TG Customer Service Diversion Link Attribution: A Data Closed-Loop Guide for Ad Channels, KOLs, and Agent Conversations

Teams using Telegram Bot customer service often face a pain point: users arrive, but you don’t know where they came from.

You’ve invested in ads, KOLs have promoted your product, and social media posts have linked to your Bot—but how many users actually initiated a customer service conversation? Which channels have the highest conversion rates? Without answers to these questions, operational optimization is impossible.

TG-Staff’s diversion link attribution feature is designed to solve this data closed-loop problem. This article takes you from theory to practice, turning your TG customer service system into a measurable conversion node.

Why Does TG Customer Service Need Diversion Link Attribution?

In traditional Telegram Bot customer service, attribution is almost a blind spot:

• Ad Campaigns: After clicking Google Ads or Facebook ads to jump to the Bot, you can’t distinguish which conversations come from search ads versus display ads.
• KOL Promotions: You give the same Bot link to 5 KOLs—whose fans have higher conversion rates? You can only guess, or ask users to fill in an “invite code,” which increases user drop-off.
• Social Media Posts: The difference in traffic-driving effects between Twitter and Facebook lacks data support.

Without attribution, operational decisions rely on intuition. There’s no basis for deciding which channel to allocate budget to or which messaging to optimize for which user type.

The value of diversion link attribution: When a user clicks the link, source information (UTM parameters, IP, browser, etc.) is automatically captured without requiring users to fill anything in. Agents can see the user’s source during conversations, forming a complete data loop of “ad → click → conversation → conversion.”

What Is a Diversion Link? How Does It Capture User Source Data?

TG-Staff’s diversion link is an official domain short link with the format https://app.tg-staff.com/{code}.

Its workflow is simple:

1. Users click the link on an ad, KOL promotion, or social media post.
2. The link first redirects to TG-Staff’s tracking page, where the system automatically captures the visitor’s IP (geolocation), browser information (User-Agent), and all URL parameters (including UTM parameters).
3. After capture, the user is redirected to the corresponding Telegram Bot to start an auto-reply or manual conversation process.

Key point: Attribution data is recorded the moment the user clicks the link. Even if they start a conversation days later, agents can still view their source information.

Differences Between Diversion Links and Regular Bot Links

Comparison Dimension	Regular Bot Link	Diversion Link (TG-Staff)
Tracking capability	None	Automatically captures UTM, IP, browser info
Attribution data	Invisible	Stored in user profile, visible to agents
Use case	Simple traffic generation	Ad campaigns, KOL attribution, channel performance analysis
User experience	Directly opens Bot chat	Redirects to tracking page then enters Bot (almost no difference)
Plan requirement	None	Standard plan and above

What Parameters Does a Diversion Link Capture?

Diversion links automatically capture the following data and store it in the user’s “user profile”:

• UTM parameters: utm_source, utm_medium, utm_campaign, utm_content, utm_term
• Visitor IP: Resolvable to approximate country/city location
• Browser User-Agent: Operating system, device type, browser version
• Custom URL parameters: You can append any custom parameters (e.g., ?ref=kol_001), and the system will capture and store them in the profile

This data is visible in the right panel of the agent’s conversation window, allowing agents to gain user context without manual inquiry.

Practical Scenarios for Ad Channel and KOL Attribution

Scenario 1: Google Ads Campaigns

You run both search ads and display ads on Google Ads and want to distinguish their conversion performance.

How to do it:

• Search ad link: https://app.tg-staff.com/abc?utm_source=google&utm_medium=search&utm_campaign=summer_sale
• Display ad link: https://app.tg-staff.com/abc?utm_source=google&utm_medium=display&utm_campaign=summer_sale

When a user clicks and enters the Bot conversation, the agent can see that the user came from “google / search” or “google / display,” allowing evaluation of conversion rates for different ad types and optimization of budget allocation.

Scenario 2: KOL Promotions

You collaborate with 3 KOLs to promote your product. Each KOL has a different follower base, and you want to know which one drives the best traffic.

How to do it:

• KOL A: https://app.tg-staff.com/abc?utm_source=kol_a&utm_medium=telegram&utm_campaign=product_launch
• KOL B: https://app.tg-staff.com/abc?utm_source=kol_b&utm_medium=telegram&utm_campaign=product_launch
• KOL C: https://app.tg-staff.com/abc?utm_source=kol_c&utm_medium=telegram&utm_campaign=product_launch

Each KOL gets a unique link. By later checking the utm_source field in the user profile, you can compare the number of inquiries and conversion rates brought by each KOL.

Scenario 3: Social Media Post Segmentation

You post promotional content on both Twitter and Facebook and want to further understand which post type (tutorial vs. promotional) drives better traffic.

