--- title: Editorial Analytics & Content Gap Analysis for Publishers description: "Content gap analysis from live reader behavior: what your audience searches for and never finds, archive pieces with live demand, and what to stop writing." url: https://preview.artificialpoets.com/use-cases/editorial-intelligence/ site: Artificial Poets type: page date: 2026-08-09T19:46:31+00:00 modified: 2026-08-18T02:10:14+00:00 --- # See What Readers Want Before You Commission It **Measured on live deployments** "What should we publish next — and what does our audience want that we've never given them?" Your readers answer that every day: in what they search for and do not find, what they reach for from each article, and which archive pieces would still be read if anything surfaced them. The Platform logs those signals as a by-product of serving and reads them back as a gap map. [See it on my numbers](/request-a-demo/) Horse & Rider · Ride TV · Equine Network · Equus Magazine · The Score · Equine Network Lockup ## The problem, in your numbers The referral cliff is a market condition. What you commission next is an editorial decision — and the best demand data left is first-party. - **−33%** Google traffic to publishers, in one year (−38% US) — Chartbeat / Press Gazette - **38%** Executives confident about the year ahead, against a −43% three-year search-referral forecast (Reuters Institute) - **3–4 → 1–2** Pageviews per arriving visit under zero-click search (Nitropay) - **38% → 41%** Internal traffic's share of publisher pageviews, one year (Chartbeat) — the growing channel runs on your own pages ## The gap map Reader demand against library coverage: demand read from on-site search and the interest graph, coverage from the vectorized library. Two of the four zones cost nothing new to act on. Archive gold is inventory you already paid for, and Overserved is work you can stop doing. - **Blind spot** — High demand, no content. Commission here. - **Archive gold** — Old content, live demand. Resurface, don't rewrite. - **Sweet spot** — Live demand, current coverage. Defend it. - **Overserved** — Heavy coverage, thin demand. Stop commissioning here. ## The evidence, at its honest tier - **The intelligence is the exhaust of a serving engine measured on live deployments** — multi-page sessions +46% on enabled titles (10.3% → 15.1%) vs −16% on comparison titles (12.0% → 10.1%) — nine months, same network, same weeks - **The intent reads are checked by behavior, not clicks** — continuation past the fourth served article runs 70–82%, with a ~19-second per-article reading floor — matches are read, not tapped and abandoned - **The currency is engaged time, not pageviews** — ~30 seconds of reading per served article, ~50 seconds median added reading per engaged session - **The honest limit:** — what is measured is the engine's read of reader intent and the depth it produces. Whether the article you commission against a gap performs is your writing on our map — we do not claim a measured commissioning outcome The serving engine these signals come from, measured: [two titles grew multi-page sessions 46% while the comparison group fell 16%](/customers/equine-network-rollout/). **Introducing** ## Artificial Poets Platform One engine behind every solution on this site. It learns your archive and your readers, then acts inside your CMS, your templates and your ad stack. - It learns your archive: **Every story you have published, current again** — The engine understands each piece by what it is about, not when it ran or where it was filed. A feature from 2019 competes for the next slot on merit with one from this morning. - It reads the visit: **What a reader wants, without asking** — Interest builds from what someone actually does in the session. No login, no third-party cookies, nothing leaving your domain. Useful on the second pageview, not the tenth visit. - It chooses: **The right next read, not the popular one** — Someone comparing products and someone following a running story want different things. A most-read list gives both the same five links and serves neither. - It serves: **There before the reader leaves** — The feed, the recommendations, the search answer and the signup ask all run on the same engine, in your templates and your ad stack. Any slot that arrives with them is yours to sell. - It proves: **A lift you can defend, or we say so** — Every deployment runs beside titles that did not get it, plus a serving pause. That is how a result becomes a number you can take to a board instead of a vendor claim. ## FAQ ### We already pay for Chartbeat, Parse.ly and GA4 — what does this add? Those tools report the performance of what you published. Content gap analysis needs the half your analytics cannot see: demand with no page to land on — searched-not-found queries, intents the matcher can't fill, archive pieces readers would take but never encounter. And it isn't another dashboard to stop opening by week three: the output is a commissioning-cycle brief, not a screen. ### Where does the gap signal actually come from? From your own readers, not from keyword tooling. Demand comes from on-site search that returned nothing useful and from what readers reach for article to article; coverage comes from your vectorized library. If the signal were external search volume, this would be SEO tooling with a new name, and it would point you at fights rather than gaps. ### What