TG Bot Customer Service Auto-Reply Keywords & Command Menu Design Guide: 4 Practical Steps to Reduce Repetitive Inquiries

Operating a Telegram Bot customer service channel, the most time-consuming part is often not complex technical issues, but repeatedly answering the same questions like “What’s the price?”, “When will it ship?”, “How to get a refund?”. If agents spend a lot of time each day copying and pasting standard replies, not only is it inefficient, but it also delays conversations that truly require human intervention. By designing a proper tg bot customer service auto-reply keyword and command menu system, you can reduce repetitive inquiries by over 80%, allowing agents to focus on high-value conversations.

Based on TG-Staff’s flow editor and routing rules, this article explains in 4 steps how to build an efficient and iterable auto-reply system from scratch, along with a practical configuration checklist.

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Why Does Your Telegram Bot Customer Service Always Answer Repetitive Questions?

Many teams face three typical challenges when using Telegram Bot for customer service:

• Manually replying to high-frequency questions: Agents handle 50-100 conversations daily, over 60% of which are the same questions, requiring manual input or pasting of standard scripts each time.
• Users can’t find self-service entry points: The bot menu only has simple /start and /help commands, so users can only trigger human agents by typing natural language, unable to get common answers on their own.
• Inaccurate keyword matching: Simple keyword replies are configured, but often trigger incorrectly (e.g., “quote” and “price” mixed up), or fail to match when users phrase things slightly differently.

The core solution to these problems is to establish a combined system of keyword auto-replies + command menus. Keyword auto-replies are suitable for single-turn Q&A (e.g., “shipping time” triggers a fixed reply), while command menus are ideal for multi-step guidance (e.g., /start → select “View Order” → enter order number). Together, they cover most common scenarios.

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Step 1: Plan High-Frequency Questions and Keyword Mapping Table

Before configuring any tools, spend 30 minutes compiling a “high-frequency question list” — this is the foundation of the entire auto-reply system.

Extract Top 10 High-Frequency Questions from Historical Conversations

If you have historical chat records, you can directly filter the most repeated content. Below is an example of high-frequency questions for a typical e-commerce or SaaS customer service:

Question Type	Common User Input	Standard Reply
Price Inquiry	”price”, “how much”, “fee”, “plan”	Reply with current plan prices and attach link
Shipping Time	”shipping”, “logistics”, “how long to arrive”	Inform about shipping cycle and tracking method
Refund Process	”refund”, “return”, “cancel order”	Step-by-step instructions for refund application
Account Issues	”can’t log in”, “forgot password”, “account banned”	Guide to self-service recovery or submit ticket
Technical Support	”error”, “error code”, “not working”	Request screenshot and transfer to human agent

Key point: For each question type, collect 3-5 common variations of actual user input. For example, for “price”, include “how much”, “what’s the fee”, “plan price”, “monthly cost”, etc., to avoid matching failure with only one word.

Keyword Conflict and Priority Handling Principles

When the same user input might match multiple keywords (e.g., both “price” and “quote” point to the same reply), clarify priorities:

• Exact match first: If a user types “plan price”, prioritize matching the full phrase rather than splitting into “plan” and “price” separately.
• Short word conflicts: Avoid using single characters or very short words (e.g., “p”, “c”) as standalone keywords, as they are prone to false triggers. Use at least 2-3 characters.
• Exclusion word mechanism: For example, although “price” and “quote” are similar, business scenarios may differ (“quote” might refer to custom quotes). Configure different replies or use exclusion lists to prevent confusion.

Best practice: First create a mapping table in Excel or Notion with columns like “Keyword Group”, “Reply Content”, “Priority”, and “Transfer to Human”, then import into the flow editor.

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Step 2: Build Auto-Reply Menu with Visual Flow Editor

TG-Staff’s drag-and-drop flow editor lets you build complete auto-reply logic without coding. Here are the core steps.

Building a Welcome Message and Main Menu

1. Create a New Flow: In the TG-Staff console → Flow Editor → New Flow, name it “Main Menu”.
2. Add a “Start” Node: Set the trigger condition to the /start command or when a user first enters the Bot.
3. Write the Welcome Message: Include brand introduction and common feature prompts, for example:

   Welcome to XX Customer Service Center! 👋
   You can enter the following keywords for quick help:
   • “Price” → View package prices
   • “Shipping” → Track logistics
   • “Agent” → Transfer to a human
   Or use menu commands: /price, /shipping, /support

4. Link Menu Options: Add 4-6 buttons or text options, each pointing to a different sub-flow or reply node.

Configuring Keyword Trigger Branches

1. Add a “Keyword Match” Node: Drag a “Keyword Match” module into the flow.
2. Enter the Keyword List: For example, for the “Price” node, enter 价格, 多少钱, 费用, 套餐价格, 月付 (separated by commas or new lines).
3. Set Reply Content: Supports plain text, buttons, images, or links. For example:

   Our packages include Standard and Pro versions. For details, see: Package Page
   If you want to learn about specific features, enter “Feature Comparison”.

