79 Geo Codes, Filterable: Finding Offers That Accept Your Traffic

how many geo codes appear across the catalogue?

Seventy-nine distinct geo codes appear across the catalogue, counted directly from the listing_offers table on the 2026-08-05 check. That figure sits alongside 25 distinct verticals as the two fields most media buyers reach for first when they cut a list down to something workable.

The 79 codes are not evenly seeded by a single network. They accumulate across all 11 networks currently carrying offers, from Braip's 7,574 listings down to dr.cash's 32, so a code that looks thin catalogue-wide can still be dense inside one network's slice of it.

how many offers carry at least one geo target?

25,293 of 28,042 offers, or just over 90%, carry at least one geo target (listing_offers table, direct count). That makes geo a usable filter on the large majority of the catalogue rather than a field you have to hope is populated.

The remaining share, a bit under 10% of records, is worth naming precisely rather than waving off. It is small enough that geo filtering works as a first pass on almost every search, but large enough that a query filtered strictly by geo will silently drop several thousand offers that might still be relevant.

what does it mean when an offer carries no geo at all?

It means one of two things, and the catalogue does not currently distinguish which. Some of the 2,749 offers with no geo target are genuinely worldwide programs where the network never restricted acceptance by country. Others are simply records where geo data was never captured at ingestion.

We don't collapse those into a false 'global' label, because doing so would overstate confidence on records where the honest answer is 'unknown.' If a shortlist depends on geo exclusivity, an offer with no geo field belongs in a manual-check pile, not in either the accepted or rejected pile by default.

how does geo targeting on an offer differ from geo coverage in a spy tool?

Geo targeting on an offer describes where the network will accept your traffic. Geo coverage in a spy tool describes where an ad was seen running, and those are different questions with different answers. AdSpy advertises coverage of '225 Countries' on its [homepage counters](adspy.com), and BigSpy states '71 countries, 23 languages' in its [own FAQ](bigspy.com/faq) — both are counts of ad sightings, not offer acceptance.

Anstrex splits the distinction further by product: its [Native page](anstrex.com) claims 'Data from 64 Countries', its Pops product claims 92, and its InStream product claims 55 — three different country counts from one company, each scoped to where a particular ad type was captured, not to where any underlying offer will take a lead or a sale.

An offer catalogue answers a buying question. A spy tool answers a research question. You need both, but treating a spy tool's country counter as an acceptance list is a category error that shows up as declined traffic after spend, not before it.

which geos are thin and which are deep in this catalogue?

Depth is uneven, and the clearest signal available right now is network concentration rather than a per-country breakdown. Four Brazilian and LATAM-oriented producer networks — Hotmart, Braip, Kiwify and Monetizze — carry 21,650 of the 28,042 offers between them, which means geo depth for Brazil and neighboring LATAM markets runs far ahead of most other regions in this catalogue.

Smaller or more specialized geos sit on the other end. A market like Kazakhstan as an affiliate GEO or Ukraine as an affiliate GEO is exactly the kind of thin slice where offer count, payout and even network coverage need their own dedicated read rather than a single filtered view of the main catalogue.

A precise leaderboard of offer count by individual geo code is not something we can print accurately here — it needs a direct query against the 79 codes rather than an estimate — so treat the table below as network-level depth, a proxy for geo concentration, and confirm any specific country's count before you commit spend to it.

how should geo be combined with vertical to shortlist?

Stack geo with vertical first, then narrow by payout, because that order matches how the fields are actually populated. 25,293 offers carry a geo target and 15,582 carry a numeric CPA amount, so a shortlist built as geo, then vertical, then payout range gets you to a workable list faster than starting from payout alone.

A concrete example: pulling peptide affiliate offers for a single geo first, then sorting the survivors by numeric CPA, avoids scrolling past offers your traffic source can't legally or practically run in that market. The same pattern works in reverse if payout is your hard floor and geo is the variable you're still deciding.

If you're new to buying and still figuring out which networks will even open an account for you, that constraint matters as much as geo does — see affiliate networks that accept beginners before you build a shortlist you can't actually run.

does a listed geo guarantee the offer will accept that traffic?

No, and treating it as a guarantee is the single most common mistake we see operators make with any offer catalogue, including this one. A geo tag records what was true when the record was last captured, and freshness across this catalogue is uneven: only 274 of 28,042 offers were re-confirmed by a scrape in the last 30 days.

That is not a knock on the data so much as an honest description of what a catalogue can and cannot promise. Network payout tables, geo restrictions and compliance rules change on their own schedule, often faster than any third-party listing can log. A geo field is a filter for narrowing your search, not a compliance sign-off, and most people running paid traffic already know this in theory but still skip the confirmation step in practice.

