Set up shift types and pay multipliers

Updated May 22, 2026

Shift types are the foundation of Yaplet's time-tracking system. Before your agents can clock in, you need at least one shift type configured. Each type has a name, a color, a pay multiplier, and a flag that controls whether that shift puts the agent online for live chat.

Create a shift type

  1. Go to Settings → Shift types (or Time management → Shift types).
  2. Click Add shift type.
  3. Fill in the fields described below.
  4. Click Save.

Shift type fields

Name

A descriptive label your agents will see when clocking in. Examples: "Regular chat", "Weekend on-call", "Holiday cover", "Training", "Back-office".

Color

A hex color used to visually distinguish shift types in reports and the shift table. Pick colors that are distinct at a glance.

Rate multiplier

A decimal multiplier applied to each agent's base hourly pay rate when calculating earnings for this shift type:

Multiplier Meaning
1.0 Normal pay (standard rate)
1.5 Time-and-a-half (typical overtime or weekend)
2.0 Double pay (public holidays)

The formula is: pay = hours × agent_pay_rate × rate_multiplier. You set each agent's base pay rate in their team member settings.

Chat available (Availability type)

This flag has two options:

  • Chat Duty — Clocking in on this shift type sets the agent as online. They receive incoming conversations and count in the auto-assign pool. Use this for any shift where the agent should be actively chatting.
  • Other Work — Hours are tracked but the agent's online status is not changed. Use this for training sessions, admin tasks, or any work that shouldn't route chats to the agent.

Restrict which agents can use a shift type

Under the shift type's Agent permissions section, select which team members are allowed to clock in on this type. Agents won't see shift types they don't have permission for when selecting a shift.

Edit or delete a shift type

Click any shift type's name to open the edit form. Deleting a shift type does not delete past shifts logged under it — historical data is preserved.

Did this article answer your question?