Telegram Customer Service Scheduling Guide: Use Bot to Achieve 24/7 Seamless Message Acceptance

#Telegram Customer Service Scheduling Guide: Use Bot to realize 24x7 seamless message reception

To build an efficient Telegram customer service system, scheduling is a core link that cannot be avoided. For cross-border teams, Web3 projects or community operators, users may be distributed in multiple time zones, and team agents cannot be guaranteed to be online all day long. If no one responds after a user sends a message during non-duty hours, satisfaction will be reduced at best, and potential customers will be lost at worst. The key to Telegram customer service scheduling is not to let agents work shifts 24/7, but to achieve seamless message reception through Bot automatic replies, so that users can get instant feedback at any time. This article will combine the TG-Staff platform to explain in detail how to configure the scheduling and backup mechanism to cover all-weather consultation needs.

Why does Telegram customer service need to schedule and communicate with Bot?

Scheduling issues are particularly acute when the team only has 3-5 agents. Common pain points include:

Time Zone Difference: The user asked a question at night in Europe, and the domestic agent was resting, so the message was ignored.
Remote Team: Agents are located in different cities and cannot fix working hours, resulting in uneven distribution of sessions.
Non-working hours: During weekends or holidays, inquiries sent by users are not answered, which turns into a negative experience.

The solution is not to require agents to be online 24 hours a day, but to establish an automatic process: when all agents are offline, the Bot will automatically reply and guide users to leave messages. This can not only reduce labor costs, but also ensure that users always receive a response. The essence of “7x24” service is zero waiting perception rather than real agents on duty around the clock.

Understand the core of TG-Staff scheduling: conversation offloading and Bot automatic reply

TG-Staff provides two key functions to support shift scheduling and bailout: Session diversion rules determine how new sessions are assigned to agents; Visual command process is used to build Bot automatic replies as a bailout mechanism during off-duty periods.

Session offloading rules: rotational distribution vs online priority

In the “Project Settings” of the TG-Staff console, you can configure two offload modes:

Diversion rules	Applicable scenarios	Behavior description
Allocation in turns	Fixed shift system (such as morning shift, mid-day shift)	Polling authorized agents in order to ensure that each agent takes over the conversation evenly. Suitable for teams with fixed shifts.
Online priority	Flexible shift system (agents are online at any time to take orders)	Priority will be assigned to the currently online agents; if all are offline, the new session will be temporarily suspended and will be collected manually after the agents come online. Suitable for teams where agents have irregular working hours.

Which rule you choose depends on how your team is managed. If agents need to switch strictly between morning and evening shifts, rotational allocation will be more equitable; if agents are allowed to choose their own online time, online priority will be more flexible.

Bot automatic reply: use command process to build messages and guidance

TG-Staff’s command process editor uses drag-and-drop operation to build interactive logic without coding. For off-duty periods, you can create an “off-hours” process:

New Process: Enter the “Command Process” module in the console and click “New Process”.
Set trigger conditions: Select “User sends the first message” as the trigger event.
Add reply node: Drag a “Send Message” node and enter the automatic reply content (see example below).
Optional: Add a menu button: such as the “Submit Message” button, which will guide the user to enter key information after clicking it.
Save and Publish: Link to the corresponding Bot project, and the process will take effect immediately.

Tip: Shift scheduling does not have to be switched manually

TG-Staff’s “online first” offloading rule will automatically assign new sessions to online agents. If all agents are offline, new sessions will not be lost, but will be manually allocated after the agents come online. Combined with Bot automatic reply, seamless message reception during non-duty hours can be achieved.

Step one: Create a Bot automatic reply process as a backup during non-duty periods

Design welcome messages and message guidance during non-duty hours

The content of the automatic reply directly affects the user’s first impression. It is recommended to use the following speech template:

“Hello! Our customer service agents are currently not online during non-working hours. Please leave your questions and contact information (such as Telegram username or email), and we will reply to you as soon as possible during the next working period. Thank you for your understanding!”

You can also add a “Submit Message” button, which triggers a simple form process to collect user input when clicked. For example:

The user clicks “Submit Message” → Bot replies: “Please enter your question directly, we will record it and deal with it first.”
User input → The process automatically saves the conversation and displays it in the “pending” conversation list after the agent comes online.

Collect key information based on user portraits

If you use the professional version, TG-Staff’s user portrait function can automatically record the user’s language, source channel (such as the parameters carried by the diversion link) and first access time. When leaving messages during non-duty hours, these messages will be saved together. After the agent goes online, you can see the user’s complete background by opening the session without asking repeatedly.

