Multi-Channel Attribution Diversion Guide: Using Telegram Diversion Links for Accurate Performance Tracking on TikTok, KOLs, and More

In cross-border customer service and community operations, Telegram Bot has become the core hub connecting users and teams. However, when your users come from TikTok short videos, KOL live streams, Google Ads, and email marketing simultaneously, teams often face a thorny issue: Where exactly did these users come from? Which channel brings higher consultation conversion rates? This is the application scenario of multi-channel attribution diversion. This article will guide you step-by-step on how to use Telegram diversion links to establish independent tracking for each channel, upgrading from fuzzy attribution to precise operations.

What is Multi-Channel Attribution Diversion and Why Does Telegram Bot Operation Need It?

Multi-channel attribution diversion, simply put, assigns a unique tracking identifier to each user source channel, so that when a user enters your Telegram Bot, the system automatically records their source. This way, when you analyze backend data, you can clearly see:

• How many users come from TikTok video descriptions?
• Are KOL A’s followers more active and have higher conversion rates than KOL B’s?
• Did the Google Ads campaign bring the expected number of inquiries?

For Telegram Bot operation teams, without attribution diversion, it’s like advertising in the dark. You only know someone is coming, but you don’t know who brought them, how much it cost, or whether it’s worth continuing to invest. Multi-channel attribution diversion is the key tool to solve this pain point, making every marketing budget traceable.

Three Major Pain Points of Traditional Telegram Attribution

Inability to Distinguish Which Channel Users Come From

When your Bot link is only one (e.g., t.me/your_bot), all users click into the same entry. Whether a user sees a TikTok video, KOL recommendation, or searches directly, the backend only shows “new user joined” without any source tag. The team cannot determine which channel is effective and can only allocate budgets based on gut feeling.

KOL Collaboration Effects Hard to Quantify

When collaborating with KOLs, you usually pay a fixed fee or pay per performance. But if you can’t distinguish which users are brought by the KOL, you cannot calculate each KOL’s CPL (cost per lead) or conversion rate. After the collaboration ends, you can only rely on screenshots provided by the KOL or user verbal feedback to evaluate effectiveness, making the data unreliable and lacking basis for renewal or price adjustment.

Inability to Compare ROI Across Multiple Channels

When running TikTok, Google Ads, Facebook, and email marketing simultaneously, without independent attribution links, you cannot scientifically compare the traffic cost and conversion efficiency of each channel. You might spend 80% of the budget on a channel that brings only 20% of effective inquiries. This information gap directly distorts ROI calculation and affects subsequent investment strategies.

Four Steps to Build a Telegram Multi-Channel Attribution Diversion System

Below, using TG-Staff’s diversion link feature as an example, we demonstrate how to build a complete attribution system from scratch. TG-Staff’s diversion link is a short URL under the official domain (e.g., https://app.tg-staff.com/abc123), which automatically redirects to your Telegram Bot and captures the visitor’s IP, browser information, and URL parameters.

Step 1: Create a Project and Diversion Link in the TG-Staff Console

1. Log in to the TG-Staff App Console.
2. Go to your Bot project settings page.
3. Find the “Diversion Link” module (available in Standard plan and above).
4. Click “Generate New Link,” and the system will immediately generate a unique short link, e.g., https://app.tg-staff.com/abc123.

Now you have the first diversion link, but it hasn’t been bound to a specific channel yet. Next, create independent links for each channel.

Step 2: Generate Independent Links for Each Channel and Add Tracking Parameters

Repeat the link creation for each channel, adding custom URL parameters during generation. TG-Staff will automatically capture these parameters and associate them with user sessions.

Channel	Link Example	Tracking Parameters
TikTok Short Video	https://app.tg-staff.com/tiktok01	?utm_source=tiktok&utm_medium=video
KOL A Live Stream	https://app.tg-staff.com/kola01	?utm_source=kol&utm_medium=live&ref=kola
KOL B Bio	https://app.tg-staff.com/kolb01	?utm_source=kol&utm_medium=bio&ref=kolb
Google Ads	https://app.tg-staff.com/ads01	?utm_source=google&utm_medium=cpc&campaign=spring

Naming Suggestions: Use clear, maintainable naming conventions, such as 渠道-日期-编号 (tiktok-2025Q1-01), to avoid confusion later.

Step 3: Embed Links into Channel Materials

• TikTok: Place the TikTok-specific link in the video description’s “Contact Us” section or pinned comment.
• KOL: Give the KOL link to collaborating influencers for their Telegram channel bio, live stream links, or pinned community messages.
• Google Ads: Use the short link in ad landing pages or direct links.
• Email Marketing: Insert the link in emails, along with UTM parameters for tracking.

Ensure that when users click the link, they are redirected to your Telegram Bot and trigger the welcome flow automatically.

