From keyword cleaning to topic trees, briefs and fact-checked AI articles — the SEO content production line that publishes directly to your Shopify store.
Shopify Blog & Content Planning turns keyword research into a production line built for Shopify stores: clean and classify keywords, map them onto a multi-dimensional content tree, generate briefs that differentiate siblings, then write articles grounded in live-fetched facts instead of model memory. Every article is self-scored across ten dimensions and fact-checked, then published to your store as a draft with FAQ metafield — handle locked to the slug so URLs stay stable.
Batch import from keyword tools, brand-term filtering, and rule+AI classification into ToC / ToB / regional intents.
Keywords, articles and product knowledge unified across eight dimensions — attribute, device, scenario, region and more.
A topic tree of thousands of nodes that plans internal linking and content boundaries before a single word is written.
Briefs detect overlap with existing pages, anchor keywords, and cover pillar gaps — no two articles compete for the same intent.
Live web research grounds every article in current facts — numbers must trace back to verified sources, so AI doesn't invent statistics.
Accuracy, E-E-A-T, usefulness, uniqueness, internal links, keyword coverage and more — low scores lock the article from publishing.
Automatic FAQ JSON-LD generation kept in sync with the article body for rich results.
Tree-based and batch-based interlinking plus related-posts blocks — link equity flows where it's planned.
Draft → cover image → article body → FAQ metafield, with handle locked to the slug so URLs stay stable.
The pipeline supports multiple languages end-to-end for stores selling across markets.
A full pipeline from keyword cleaning to topic trees, briefs, generation and publishing — dozens of articles per week from one operator.
Research-first: articles are grounded in live-fetched facts with mechanical number tracing — no hallucinated statistics or citations.
A complete planning system — facets, content tree, briefs, sibling dedup and pillar-gap coverage — so content compounds instead of colliding.
Ten-dimension self-scoring plus fact-checking; articles with low scores or factual errors are locked from publishing.
FAQ JSON-LD, internal links and related-posts are generated automatically as part of the article, not bolted on later.
AI articles kept errors — one had 2 critical issues after 4 patch rounds. Whitelist sources and traceable numbers make fact-checking converge.
Read article →We ran the full fact-check pipeline on every article at about $0.05 each. A rule-based YMYL classifier cut per-article cost to roughly $0.01 — a 5x saving — without touching the checks that actually matter.
Read article →AI writers hallucinate numbers and citations — a fatal flaw for SEO. Research-first writing plus mechanical number verification: how to keep AI content grounded in truth.
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