Step 2: Configure session offloading to match team scheduling mode

Fixed shift scenario: rotating assignment + designated customer service group

Suppose your team has 4 agents, divided into morning shift group (Agents A, B) and evening shift group (Agents C, D). You can create two projects in TG-Staff (or use different customer service scopes of the same project):

Morning Shift Project: Set the customer service scope to “Designated Customer Service”, including only agents A and B, and select “Rotate Assignment” as the diversion rule.
Night shift project: Set the customer service scope to “designated customer service”, including only agents C and D, and the diversion rule is also “allocation in turns”.

Agents only need to log in to the web portal during duty hours, and the system will automatically assign new sessions to online agents in turn. Even if agents log in during off-duty periods, they will not receive sessions that do not belong to their shift.

Flexible scheduling scenario: online priority + all customer service

For scenarios where remote teams or agents are located in different time zones, it is recommended to use the “online first” rule:

Diversion Rule: Select “Online Priority”.
Project Customer Service Scope: Select “All Customer Service”.
Agent Behavior: Agents can log in or log out of the system at any time. New sessions are automatically assigned to currently online agents; if all are offline, the session will enter the “pending” queue, and agents can manually claim it after they come online.

This method does not require manual scheduling. Agents can go online according to their own schedule, and the system automatically balances the load.

Best practice: Use offload links to coordinate with scheduling

If you use TG-Staff’s “diversion link”, you can carry different parameters when advertising or social media placement. In conjunction with shift scheduling, when a user clicks a link during off-duty periods, the Bot automatically replies and records the source. After the agent goes online, he or she can see complete attribution information in the session, improving conversion tracking accuracy.

Step 3: Set agent roles and permissions to avoid misoperations

In the “Team Management” of the TG-Staff console, you can configure project-level permissions for each agent:

View Permission: Allows agents to view conversation history, but cannot reply.
Reply Permission: Allow agents to reply to messages.
Transfer Permission: Allow agents to transfer sessions to other agents.

For replies to messages during non-duty hours, it is recommended to enable “reply permissions” and “view permissions” for agents, but limit “transfer permissions” to avoid misoperations. In addition, if you use the content risk control function of the professional version, you can configure risk phrases (such as wallet addresses, sensitive words). If the agent hits the risk words before sending the message, the system will pop up a secondary confirmation window or prevent the sending. This is especially important in Web3 or exchange scenarios to prevent agents from mistakenly sending payment addresses or sensitive information.

Step 4: Test and iterate: Simulate the off-duty experience

Before officially going online, be sure to conduct a complete simulation test. Here is the checklist:

All simulated agents are offline: Have all agents log out of the web portal, and then use the test Telegram account to send messages to the Bot.
Verification automatic reply: Confirm whether the Bot has sent the greeting message during off-duty periods according to the preset process.
Check message saving: After the agent goes online, whether the user’s message content, timestamp and source information can be seen in the “pending” session list.
Test session takeover: After the agent clicks “Takeover”, whether the agent can reply to the user normally and whether the user can receive the reply.
Confirm user notification: After the user leaves a message, does he receive a confirmation message (such as “Your message has been recorded and we will reply during working hours”).

If you find that the automatic reply is not triggered or the message is not saved, check whether the command process has been released and whether the triggering conditions are correct. It is recommended to conduct at least 3 rounds of simulation testing before real user feedback.

FAQ

Q: After a user leaves a message during non-duty hours, can the agent see the historical chat records when online?

Answer: Yes. TG-Staff will completely save the conversation history, including user message content, timestamp and source information. After an agent goes online, he can see user messages in the “pending” conversation list and can reply directly.

Q: If the user sends multiple messages while the agent is offline, will they be merged into one conversation?

Answer: Yes. All messages sent by the same user while offline will be classified into the same conversation. Agents can see the complete context after coming online to avoid repeated processing.

Q: Does the free version or standard version support Bot automatic reply and message acceptance?

Answer: Supported. Both the free trial period (3 days) and the standard version include visual command flow functions, which can be used to build automatic responses during off-duty hours. However, advanced features such as user portraits, content risk control, etc. are only available in the professional version.

Q: Do I need to manually adjust the diversion rules when switching shifts?

Answer: No. If you use the “online priority” rule, the system will automatically detect the online status of the agent; if you use “rotational assignment”, you only need to ensure that the corresponding agent is online. No need to manually switch rules.

Q: Does TG-Staff support multi-project and multi-Bot scheduling?

Answer: Supported. You can configure the diversion rules, customer service scope and command process separately for each Bot project in the console, so that different Bots can use different scheduling plans.

Start building your Telegram customer service scheduling system now: Sign up for a free 3-day trial of TG-Staff to experience the complete process of conversation offloading, Bot automatic reply and message taking. If you want to learn more about shift configuration or customized solutions, you can check the official documentation or contact the customer service Bot @tgstaff_robot.