Telegram Ads Competitor Research: How to Track What Rivals Are Running (2026)#

Telegram is one of the most opaque advertising platforms available today. Unlike Google or Facebook, there is no public ad library, no transparency tool, and no official way to see what your competitors are running. Sponsored messages appear in channels and disappear — unless something captures them first.

That gap is exactly what makes systematic competitor research both difficult and valuable. If you can see what rivals are spending on, you gain an asymmetric advantage: you know their positioning, their angles, their channel targets, and their timing before you spend a dollar of your own budget.

This guide walks through a five-step process for reverse-engineering competitor Telegram ad strategies using an archived dataset of sponsored messages.

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Why Telegram Ad Competitor Research Matters#

When a competitor runs Telegram ads, they are making implicit decisions about:

• Which audiences are worth paying to reach (reflected in which channel categories receive their ads)
• What messaging resonates (reflected in creative text, CTA language, tone)
• What budget they are committing (inferred from how many channels receive the ad and how frequently it rotates)
• What seasonal moments they prioritize (reflected in when campaigns appear and disappear)

On Facebook or Google, you can often see competitor ads directly in the platform's ad library. On Telegram, that data only exists if someone has been systematically polling the sponsored messages API across thousands of channels simultaneously. That is what Telegram Ads Spy does — running continuous ingestion across 9,000+ channels so that you do not have to.

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What Data You Can Extract#

Before diving into steps, it helps to know what the archive actually contains for each sponsored message:

• Creative text — the full ad copy including title, body, and CTA button text
• Media type — banner (photo/video), channel-picture, or text-only
• Accent color — brand color used in the ad card
• CTA URL — the landing page or Telegram deep link
• Channel target — which channel the ad appeared in, and that channel's niche/language
• Timestamp — when the impression was recorded
• Payment source — whether the ad comes from the EUR cabinet (can_report: false) or TON-based spend (can_report: true)

From these fields you can reconstruct a detailed picture of any advertiser's Telegram presence over time.

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Step 1: Identify Competitors in the Archive#

Start at the search bar. You have two main approaches:

Search by advertiser name or brand. If your competitor is a crypto exchange called "AlphaSwap," search for "AlphaSwap" in the creative text field. The archive returns all creatives containing that term, sorted by date. You immediately see every variant they have ever run.

Search by keyword or niche. If you do not know your competitors by name, search for terms your audience cares about — "copy trading," "p2p exchange," "crypto signals," "forex robot." Every advertiser who has used those terms in their copy appears in the results. Filter by language to narrow to your market.

Once you identify relevant advertisers, click through to their advertiser profile. This page aggregates all creatives attributed to that brand, deduplicated and sorted chronologically.

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Step 2: Analyze Creative Rotation Patterns#

A single creative tells you what a competitor is saying right now. A sequence of creatives over weeks tells you how they think about creative strategy.

Look at:

• Number of variants running simultaneously. An advertiser running 6-8 distinct creatives at once is A/B testing aggressively. One running a single creative for 4 weeks is either confident or under-resourced.
• How often copy changes. Frequent copy refreshes suggest active optimization. Stable copy over months suggests a proven performer they are milking.
• How often media changes. If they keep the same banner for 6 weeks, that banner is working. If they cycle banners every 10 days, they are testing visual angles.
• What they test. Look for systematic variation: same copy, different CTAs; same CTA, different benefit claims; same offer, different tones (urgent vs. aspirational).

This rotation pattern tells you how sophisticated their creative operation is and gives you clues about what is and is not converting for them.

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Step 3: Map Channel Targeting#

Each impression in the archive carries the channel it appeared in, along with that channel's primary niche and language classification.

Build a frequency table: which channel categories receive the most impressions from this advertiser? A crypto exchange targeting predominantly finance/trading channels is playing a narrow, high-intent game. The same exchange also appearing in general tech and lifestyle channels is trying to build broader brand awareness.

This channel map tells you:

• Which audiences your competitor considers high-value
• Which niches they are ignoring (potential opportunity for you)
• Whether they are expanding or contracting their channel reach over time

If a competitor suddenly starts appearing in a new channel category, they are either testing a new audience or responding to saturation in their core targets.

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Step 4: Identify Seasonal and Event-Driven Patterns#

Sort your competitor's creatives by date and look for clustering. Campaigns that spike around specific dates usually correspond to:

• Token launches or exchange listings
• Sports events (World Cup, Champions League finals — common for betting and crypto apps)
• Market volatility moments (BTC price moves triggering urgency campaigns)
• Regulatory news (competitors front-running rule changes with targeted messaging)
• End-of-quarter promotions

Once you identify these patterns, you can anticipate when they will advertise next. If a competitor consistently runs heavy campaigns around major sports events, you know to either counter-program or outspend them before the event begins.

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Step 5: Extract Landing Page CTAs#

The CTA URL in each creative is often the most overlooked data point. URL patterns reveal:

• Which product or offer the campaign promotes. /sign-up/promo-bonus vs. /trading/futures vs. /app/download — each targets a different funnel stage.
• UTM parameters. Competitors who include UTMs in their Telegram URLs expose their internal campaign naming conventions, sometimes revealing channel-level or creative-level tracking.
• Landing page language and localization. Does their CTA URL point to a localized page? If they are sending Russian speakers to an English landing page, there is a conversion gap you can exploit.
• Button text patterns. "Trade now" vs. "Get bonus" vs. "Join 2M traders" — each signals a different value proposition hypothesis.

Collect CTA button text across all creatives and look for what the competitor tests and what they converge on. The button text they settle on after rotation is usually the one that performed best.

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How Telegram Ads Spy Makes This Systematic#

Manually tracking competitor Telegram ads is nearly impossible without tooling. The sponsored message API only returns ads visible in channels you are monitoring at the moment you poll. You would need accounts in hundreds of channel categories, polling every 30 minutes, 24 hours a day.

Telegram Ads Spy handles this infrastructure layer. The archive currently covers 9,000+ channels across all major niches and languages, with continuous ingestion. You get:

• Full-text search across all captured creatives
• Advertiser profiles that aggregate all impressions by brand
• Filters for language, niche, date range, media type, and payment source
• Keyword alerts that notify you when a new creative matching your terms appears

This turns competitor research from a manual, sampling-based exercise into a systematic, continuous workflow.

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Practical Example: A Hypothetical Crypto Exchange#

Imagine you are launching a futures trading platform competing with "NovaTrade Exchange."

1. Search "NovaTrade" — find 34 unique creatives over the past 90 days.
2. Their creative rotation shows heavy testing: 8 variants running in parallel, cycling every 12-15 days.
3. Channel map shows 70% of impressions in crypto/finance channels, 20% in tech, 10% in general news.
4. Date analysis reveals spikes around two BTC volatility events and one exchange listing.
5. CTA URLs consistently point to /futures/signup?bonus=10 — they are leading with a signup bonus for futures traders.
6. Button text evolution: started with "Start trading" → converged on "Get 10% bonus" after week 3.

From this you learn: futures signup with a percentage bonus is their proven hook, they are not yet penetrating lifestyle audiences (opportunity), and they activate campaign surges around market volatility. Your launch strategy can counter-position on a different hook, target the lifestyle channels they ignore, and have a campaign ready before the next major market move.

That is what systematic competitor research on Telegram looks like. The data exists in the archive — the question is whether you use it.

tgadsspy research (2026). Telegram Ads Competitor Research: How to Track What Rivals Are Running (2026). tgadsspy.com. Retrieved from https://tgadsspy.com/blog/telegram-ads-competitor-research-guide-2026