4. Test Hit Rate: In the TG-Staff test panel, enter different variants (e.g., “How much is this package?”) to confirm matching success.

Note: For high-frequency questions (e.g., “Price”), you can set it to “Exact Match” mode to prevent the word “Price” in “Price List” from triggering other replies. For questions with clear intent (e.g., “Refund Process”), using “Partial Match” is more user-friendly.

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Step 3: Set Session Routing Rules to Ensure Complex Issues Reach Human Agents

No matter how perfect the auto-reply, there will always be users with complex issues that cannot be covered. At this point, you need to properly configure routing rules so that sessions requiring human intervention quickly reach the agents.

In TG-Staff, you can configure two routing rules for each project:

• Round-robin (default): Distributes sessions that don’t hit auto-replies to available agents in order, suitable for teams with a fixed number of agents and balanced workloads.
• Online-first: Prioritizes online agents, falling back to round-robin when all are offline, ideal for teams with irregular working hours.

Configuration recommendations:

1. In Console → Project Settings → Session Routing, select “Online-first” mode (suitable for most teams).
2. Set the default action for “Unmatched auto-reply”: jump to the “Transfer to agent” node or directly enter the routing queue.
3. Add a “Human agent” keyword node in the flow. When users input “agent”, “customer service”, or “transfer to agent”, they trigger the routing link directly without waiting for auto-reply execution.

This way, users immediately receive a standard reply when typing “price”, and are instantly transferred to an agent when typing “agent”, without interference.

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Step 4: Continuously Optimize Keyword Library with User Profiles and Statistics

The auto-reply system is not a one-time task; it requires continuous iteration based on actual data. The user profile and statistics features in TG-Staff Pro help you pinpoint issues precisely.

View Sessions with Unmatched Keywords

Navigation: Console → Session Records → Filter “Unmatched auto-reply”.

This lists all session content where user input was not hit by any keyword. Regularly (recommended weekly) review these records to discover new high-frequency question variants. For example, users might input “how to pay” or “payment methods”, which would be missed if only “price” and “cost” were configured.

Steps:

1. Export or copy unmatched session content.
2. Sort by frequency and extract the top 5 new keywords.
3. Return to the flow editor, add new words to the corresponding keyword nodes, or create new nodes.

Tailor Reply Content by User Segments

TG-Staff Pro supports user tags and profiles. You can differentiate reply content based on user behavior (e.g., “new user”, “VIP customer”, “frequent inquiry user”). For example:

• When a new user first asks about “price”, the reply focuses on free trial and entry-level plans.
• When a VIP customer asks about “price”, the reply includes exclusive discount codes or upgrade guidance.
• When a frequent refund user asks about “refund”, the reply directly provides a link to a human agent, reducing self-service time.

This granular optimization not only improves experience but also reduces agent handling costs.

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Frequently Asked Questions

Q: Can keyword auto-reply and command menu be used simultaneously? A: Yes. Keyword auto-reply matches user input first, while the command menu provides structured guidance. They can be chained in the TG-Staff flow editor, e.g., after a user types “price” to trigger a reply, a menu option can be presented.

Q: How to avoid false keyword triggers? A: It’s recommended to set “exact match” or “partial match” mode for each keyword node in the TG-Staff flow editor, use exclusion word lists (e.g., configure “price” and “quote” separately), and regularly check for false hits through session records.

Q: Can I configure auto-reply during the free trial? A: Yes. After registering TG-Staff, you get a 3-day free trial, during which you can fully use the flow editor, keyword matching, and command menu. After the trial, you need to subscribe to Standard or Pro to continue.

Q: Does keyword auto-reply support multiple languages? A: Yes. TG-Staff’s auto-translation feature (Standard includes AI translation, Pro additionally supports Google/DeepL) allows agents to translate replies, but keyword matching is based on the original input text. It’s recommended to configure keyword lists for corresponding languages in multilingual scenarios.

Q: Do session routing rules affect auto-reply? A: Yes. Routing rules (round-robin/online-first) only affect sessions that require human handling. Sessions that hit keyword auto-reply do not enter the routing queue, so they don’t interfere.

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Through these 4 steps, you can build an efficient tg bot customer service auto-reply system covering over 80% of common inquiries. To further optimize command menu templates or configure routing rules, refer to the TG-Staff documentation for detailed guides. For one-on-one configuration help, contact the support bot: @tgstaff_robot.

Start now and register for a free TG-Staff trial to experience the efficiency gains from keyword auto-reply and command menus.