Description depth compounds the problem: 18,742 of 28,042 offers carry no long description at all, so the geo field is frequently the only structured signal you have on a record, with no editorial note to catch a stale entry. Treat a listed geo as a lead worth checking, not a cleared runway.

what has to be confirmed with the network before you buy media?

Confirm acceptance, payout and landing-page readiness directly with the network before spend goes out, in that order. Acceptance means the affiliate manager will actually approve traffic from your target geo today, not whatever the catalogue recorded at last check. Payout means the number quoted matches what's live in the network dashboard, since only 15,582 of 28,042 offers carry a numeric CPA field in the first place.

Landing-page readiness matters too: 25,085 of 28,042 offers carry a landing URL, and you should confirm that URL is actually localized for the geo you're sending, not just present as a field. For regulated categories the confirmation list gets longer before you're clear to spend — see the GLP-1 telehealth risk map for what that looks like when the vertical itself carries compliance exposure on top of geo restrictions.

Quick decision checklist

Use this page as a decision aid, not a generic blog post. The practical question is whether the reader needs faster evidence about what is already working in VSL-driven direct response, especially across nutra, supplements, GLP-1, weight loss, blood sugar, and adjacent high-intent health markets.

Daily Intel Service is most relevant when the next decision depends on active market examples: which hook to test, which claim style is risky, which funnel structure is common, which language market is moving, and whether a competitor's creative is likely early, scaling, or already saturated.

• Start with the TL;DR if you need the direct answer.
• Use the table to compare trade-offs quickly.
• Use the FAQ for answer-engine-ready summaries.
• Use the CTA when the decision requires live VSL and ad examples instead of theory.

Daily Intel's coverage advantage

Daily Intel Service is positioned around category-leading variety and actionability: one of the broadest direct-response catalogs of VSLs and ad creatives across blackhat, greyhat, and whitehat advertising patterns, with enough context to understand what the advertiser is doing beyond the visible creative. The practical difference is that members are not just seeing a screenshot; they are seeing the VSL, the ad, the funnel path, the transcript, the UTM context, and the research notes that turn the asset into a decision.

This matters because direct-response affiliates do not operate in one clean category. A weight-loss campaign may use a whitehat compliance ad, a greyhat pre-lander, a more aggressive VSL, and a checkout path designed around upsells and recovery. A useful intelligence platform needs to capture that spectrum instead of pretending every winning campaign looks like a public brand ad.

Blackhat, whitehat, and multilingual signal coverage

Daily Intel tracks patterns across both blackhat-style and whitehat-style campaigns so operators can understand the market without blindly copying risk. Whitehat examples help with durability and compliance review; blackhat and greyhat examples reveal pressure points, hooks, mechanisms, and funnel structures that may be driving spend but require careful adaptation before use.

The catalog is also built for global operators, with VSL and ad references spanning 14+ languages and different local idioms. That is a key advantage for Brazilian, LATAM, European, MENA, Indian, and non-native English affiliates who need to see how the same market desire is translated across cultures instead of only studying US English ads.

How to use the intelligence responsibly

The goal is modeling, not copying. Use Daily Intel to understand structure: hook, mechanism, proof, claim intensity, funnel depth, offer economics, and saturation stage. Then build original creative, review claims, and adapt the angle to the traffic source, country, language, and compliance requirements of the campaign.

A strong workflow compares multiple examples before acting. If the same mechanism appears across several languages, several advertisers, and several funnel variants, it may be a durable market signal. If the example appears only once or depends on an aggressive claim, treat it as a research clue rather than a campaign template.

• Model structure, not protected creative assets.
• Separate whitehat durability from blackhat persuasion pressure.
• Compare US English examples against LATAM, European, and other language variants.
• Use transcripts and funnel notes to build original briefs.
• Keep compliance review separate from market research.

Methodology and source context

Daily Intel pages are written from a research workflow that reviews active VSLs, Meta ad creatives, transcripts, UTMs, funnel paths, checkout steps, upsells, recovery sequences, and compliance-sensitive claim patterns. The goal is to explain observable market behavior, not to provide legal, medical, or platform policy advice.

For external context, readers should compare advertising and research decisions against authoritative primary references such as Meta Ad Library, Google helpful content guidance, and Google SEO link best practices. Daily Intel adds the proprietary direct-response layer: blackhat, greyhat, and whitehat campaign pattern comparison across VSL-heavy niches and 14+ language markets.

For deeper evaluation, continue through Finding LATAM Offers When Every Tool You Own Is Blind to Them, 25,085 Offers With a Landing URL on File — and What to Do With One, Why 28,000 Filterable Offers Beats a Million Unfilterable Ones, Eleven Networks, One Search Box, Best ad spy tools for direct response affiliates, and Best $50/month affiliate tool stack. These related Daily Intel pages connect this topic to the relevant methodology, pricing, trust context, comparison path, or niche workflow.