Automated AI customer service online list: Telegram Bot 7-day deployment full-process inspection items

Want to quickly launch an automated AI customer service system, allowing Telegram Bot to handle user inquiries, complete session offloading, and achieve compliance operations within 7 days? This article is a landing guide for you.

Whether you are running cross-border SaaS, Web3 projects, or providing support for multi-language communities, a clear online checklist can avoid pitfalls. We take TG-Staff as an example and break down the inspection items from 0 to 1 on a daily basis, covering Bot configuration, process construction, agent training and quality inspection. You can check this list, tick items one by one, and go online in 7 days.

Day 1: Bot basic configuration and access preparation

Build Telegram Bot from scratch and complete the binding with the TG-Staff console to lay the foundation for subsequent automated processes.

1.1 Create/bind Bot and obtain Token

If you don’t have a Bot yet, create a new Bot via @BotFather and get the API Token. Teams that already have Bot can simply copy the existing Token.

Check items:

• Bot name and description have been set according to business needs (can be edited directly in the TG-Staff console without jumping to BotFather)
• Token copied and saved to a safe location
• Confirm that the Bot is not occupied by other platforms or scripts

1.2 Create a new project in TG-Staff and authorize it

Log in to TG-Staff Console, create a new project, and enter Bot Token to complete authorization.

Check items:

• The project name corresponds to the purpose of the Bot (such as “Pre-sales consultation” and “After-sales work order”)
• After the authorization is successful, the console displays the Bot online status
• Free trial activated (sign up to enjoy a 3-day trial, including all the features of the standard version)

Day 2: Automated process construction - from welcome message to menu commands

Use the visual command process editor to complete the Bot’s welcome message, menu buttons and multi-step interaction process design with zero code, ensuring that users can complete common consultations by themselves after entering.

Operating steps:

1. Open the “Command Flow” editor in the console
2. Drag the “Welcome” node and set the copy sent when the user starts /start for the first time (can include brand introduction and FAQ entrance)
3. Add the “Menu Button” node and configure the button text and corresponding commands (such as “Query Order”, “Contact Customer Service”, “View Help”)
4. Concatenate multi-step processes: For example, the user clicks “Query Order” → Bot asks for the order number → Automatically responds to the query results

Check items:

• The welcome message already contains key guidance information
• Menu button jump logic is correct, no loops or dead links
• Multi-step process test passed: simulate user input and verify that the response of each branch meets expectations
• Save the process and publish it to the online environment

Day 3: Agent account configuration and permission assignment

Create an independent agent account, set project-level permissions and operation scope, and ensure a clear division of labor among the team.

3.1 Add agents and assign project customer service scope

In the “Agent Management” of the console, create an independent login account for each customer service member.

Check items:

• The number of seats is within the package quota (3 seats for free trial, 5 seats for standard version, and 20 seats for professional version)
• Each agent is assigned a corresponding project customer service scope (all customer service or designated customer service)
• The agent has set an independent password and completed the first login.

3.2 Configure session diversion rules (rotating distribution vs online priority)

TG-Staff supports two diversion rules, suitable for different scenarios.

Diversion rules	Applicable scenarios	Behavior description
Allocation in turns (default)	Fixed number of agents, team shift system	Polling authorized agents in sequence to ensure load balancing
Online priority	Agent online time is inconsistent and peak consultation	Priority is assigned to the current online agent; when all offline agents are assigned, fall back and take turns

Check items:

• Select appropriate diversion rules according to team scheduling mode
• Test the diversion effect: use multiple test accounts to initiate a session and confirm that they are assigned to different agents

Day 4: Session diversion and diversion link verification

Configure the diversion link (magic link) and test the complete conversion link from advertising/social media → Bot → manual agent to ensure that users can be smoothly assigned to online agents.

4.1 Generate diversion links and embed promotion channels

Create a new magic link in the “Diversion Link” console. TG-Staff will generate an official domain name short link (such as https://app.tg-staff.com/{code}).

Check items:

• Diversion link has been generated and copied
• Links have been embedded in advertising, social media profiles, official website buttons and other channels
• Generate independent links for different channels for subsequent attribution analysis

4.2 Verification diversion process and user attribution tracking

After clicking the diversion link, the system will automatically capture the user’s IP, browser information and URL parameters.

Check items:

• After the test user clicks the link, he can jump to the Bot normally and trigger the welcome message
• Session ownership is correct: user information (IP, browser, channel source) is visible on the agent session interface
• No 404 or jump exception occurs in the diversion link

Day 5: Batch message sending and operation contact

Send messages in batches according to user groups, verify whether the group sending function is normal, and prepare for subsequent user recall and conversion.

