AI writing for your e-commerce blog — what actually works

Let us be direct: yes, AI can write your blog. No, it cannot do it in your place without supervision. Between those two statements lies a whole craft — and that craft is what separates the stores whose organic traffic climbs from those publishing filler nobody reads, not even Google.

Having watched hundreds of generated articles go by, here is an honest sort between what works and what shows.

What Google actually thinks about AI content

Let us kill the fantasy: Google does not penalise AI-generated content as such. Its official position, repeated since 2023, fits in one sentence — what counts is whether the content is useful, not how it was produced. The "Helpful Content" system punishes useless content, whether it was written by an underpaid human or by a language model.

In practice, what Google demotes without hesitation:

• interchangeable articles that could be published on any site without changing a word;
• texts that circle the subject without ever giving concrete information;
• mass production with no review — a hundred articles published the same day, all built on the same skeleton.

None of that is specific to AI. But AI makes those mistakes easy, and that is the trap.

What can be spotted a mile off

You have already read badly used AI content, even without knowing it. The signs do not lie: introductions that open with "In an ever-changing world", hollow transitions ("it is essential to note that"), lists of generalities valid for every product on earth, and above all — no figures, no examples, no opinion.

The real problem is not stylistic, it is informational. A language model used on its own knows neither your catalogue, nor your prices, nor your customers, nor the questions your support inbox receives. So it produces plausible, empty content. That is exactly the difference we set out in our comparison of raw AI, a copywriter or a specialised tool: the same model, connected to your data or not, does not produce remotely the same result.

What works: AI framed by your data

The e-commerce blogs that succeed with AI all follow the same recipe, in three ingredients.

1. An anchor in the catalogue

An article on "how to choose a cold air intake kit" written in a vacuum is generic. The same article citing three precise references from your catalogue, their prices, their fitting differences, and pointing to your product pages — that is content neither your competitor nor a content farm can publish. The catalogue anchor is your unfair advantage: your data is unique, your AI should use it.

2. A human brief

AI writes well when it is told what to write. The target keyword, the search intent, the tone, the length, the outline if needed: ten minutes of framing saves an hour of rewriting. That is the principle of the brief — the same one you would give a freelance writer, except delivery takes two minutes instead of two weeks.

3. A systematic review

Reviewing is not rewriting. On a properly framed article, the review takes five to ten minutes: check the factual claims, adjust a turn of phrase, add the anecdote or the tip only you know. That final layer — 5% of production time — is what takes an article from "decent" to "published under your name without blushing".

The economics, straight

A 1,200-word blog article from a decent web copywriter costs between £80 and £250. At four articles a month — the minimum rhythm for a blog to produce results, discussed in how many articles to publish per month — that is £4,000 to £12,000 a year. Most independent stores do not have that budget, and that is the real reason their blog is dead: not a shortage of ideas, the cost of production.

Framed AI changes the equation: the marginal cost of an article tends towards zero, and your investment moves to where it has value — choosing topics and reviewing. You are not replacing a writer; you are giving yourself a publishing volume you would never otherwise have funded.

The method, step by step

If you are starting from zero, here is the shortest path:

1. Inventory customer questions. Support emails, questions at trade shows, your store's internal searches: every recurring question is an article.
2. Attach a keyword to each topic. One article, one target query. Our guide to finding your store's keywords details the method, starting from your own catalogue.
3. Brief, generate, review. Tone, length, products to link. Generate, then spend your ten minutes reviewing.
4. Publish at a constant rhythm. Two articles a month sustained beat eight articles one month and nothing after.
5. Link. Every article should point to your product pages and to other articles — that is what turns an isolated post into an SEO asset, as our article on the blog as a search lever explains.

Our position, since one should have one

We built Publium precisely on this conviction: AI alone produces filler, AI plugged into a catalogue and reviewed by a merchant produces content that ranks. That is why the app does not "generate text" — it reads your products, your categories and your pages, proposes keywords drawn from your own catalogue, writes with your data, and leaves you the last word before publishing.

The blog stays your voice. The AI merely holds the pen — and it writes much faster than you do. Want to see that on your store? Ask for a demo: within an hour you will know whether the recipe works for your catalogue.