Step 4: View Attribution Data and Channel Comparison in the Backend

In the TG-Staff backend, go to the “Diversion Link” statistics page to see metrics such as the number of user sessions, messages, and agent assignments brought by each link. By comparing data across different links, you can:

• Evaluate the traffic efficiency of KOL A vs. KOL B: Which link has a higher click-through rate? Which session has better conversion?
• Determine the quality of traffic from TikTok short videos vs. live streams: Are short video users more likely to inquire about products, or are live stream users more likely to make purchases?
• Optimize budget allocation: Invest more budget in channels with lower CPL and higher conversion rates.

Real-World Scenario: TikTok vs. KOL Channel Comparison

Imagine you run a cross-border e-commerce team that provides pre-sales consultation and order inquiries via a Telegram Bot. You collaborate with two KOLs (KOL A and KOL B) and run short video ads on TikTok. You generate unique diversion links for each channel:

• https://app.tg-staff.com/tiktok-video (TikTok short video)
• https://app.tg-staff.com/kola-live (KOL A live stream)
• https://app.tg-staff.com/kolb-bio (KOL B profile)

After one month, the backend data shows:

Channel	Sessions	Messages	Agent Handled	Avg Session Duration
TikTok Short Video	1,200	8,500	980	4.2 min
KOL A Live Stream	850	6,200	720	5.8 min
KOL B Profile	400	2,800	310	3.1 min

Interpretation:

• TikTok short videos brought the most sessions, but the average session duration is short, indicating users are mostly browsing quickly with limited deep consultation intent.
• KOL A’s live stream had fewer sessions than TikTok, but the longest average session duration (5.8 min) and high agent handling volume, suggesting live stream fans are more patient and have higher conversion potential.
• KOL B’s traffic was the weakest, with few sessions and short durations, possibly due to follower activity or promotion placement.

Optimization Suggestions:

• Increase budget for KOL A or try more live stream collaborations.
• Optimize TikTok short video content by adding hooks (e.g., limited-time offers, free trials) to encourage deeper consultation.
• Discuss with KOL B to adjust promotion placement or content format, or consider changing partners.

Notes and Best Practices

Link Naming Conventions and Maintenance

• Naming Rules: Use the 渠道-日期-编号 format, such as tiktok-2025Q1-01 and kol-zhang-03, and avoid vague names (e.g., test, link1).
• Regular Cleanup: When a channel collaboration ends or a campaign expires, promptly delete or archive the corresponding diversion links to prevent data contamination.
• Data Backup: Regularly export key attribution data to prevent data loss due to project expiration or plan changes.

Combining Session Routing Rules to Optimize Handling

When a channel (e.g., KOL live stream) brings a traffic spike, it is recommended to use TG-Staff’s session routing rules to ensure agents respond promptly and avoid user churn.

• Online-First Mode: Prioritize assigning sessions to currently online agents, suitable for scenarios with high traffic fluctuations.
• Round-Robin Mode: Distribute sessions sequentially among authorized agents, suitable for stable agent numbers and even traffic.

It is recommended to enable “Online-First” mode during traffic peaks, combined with TG-Staff’s agent online status, to achieve automatic load balancing.

Summary: From Fuzzy Attribution to Precision Operations

The core value of multi-channel traffic splitting lies in moving from “guessing” to “calculating”. In the past, you could only guess which channel performed better; now, you can verify each channel’s true contribution through data. Whether it’s TikTok short videos, KOL live streams, Google Ads, or email marketing, the traffic-driving effect of each channel is clearly visible. This not only helps you optimize your ad budget but also provides solid evidence for KOL contract renewals and price negotiations.

Start now: Log in to the TG-Staff App Console to create your first traffic splitting link and set up independent tracking for each channel. You can also refer to the Official Documentation for detailed configuration and parameter descriptions of traffic splitting links. If you have any questions, feel free to contact @tgstaff_robot online customer service.

Frequently Asked Questions

Q: Does the traffic splitting link support custom parameters? For example, can I add ?campaign=spring_sale?

A: Yes. TG-Staff’s traffic splitting link captures all custom parameters in the URL (such as utm_source, campaign, ref, etc.) and automatically associates them with the user profile of that session. It is recommended to use standard UTM parameter naming for cross-tool unified analysis.

Q: In a KOL collaboration, can I use multiple traffic splitting links to track different promotion positions?

A: Yes. You can generate separate traffic splitting links for the same KOL’s YouTube video description, live stream link, and community pinned message to compare the traffic-driving efficiency of different promotion positions. Just differentiate them by naming.

Q: Will the tracking data of traffic splitting links be retained permanently?

A: Data retention duration depends on your plan and project validity period. It is recommended to regularly export key data for backup. For specific retention policies, please refer to TG-Staff’s official documentation or contact customer service bot.

Q: If a user visits via a traffic splitting link and later enters the Bot through another channel, will the attribution be overwritten?

A: The attribution of the traffic splitting link is based on the first visit. The system records the first traffic splitting link through which the user entered, and subsequent visits will not overwrite the initial source. This helps maintain the stability and comparability of attribution data.

Q: How many traffic splitting links can I generate during the free trial? Is there a quantity limit?

A: During the free trial, you can use all features of the standard plan, including traffic splitting links. For specific link quantity limits, please refer to the plan page description. It is recommended to fully test the attribution effects of different channels during the trial period.