be further distinguished as per urgency. The picks with high urgency will be resolved first!
5. Resolving the issues
6. Finding the reason
   1. RCA will be done as per each group of cluster focusing on high impact tickets first