Citing Our Figures: What Each Number Means and When It Was Counted

which counts do we publish and how is each defined?

Every count on Daily Intel Service traces to one column in one table, not an estimate rounded for a landing page. The offer count of 28,042 comes from rows in the listing_offers table carrying status 'active', counted directly on 2026-08-05. The creative-side counts come from four separate migration tables — ads, VSLs, library items and media assets — each tracked independently rather than blended into one figure.

Beyond raw volume, the catalogue spans 25 distinct verticals and 79 distinct geo codes across those 28,042 offers. Of those, 25,293 carry at least one geo target and 25,085 carry a landing URL, both counted the same way on the same date. Networks vary widely in how much of the catalogue they contribute, which the table below breaks down by network.

when was each figure last counted?

Every figure on this page was counted on 2026-08-05, against the live production database rather than a cached export or a marketing deck. That date is a snapshot, not an expiration date — the same queries can be re-run later to produce a new, equally citable figure. Nothing here is frozen at a product launch and left unchanged for a year.

Counting date and content freshness are two different things, and treating them as one would overstate what the catalogue can promise. Only 274 of the 28,042 offers were re-confirmed by a scrape in the 30 days before the count, so 'counted on 2026-08-05' should not be read as 'verified live on 2026-08-05' for every row. The count is exact; the underlying offer data is not uniformly fresh.

what does 'active offer' mean in our schema?

'Active' means the offer carries status='active' in the listing_offers table at the moment it was counted, nothing more. It is not a claim that the advertiser is currently running traffic, that the payout is still honored, or that the landing page still resolves — it is a status field set when the offer was captured or last confirmed by the catalogue's own process.

• A status of 'active' does not guarantee a recent scrape: only 274 of 28,042 offers were re-confirmed within the 30 days before the count.
• Not every active offer carries a geo target — 25,293 of 28,042 do, leaving roughly 2,749 without one recorded.
• Not every active offer carries a landing URL — 25,085 of 28,042 do.
• Two configured networks, Digistore24 and TerraLeads, currently carry zero active offers; the network exists in the schema but is empty in the catalogue.

what does the ad count include and exclude?

The published ad count of 4,296 includes only rows in the ads_migration table: individual ad creatives tied to catalogue offers. It excludes VSLs, tracked separately in vsl_migration at 3,979; library items, tracked in library_items at 745; and media assets, tracked in media_migration at 6,080. Each of those is its own countable figure and should be cited as such rather than folded into 'ads'.

On raw ad volume, the comparison to larger spy tools is not close, and this catalogue does not claim otherwise. AdSpy states '208,180,000 + Ads' on its own homepage and BigSpy claims 'over 1 billion pieces of ad creative data,' neither with a stated as-of date next to the counter. Set against 4,296 dated ads, the honest read is that this catalogue is smaller by orders of magnitude on creative volume — and arguably the more citable of the two figures, since a dated count can be checked against a moment in time in a way an undated counter cannot.

which claims do our numbers explicitly not support?

These figures do not support an ad-volume superiority claim, an 'updated daily' claim, or a claim that the catalogue is uniformly detailed, each for a specific counted reason. On volume, competitors publish far larger creative counts than the 4,296 ads tracked here. On freshness, only 274 of 28,042 offers were re-confirmed by a scrape in the 30 days before the count, short of what 'daily' would require. On depth, description coverage is uneven, as the table below shows.

The catalogue's actual advantage is structural coverage, not size. None of the eleven researched competitors — AdSpy, AdPlexity, Anstrex, BigSpy, PowerAdSpy, Minea, Dropispy, Foreplay, AdHeart, PiPiADS or Atria — names Hotmart, Braip, Kiwify or Monetizze anywhere in its stated coverage, and those four Brazilian and LATAM producer networks alone account for 21,650 of the 28,042 offers. A researcher writing about coverage gaps between Western and CIS-facing tools, such as the Daily Intel Service vs Publer: Western vs CIS Ad Data comparison, should cite that network breakdown rather than a generic 'more offers' claim.

how should a figure be attributed?

Attribute a figure by naming its source table and count date in the same sentence as the number itself — for example, '28,042 active offers (listing_offers, counted 2026-08-05).' A bare number with no source table attached is not verifiable against this catalogue by any fact-checker, however confident the phrasing sounds.

The same discipline applies to pages that cite these figures secondhand. A page such as Tyver vs Daily Intel Service: $79 and $29.90 Compared should restate a field count like the 15,582 numeric-payout figure with its count date attached, rather than repeat it as if it were a fixed, undated fact.

Locale pages carry the same obligation. A page describing translation coverage, such as Daily Intel Service in Ukrainian: What the Locale Covers, should cite the 16-language queue and its zero-recorded-failure rate directly from the content-factory journals, dated, rather than paraphrase an earlier article that already lost the date.

how often do these numbers move?

These numbers move continuously, because the catalogue is a live database rather than a static export refreshed on a fixed schedule. Networks add and remove offers on their own timetables, and Braip alone carries 7,574 of the 28,042 offers — the single largest network share — so a change in one network's feed can shift the total noticeably within days.

The scrape-freshness figure moves on a slower, less predictable cycle than the raw offer count. With only 274 of 28,042 offers re-confirmed in the 30 days before the 2026-08-05 count, a comparison built on this catalogue for a fast-moving claim should be re-counted rather than reused past a few weeks old.

who should be contacted to confirm a figure?

Contact the Daily Intel Research Desk at contact@nutra.international to have any figure on this page re-counted or its source table confirmed before publication. Because every number here is a direct database count rather than a fixed export, the desk can re-run the same query and report the current figure alongside the date it was pulled.

Pricing questions route separately from catalogue-count questions, since this page carries no price figures of its own. A reader confirming access terms or current pricing should start from Daily Intel Service for CIS Buyers: Price and Access and contact the desk directly if a figure there needs re-verification against the same standard used here.

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 Where This Sits in a Stack That Already Has an Ad Spy Tool, What This Is Not: Six Things We Don't Do, How Fresh the Catalogue Actually Is — the Uncomfortable Answer, Two Vendors Claim to Be the Biggest. We Don't, and Here's the Number., 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.