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Drafts an editor approves, with results shown.

AI Content Optimisation reads how your pages perform, finds topics your site has not covered and prepares briefs, headlines and descriptions for an editor to approve. Results come back to each piece. No draft goes live unread. Topics come from data, not habit.

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What it is

Content work scatters. Keywords live in a sheet and drafts sit in email threads. Ask which March post sent a single enquiry to the sales desk and nobody can answer. Topics get picked by instinct.

Here the keyword, the brief, the draft and the published address are kept together, and search reports are matched back to each piece. The editor still rewrites every draft. Only the guessing stops.

Where it goes wrong today

The problems this is meant to ease.

Topics chosen by habit

Nobody records what a post earned. The team repeats the subjects it enjoys writing, and the questions buyers actually type into search go unanswered for months because no list of them exists.

Two posts fighting for one phrase

Pages compete with each other. Writers on different weeks cover the same subject, neither page ranks well, and the marketer learns of it only when both slip together in a monthly report.

Old posts left to decay

Slow decline goes unseen. A page that once brought enquiries slides down the results, nobody notices, and a new post gets written when repairing the old one would have taken less effort.

Weak headlines and buried answers

Readers leave too early. A visitor lands, scrolls past three paragraphs of preamble and goes, while the call to action waits at the bottom of a long page that almost nobody reaches.

Facts that drift from the product

Old facts stay online. A blog quotes a withdrawn offer or an old specification, and somebody in sales spots it a month later, after customers have read it and asked about it.

Brand voice varies by writer

The site sounds like several firms. Freelancers, interns and the founder each write differently, and without one style guide and one reviewer the pages read like separate companies sharing a domain.

Inside the module

What AI content optimisation does.

A scorecard for every piece

Each page gets its own record. Visits, time on page, form fills and ad clicks are gathered against the published address, so a post is judged by enquiries and not by traffic.

Topics and gaps from search intent

Pick a keyword and a brief appears. It names what the searcher wants, the questions around it and the pages on your site that should link in, then lists subjects rivals cover that you skip.

Clearer structure and wording

Suggestions sit beside the original. Long pages are checked for reading level, buried answers and headings that say nothing, and the editor accepts or rejects each change, so the writer keeps the pen.

Headlines, descriptions and calls to action

Choices stay with the marketer. Several versions are drafted for each piece and cut to the character limits of search results and ad platforms, then a marketer picks one and edits it.

Refresh and internal linking list

Old posts get a second look. Pages that once ranked and have slipped are listed with the searches they lost, and with orphan pages that no other page links to.

Conversion checks on each page

Find where people stall. The page shows where visitors left, which button went unused and which form field stalled people, so the marketer can pick one small change to test.

Editorial review and fact check

Nothing unsupported slips through. Every draft is held against your style guide, your approved claims and your product facts, and anything the software cannot support is highlighted for a person. Approval carries a name and date.

Where it gets used

What this looks like in a working week.

A distributor of building supplies

Start from contractor questions. The marketing manager lists what contractors ask on the phone, each question becomes a brief built from search intent, and a technical editor checks every specification.

A dental clinic

Old posts get repaired. Posts on aligners and root canal care are ranked by the searches they lost, the practice manager refreshes the worst three, and the dentist signs off each claim.

An online clothing retailer

Two guides may compete. Category pages and buying guides are compared for overlap and the marketer merges two guides that chased the same search and links the survivor to the pages that sell.

A software company

Count sign-ups, not visits. Help articles and blog posts are scored by the sign-ups that followed a visit, and the content lead drops topics that draw readers but no leads.

A small agency with several clients

Rules differ client by client. The account manager keeps a style guide and approved claims per client, and sends a monthly page that sets what was published beside the enquiries each piece brought.

Who touches it

The people who open this every day.

Content marketer

Edits the brief and the draft. Adds real examples from customers, reads the whole page one last time before publishing, and puts the saved hours into pieces that need knowledge only a person has.

Marketing head

Plans from the evidence. Reviews which topics produced enquiries and builds next month’s calendar from that list, so the weekly meeting argues from numbers and not from whoever speaks loudest in the room.

Designer

Works from a full brief. Receives sizes, copy, the offer and the call to action in one request, and builds without chasing missing details, so fewer rounds of redo follow.

Agency account manager

One guide per client. Keeps a style guide and a list of approved claims for each client, and shows what was published for them each month, so nobody rebuilds reports by hand.

