Every sales conversation starts with the same question: who is your audience — and why you rather than the title next door? Cookieless Audience gives publishers a documented, coded answer: a domain-level audience profile drawn from fixed v1.0 vocabularies aligned with IAB Audience Taxonomy 1.1, plus the same profile for every competitor title you get comped against. It powers pitch decks, seller-defined audience labels and direct-sales narratives — without cookies, panels or a data-science team.
Large publishers answer the audience question with first-party data teams and survey programmes. Everyone else answers it with panel numbers that thin out below the head of the market, or with media-kit language — “affluent, engaged, influential” — that buyers have learned to discount. And when an agency comps your title against three competitors, their data about you is usually better than yours.
Domain-level audience profiling changes the footing. Your properties — and your competitors’ — sit in the same 102M-domain database, described with the same coded fields: demographics, 285 sub-interests, 283 purchase-intent segments, B2B firmographics and a resolved persona, each with a banded confidence value. The profile is computed from the property itself, not from visitor cookies, so it covers the Safari, Firefox and iOS readership — roughly 40%+ of traffic — that cookie-derived audience counts systematically miss. Cookies remain on Chrome, but a premium editorial audience skews heavily to exactly the browsers that block them.
The result: a defensible, reproducible audience story you can put in front of a buyer, with codes a buyer’s own analysts can verify against the published taxonomy.
A domain-level profile describes your whole readership with one method — because it never depended on the identifier in the first place.
The same domain file feeds three distinct revenue workflows — each with its own dedicated guide.
Replace media-kit adjectives with vocabulary values: your readership’s age brackets, income bands, life stages, top INT.* and PI.* codes — and how each over-indexes against your named competitor set. See publisher pitch decks.
SDA asks publishers to describe their own inventory in taxonomy terms. Because every attribute here is aligned with IAB Audience Taxonomy 1.1, the profile of each of your domains translates directly into SDA-style audience labels. See seller-defined audiences.
Work out which advertiser categories your audience over-indexes for — purchase-intent codes are effectively a prospecting list — and arrive at the meeting knowing how you compare to every title on the buyer’s shortlist. See publisher sales intelligence.
No integration project. The dataset is a flat file you filter in a spreadsheet or warehouse — or query per-URL through the real-time API for section-level analysis of your own properties.
Look up your domains and read the coded audience attributes and resolved persona for each property or vertical site.
Look up the competitor titles you are sold against. Same fields, same vocabularies — a like-for-like comparison by construction.
Identify the interests, intent segments and demographics where your audience concentrates more strongly than the comp set.
Turn the differentiating codes into pitch-deck slides, SDA labels and direct-deal audience descriptions buyers can verify.
Vocabularies are fixed at v1.0, so the same comparison re-runs cleanly against each quarterly data refresh.
An independent outdoor publisher wants a direct deal with an equipment advertiser. Here is the audience evidence its domain profile provides — codes on the left, what the buyer reads on the right.
| Field | Profile value (code) | Reads as | Confidence |
|---|---|---|---|
| age_bracket | 25_34, 35_44 | 25–44 core readership | high |
| income_level | upper_middle | Upper-middle income | high |
| urbanicity | suburban, small_town | Suburban and small-town skew | medium |
| interest | INT.travel.camping | Camping | high |
| interest | INT.travel.adventure_travel | Adventure travel | high |
| purchase intent | PI.sporting_goods.outdoor_recreation_equipment | Outdoor recreation equipment | high |
| purchase intent | PI.travel.camping | Camping trips & bookings | medium |
PI.sporting_goods.outdoor_recreation_equipment), then places the two generalist comp titles from the agency’s plan next to it — both indexing on broad news interests but neither on outdoor equipment intent. That is a differentiated, checkable argument for a direct deal or a premium PMP, not an adjective. Explore any domain’s profile in the audience demo dashboard.| Panel measurement | First-party surveys | Cookie-derived segments | Domain-level profiles (this dataset) | |
|---|---|---|---|---|
| Covers mid-size & niche titles | Thin below the head of the market | Yes, but only your own titles | Sparse where cookies are blocked | Yes — 102M domains, head to tail |
| Competitor comparison | Only for panelled competitors | No — no competitor data | Inconsistent across vendors | Same fields for every domain, yours and theirs |
| Safari / iOS readership | Modelled | Covered for respondents | Largely invisible | Covered — profile is a property of the domain |
| Buyer verifiability | Panel methodology | Self-reported | Vendor black box | Fixed v1.0 vocabularies, published taxonomy |
| Cost & effort | Subscription | Ongoing programme | Contract-dependent | From $490 self-serve, quarterly refresh |
Yes. The demo dashboard lets you look up individual domains and inspect their audience attributes interactively. For a full comp-set analysis you would buy a tier — the top-100k file is $490 one-time, the top-1M file is $1,990 with instant checkout — or a vertical slice ($190–$490) covering your market.
SDA participation requires publishers to label their inventory using standard audience taxonomy terms. Every attribute in this dataset comes from fixed v1.0 vocabularies aligned with IAB Audience Taxonomy 1.1 — demographics, interests, purchase intent and personas — so a domain’s profile maps directly onto the taxonomy IDs SDA labels are built from. You still control which labels you declare; the dataset gives you the evidence base for declaring them.
Every attribute carries a banded confidence value (low / medium / high), and the vocabularies are published openly on the taxonomy page, so you can see exactly what each code claims. Publishers with first-party data can treat the profile as an external, third-party view — useful precisely because it is the same view a data-driven buyer would compute about you — and contact us about discrepancies.
No. First-party data is your most valuable asset and stays yours. This dataset adds what first-party data cannot: a consistent, like-for-like profile of every competitor title, and coverage of the readership you cannot observe through cookies — Safari, Firefox and iOS users, roughly 40%+ of traffic. There is no PII anywhere in the pipeline, so nothing here touches your consent posture.
Turn coded audience evidence into winning sales decks.
Find the advertiser categories your audience over-indexes for.
Label inventory with IAB Audience Taxonomy 1.1-aligned codes.
The buy-side view: persona planning without enterprise contracts.
Look up your own domains and your comp set in the demo, or download a database tier and build the comparison this week.
Open the audience demo See database pricing