How to do it:

• Twitter tutorial post: https://app.tg-staff.com/abc?utm_source=twitter&utm_medium=post&utm_content=tutorial
• Twitter promotional post: https://app.tg-staff.com/abc?utm_source=twitter&utm_medium=post&utm_content=promo
• Facebook promotional post: https://app.tg-staff.com/abc?utm_source=facebook&utm_medium=post&utm_content=promo

By using the utm_content field to differentiate post types, agents can analyze traffic efficiency across different platforms and content types.

From Click to Conversation: How Attribution Data Runs Through the Traffic Diversion Pipeline?

Attribution data is not isolated; it runs through the complete traffic diversion pipeline:

1. Ad/Social Media Campaign: Users see an ad or post and click the diversion link.
2. Capture Attribution Data: TG-Staff captures UTM, IP, and browser information and stores it in the user’s “user profile.”
3. Bot Auto-Reply: Users enter the Bot, triggering welcome messages, menus, or auto-reply flows (using visual command flows).
4. Agent Handoff: If users need human assistance, the conversation routing rules assign them to an available agent.
5. Agent Views Source: The agent sees the user’s source channel, visit time, geolocation, etc., in the right panel of the conversation window, understanding user context without manual inquiry.

How to Configure Split Links and UTM Parameters?

The configuration process is simple and requires no development:

1. Log in to the TG-Staff Console (https://app.tg-staff.com/），进入「分流链接」模块。
2. Create a new split link: Click “Create Link”, enter a link name (internal identifier, e.g., “summer_promo_kol_a”), and select the target Bot project.
3. Generate a short link: The system automatically generates a short link in the https://app.tg-staff.com/{code} format.
4. Append UTM parameters: Add UTM parameters directly after the short link, for example ?utm_source=twitter&utm_medium=post&utm_campaign=summer_promo.
5. Copy and use: Copy the complete link to ad platforms, KOL promotional copy, or social media posts.

Notes:

• It is recommended to use all lowercase for UTM parameters (e.g., utm_source instead of utm_Source) to avoid data confusion due to case inconsistency.
• Avoid special characters (spaces, &, #) in parameters. If spaces are needed, use + or %20 instead.
• It is recommended to include at least the utm_source and utm_medium mandatory fields for easier filtering.

Limitations of Attribution Data and Best Practices

Attribution is not a silver bullet; understanding its limitations is key to using data correctly.

Common Issues

• UTM parameters may be truncated: Some browsers or ad blockers may remove UTM parameters, leading to data loss.
• User sharing and forwarding: When users copy and share links with others, the original UTM parameters may be preserved, but the source is no longer the original channel.
• Clicks within Telegram: When users click a split link on other platforms, Telegram first opens an external browser before redirecting to the Bot, which may result in the loss of some UTM parameters.

Best Practices

1. Set a fallback parameter: Include utm_source=direct in your diversion link as the default value, so that when UTM parameters are not passed, it can at least be marked as “Direct Traffic”.
2. Regularly check data integrity: Spot-check the source field in user profiles weekly or monthly to confirm data is being captured correctly.
3. Combine with session volume trends: Don’t rely solely on a single attribution metric. Evaluate channel performance by combining session volume trends, user inquiry content, and final conversion rates.
4. Avoid over-reliance on attribution: Attribution data is a reference for operational decisions, not the sole basis. User behavior is influenced by multiple factors, and attribution cannot explain all causality.

FAQ

Q: Do diversion links support custom domains?

A: Currently, TG-Staff provides official domain short links (app.tg-staff.com/{code}) and does not support custom domains. However, the short links themselves can be used for ad campaigns and KOL promotions without affecting attribution data capture.

Q: Does the data captured by diversion links expire?

A: Attribution data (UTM, IP, etc.) is captured when a user first visits the diversion link and stored in that user’s profile; it does not expire. Even if the user initiates a session days later, agents can still view their source information.

Q: Do UTM parameters conflict with the tracking parameters built into diversion links?

A: No, they do not conflict. Diversion links automatically capture all URL parameters, including UTM parameters. It is recommended to only append UTM parameters to the link and avoid adding other parameters with the same name to prevent overwriting.

Q: Does the free trial support diversion link attribution?

A: The diversion link feature is included in the Standard plan and above (including the free trial period). During the trial, you can fully experience creating diversion links and viewing attribution data. After the trial ends, you need to upgrade to the Standard or Professional plan to continue using it. See the pricing page on our website for details.

Q: Can attribution data be exported or integrated with third-party analytics tools?

A: Currently, attribution data can be viewed in the TG-Staff console (user profiles and data statistics), but direct export or API integration is not yet supported. You can manually record the source field in session details or combine it with other tools for secondary analysis.

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Next Steps

• Sign up for a 3-day free trial (https://app.tg-staff.com/），体验分流链接归因功能，看看你的用户从哪来。
• Check the official documentation (https://docs.tg-staff.com/）了解分流链接的详细配置与最佳实践示例。
• Contact the customer service bot (@tgstaff_robot) for tailored advice on attribution configuration and optimize your UTM parameter strategy for your business scenario.

Empower your TG customer service system to evolve from “receiving sessions” to “measuring sessions” — attribution data is the first step.