Blog · Board and management reporting · Customer service
How a customer service leader measures repeat contact per account from the ticket export: tickets reopened or re-raised on the same issue within a stated window, the accounts whose repeat rate is well above the base, the categories where repeats cluster, and why an account-level repeat rate is a churn signal the team average cannot show.
A support team reports first contact resolution at 81 percent and is proud of it. One of the company's largest accounts has a repeat rate of 55 percent, and its renewal is in two months. The ticket export, cut per account, shows it. This guide sets out repeat contact per account, the category split, and the list.
Per account, per period:
Repeat tickets = tickets reopened, or raised in the same category within the window of a closed one Repeat rate = repeat tickets ÷ tickets Above base if repeat rate > multiple × team repeat rate, and tickets ≥ minimum
Per account, per category:
Repeat rate, to find where the repeats cluster
Account identifiers only.
tickets = first-contact resolved + repeat + open
Every ticket in one state. A ticket with a reopen date before its close date fails it and is listed.
Team repeat rate 19 percent. Multiple 2. Minimum 8 tickets.
| Account | Revenue | Tickets | Repeat rate | Repeating category | Renewal | Account manager |
|---|---|---|---|---|---|---|
| 4471 | $840,000 | 31 | 55% | Integrations: 12 of 14 repeat | 8 weeks | AM-04 |
| 2210 | $610,000 | 22 | 41% | Billing: 6 of 7 repeat | 5 months | AM-11 |
| 9034 | $95,000 | 9 | 44% | Mixed | 3 months | AM-04 |
Account 4471 has had to raise the same integration issue a dozen times. Its account manager finds out at renewal unless this list reaches them first. Account 2210 is a billing problem, which is not a support problem at all, and the list routes it.
| Category | Tickets | Repeat rate | Accounts above base |
|---|---|---|---|
| Integrations | 410 | 34% | 9 |
| Billing | 220 | 28% | 4 |
| How-to | 1,100 | 9% | 1 |
Integrations repeats for nine accounts. That is a product finding with an account list attached, which is the form engineering can act on.
Team average only. The account at 55 percent is inside the 81.
Repeat rule undefined. Two people compute two rates.
Small accounts on the list. Two tickets, one repeat, 50 percent. Minimum count.
Category ignored. A billing problem worked as a support quality problem.
Mapped once, the ticket export and the account list produce repeat rate per account, the category split and the ranked list every week. Covirage builds this from the exports as they are. The customer service page describes the setup, and the surge list guide covers the volume signal that usually accompanies a high repeat rate.
A ticket reopened after closure, or a new ticket from the same account in the same category within a stated window, seven to fourteen days, of a closed one. The window and the category matching rule are on the report. Linked-ticket fields, where the desk uses them, are the better source.
Per agent is a coaching measure. Per account is a retention measure. The same repeat can be an agent's mistake or a product problem at one customer, and the account view finds the customer who is carrying the cost either way.
The team's repeat rate across all accounts in the period. An account at more than a stated multiple of the base, with a minimum ticket count so that two tickets do not make a rate, is on the list.