Operating steps:

1. In the “Group Message” module of the console, select the target user group (you can filter by activity, tags, and last interaction time)
2. Edit group sending content (supports text, pictures, buttons)
3. Preview and send

Check items:

• User grouping conditions have been set correctly to avoid misinformation or omissions
• The mass-posted content has passed the preview review (the professional version supports content risk control detection)
• Verification after sending: at least 2-3 test users receive the message and the content format is normal
• Record the mass sending time and number of users covered for subsequent conversion statistics

Day 6: Content Risk Control and Quality Inspection System Construction (Professional Edition)

Configure risk word grouping and wallet address monitoring, and establish an agent message audit mechanism to ensure compliance and internal control. This feature is only available in the Pro version.

6.1 Create risk phrases and associate projects

In the “Content Risk Control” of the console, create a new risk phrase and enter the words or address fragments that need to be monitored.

Common risk word scenarios:

• Sensitive business terms (such as “payment on behalf of others” and “money laundering”)
• Wallet address fragment (TRC20/ERC20/BTC address prefix or full address)
• Competing product names or illegal diversion words

6.2 Test risk trigger: pop-up window confirmation and blocking sending

After the configuration is complete, have the test agent try sending a message containing the risk word.

Check items:

• When a risk word is hit, a pop-up window will appear on the agent side for secondary confirmation.
• High-risk phrases (such as full wallet addresses) can be configured to block sending directly
• The content of the pop-up window clearly informs the triggering reason

6.3 View audit logs: agents, sessions, trigger times and risk words

All triggered records are written to the audit log.

Check items:

• The specific agent, session ID, trigger time and matching risk words can be viewed in the audit log.
• Logs can be exported or filtered to facilitate regular review

Day 7: Full-link acceptance and launch

On the last day, the three roles of user, agent, and administrator were simulated, and the whole process test from user consultation → automatic reply → manual agent → quality inspection was completed. It was officially launched after confirming that there were no abnormalities.

Acceptance Checklist:

• User Role Test: Initiate sessions through different channels (diversion links, Bot direct search), verify that the automatic welcome, menu commands, and multi-step processes all work properly
• Agent Role Test: Log in to the web console, receive conversations, send messages, use automatic translation (standard version includes AI translation), transfer conversations, and add notes (professional version)
• Administrator role test: View session statistics, user portraits (Professional version), audit logs (Professional version); confirm that the subscription status is normal
• Abnormal Scenario Test: When all agents are offline, whether users can receive offline prompts; whether the offload link is stable during peak periods
• Final check before going online: Bot avatar, name, and description have been edited through the console (no need for BotFather); the package validity period has not expired; the documentation and customer service Bot entrance is ready

FAQ

**Q: How long does it take to launch automated AI customer service? ** Answer: According to the 7-day checklist in this article, a standard team can complete the entire process from Bot configuration to online within 7 days. If the team already has a Bot and TG-Staff account, the core deployment can be completed in 3-4 days.

**Q: Does TG-Staff’s automated process require programming? ** Answer: No. TG-Staff provides a drag-and-drop visual process editor that allows you to build welcome messages, menus, and multi-step Bot interactions with zero code, making it suitable for operations teams without development resources.

**Q: What is the function of the diversion link (magic link)? ** Answer: The diversion link is a short link to the official domain name of TG-Staff. After the user clicks it, the IP, browser information and URL parameters can be captured before jumping to the Bot. It is often used for advertising traffic attribution and multi-channel tracking to help teams analyze the conversion effects of different channels.

**Q: What features does the free trial support? ** Answer: After registration, you can enjoy a 3-day free trial, which includes all the core functions of the standard version (real-time two-way chat, session offloading, offloading links, etc.). After the trial period, renewal is required to resume use.

**Q: How to ensure that the messages sent by agents are compliant? ** Answer: The professional version provides content risk control function. Risk phrases (including wallet addresses) can be configured. The system automatically detects the message before the agent sends it. If the risk phrase is hit, a pop-up window will pop up for secondary confirmation or prevent the message from being sent. All trigger records can be viewed in the audit log.

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ACT NOW:

• Sign up for TG-Staff free trial: https://app.tg-staff.com/
• Check the official documentation for detailed configuration guide: https://docs.tg-staff.com/
• Contact customer service Bot consultation package and technical support: @tgstaff_robot

It is recommended to take a screenshot or save the 7-day checklist in this article and execute it accordingly, so that the automated AI customer service will no longer be in a hurry.