How it is set up

From first conversation to daily use.

Discovery
We map where content lives. We sit with the marketer and editor and list where keywords, drafts and published addresses live today, and who may approve a claim, and who presses publish.
Data readiness
Nothing is trusted until then. Search console and web analytics exports are connected, form fills are counted, each past post is matched to its address and gaps in tracking are repaired.
Trial on live pages
Start with one topic area. About twenty published pages and your real style guide feed the first briefs and drafts, and nothing is published during this stage, so a mistake costs reading time.
Staff review before launch
Staff mark what is wrong. The editor reads the briefs and drafts beside the originals, the product owner confirms the facts, and every correction is loaded back into the style guide.
Going live
The publish step stays human. Remaining topic areas are added in turn, the marketer brings the scorecards into the weekly meeting, and one named person on your team keeps the only publish button.
Reviewing afterwards
Read it back after a cycle. The team checks which briefs were used and which suggestions were rejected and why, then adjusts the rules and style guide, and reads each measure against the baseline.

Measuring it

How you would know it is working.

Record where you stand before it goes live, so the change is measured against your own figures.

Organic visits per page are taken from your web analytics for the months before go-live, and that figure is the baseline every later month is compared with.
Engagement means time on page and scroll depth for each piece. Your analytics figures for the same pages, taken before any wording changed, set the comparison.
Content conversions are form fills and enquiries traced back to a page, and the baseline is the count your CRM held before tracking was repaired.
Briefs that reach the editor complete are counted each month, and the baseline is how many briefs were complete in the quarter before the software was switched on.
Refreshed pages are tracked by the searches they regained, and the baseline is each page’s position in the last export taken before the rewrite.

Used responsibly

Where a person stays in charge.

A person approves every piece

Drafts stay marked as drafts. They keep that mark until a named editor signs them off, and the software cannot place copy in an ad account without the marketer’s choice.

Facts come from your own sources

Unsupported claims are flagged. Claims are checked against the product facts and approved statements you supply, and where a claim has no support on that list the draft marks it for review.

Limits of the suggestions

Scores are only estimates. Search intent, content gaps and readability scores come from the data available, so a new site with little traffic gives thin results and the page labels them thin. Treat them as prompts, not verdicts.

Rights and platform rules

Platform and country both change the rules. Ad copy limits, health or finance claims and image licences each vary, so your own lawyer decides what applies. No legal advice comes from the software.

How it fits

It is one part of a system, not an island.

A module earns its place by what it passes to the next one. These are the connections we set up most often.

Your website or content management system
Search console and web analytics exports
Ad accounts, for copy options and click data
CRM, so enquiries can be traced to a page
Shared drive for creative files

Already built in

Products that include it.

Digital Marketing Agency Management Software

Built for you

How we would put it in.

Common questions

Questions owners ask about AI content optimisation.

Will drafts sound like us?

Closer, but never finished. Your style guide, past articles and approved product facts go into the setup, and a human reader must approve each piece with the editor’s corrections shaping later drafts.

Do search engines penalise machine help?

They judge usefulness, not authorship. Thin or repeated pages do badly whoever writes them, which is why each draft needs real detail from your own team before it goes out to readers.

Which data must we supply?

Less than you might think. A website you can edit, web analytics with form fills tracked and search console access are enough for a first trial, and ad accounts add detail later.

Is it needed for two posts?

A sheet may be enough. A spreadsheet and a careful editor cover it, and this makes sense when several people write or many ad versions run and nobody can say which worked.

Can it publish to our site?

It stops at a draft page. Inside your content system it can create a draft, but the publish button stays with one named person, and some content systems need a small connector first.

How accurate are the gap suggestions?

Good for starting a list. Search data is noisy, so the editor should treat each suggestion as a question to answer with local knowledge, not as a finding that settles any argument.

What effort does setup take?

Mostly your time at first. Someone must write down the style guide and approved claims, someone must repair tracking, and then we connect the accounts and load the existing pages for the trial.

Who can see our data?

Only people you name. Viewing is limited to the people on your list, inside the account we set up. Storage rules for visitor data vary between countries, so your own adviser should decide where it lives.

Who needs it most

Businesses that ask for this.

Next to it

Modules that work with it.

Talk to us

Tell us how you handle AI content optimisation today.

A spreadsheet, a register or another system: say which, and we will tell you plainly what is worth changing.

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Start with your requirements

Seven short steps that tell us what you need. An engineer reads them before getting in touch.