does it give me on a Tuesday morning? A gap map you can take into a commissioning meeting, not a dashboard to check. Two of its four zones cost nothing new to act on: archive gold is inventory you already paid for, and overserved is work you can stop doing. It is designed to reduce workload before it adds any. ### Will metrics start dictating what the newsroom writes? No. It is a map, not a mandate — commissioning stays with editors. For a smaller team the largest line item is usually what to stop: the Overserved quadrant is effort already being spent on demand that isn't there. Fewer, better commissions is a workload decision editors make, not one a model makes for them. ### We publish eight stories a week. Is there enough signal at our size? Honestly, it depends on your traffic, and it is worth testing rather than assuming. Smaller titles get sparser demand signals, and the zones that stay reliable longest are the ones drawn from your own library rather than from reader volume. The baseline month will show you which side of that line you are on. ### Is this trained on other publishers' audiences? No. The interest graph is built from your library and your readers' behavior on your properties — first-party data, anonymous profiles, no PII, not pooled across customers. A niche audience's demand map is precisely what a generic model cannot have. ### How do we introduce this without a fight in the newsroom? By being clear about what it does: it reports what readers looked for and did not find, and it never writes, commissions or publishes anything. Nothing is automated into the news agenda. Editors keep the same pin, exclude and constrain controls that govern everything else the engine touches. ## Related - [Search That Understands the Question](https://preview.artificialpoets.com/use-cases/intent-search/) — "Readers search my site and leave empty-handed — can search understand what they're actually asking?" - [Two Titles Grew Multi-Page Sessions 46%. The Comparison Group Fell 16%.](https://preview.artificialpoets.com/customers/equine-network-rollout/) — Equine Network enabled the Platform on two titles and left the rest unchanged. Over nine months the enabled titles grew multi-page sessions 46%; across the comparison titles the same measure fell 16%. - [Internal Traffic Went From 38% to 41%. That’s the Whole Strategy.](https://preview.artificialpoets.com/blog/internal-traffic-strategy/) — While publishers fought over shrinking external channels, the largest single "referrer" in the industry quietly became the publisher's own site: internal traffic rose from 38% to 41% of total publisher traffic as search and social receded. Three points of share sounds incremental. It is not — it is the only channel that grew, and the only one you own outright. - [You Can’t Get the Traffic Back. You Can Get the Session Back.](https://preview.artificialpoets.com/resources/traffic-back/) — The economics of session depth, and the causal evidence behind it: +53% pageviews per user, 95% CI [+48%, +58%], with the modelling assumptions written down. ## See how this works on your titles Thirty minutes on your analytics. We tell you what share of your sessions stop at the first page, and what this would realistically move first for a setup like yours. You leave with the annotated read. No deck. [See it on my numbers](/request-a-demo/) How these numbers are made: [the measurement method](/solutions/measurement/). Figures from a multi-title publisher network measured continuously, August 2025 to May 2026. Last updated August 15, 2026. ## Questions this page answers ### What is content gap analysis for publishers? It is reading demand against coverage: what readers search for and do not find, what they reach for from every article, and which archive pieces would still be read if anything surfaced them. Those signals are logged as a by-product of serving and read back as a gap map. ### How does the gap map work? Demand comes from on-site search and the interest graph; coverage comes from the vectorized library. Each topic cluster lands in a zone. Two of the four cost nothing new to act on: archive gold is inventory you already paid for, and overserved is work you can stop doing. ### How much does editorial intelligence cost? There is no public price list; pricing follows network size and formats. The intelligence is the exhaust of a serving engine rather than a separate analytics product, so it arrives with the deployment instead of adding another subscription and another dashboard to check. ### Who is it for? Editors and commissioning leads deciding what to publish next with a smaller team than they had. It is built to reduce workload before it adds any: the first two zones it surfaces are things you can stop doing and things you already own. ### Does this mean an algorithm decides our coverage? No. It reports what readers looked for and did not find; what to do about that stays an editorial decision. Nothing is auto-published, nothing is auto-commissioned, and the same pin, exclude and constrain controls that govern serving apply to everything the engine touches. ### How do I get started? The signals accumulate from the moment indexing starts, so the four-week measurement-only baseline is already producing the first gap map before anything is served. Authorization, CMS access and infrastructure access are the requirements, and integration is carried out by our team.