Most business websites are not short of ideas. They are short of hours.<\/p>\n
A product catalogue with four thousand items needs four thousand descriptions. A services company knows it should be publishing regularly and does not. A site launch stalls because nobody has written the About page.<\/p>\n
AI solves the volume problem.<\/strong> It does not solve the judgement problem, and website content is public \u2014 which raises the cost of getting it wrong.<\/p>\n Four things, in order of how safely you can adopt them.<\/p>\n The clearest win. From product attributes, at scale, in a consistent tone.<\/p>\n Give it the real attributes<\/strong> from your product records rather than letting it fill gaps. Most invented specifications come from missing information.<\/p>\n Check every specification.<\/strong> Dimensions, materials, compatibility, certifications. It will produce plausible ones.<\/p>\n A first draft to react to, which for most people is faster than starting from nothing.<\/p>\n The catch:<\/strong> generated articles are competent and conventional. If everyone in your industry publishes the same way, everyone reads the same.<\/p>\n What makes an article yours<\/strong> is the specific example, the real customer situation, the opinion. That is what you add.<\/p>\n Service pages, About pages, FAQ answers. Useful for a first pass.<\/p>\n Read carefully.<\/strong> These are the pages people judge you on.<\/p>\n Genuinely tedious, needed on every page, and low risk.<\/p>\n A good use.<\/strong> Nobody enjoys writing four hundred meta descriptions and they matter for search.<\/p>\n FIGURE 1: FOUR USES, SAFEST FIRST<\/p>\n Meta descriptions and titles<\/p>\n Product descriptions<\/p>\n Blog drafts<\/p>\n Page copy<\/p>\n A real concern, and the answer is more nuanced than either extreme.<\/p>\n Search engines do not penalise AI-generated content for being AI-generated.<\/strong> They penalise content that is unhelpful, thin or duplicated.<\/p>\n What that means practically:<\/strong><\/p>\n Original and useful is fine<\/strong>, regardless of how it was produced.<\/p>\n Generic filler is not<\/strong>, regardless of how it was produced. And AI makes generic filler very easy to produce in bulk.<\/p>\n Duplicated content is the real risk.<\/strong> If your generated descriptions closely resemble everyone else’s generated descriptions of the same products, none of them rank.<\/p>\n The test:<\/strong> does this page contain something a reader could not get from ten other pages? If not, publishing it does not help you.<\/p>\n Four things, and the first two matter most.<\/p>\n Real product attributes, real specifications, real details from your records. The gaps you leave are exactly where it invents things.<\/p>\n Three descriptions you like produces far better output than a paragraph describing what you want. This is the single highest-return technique available.<\/p>\n A real customer situation. A specific number from your own experience. An opinion. This is what makes the page worth existing.<\/p>\n The grammar will be fine. The question is whether the claims are correct, and that needs somebody who knows the products.<\/p>\n FIGURE 2: CONTENT THAT HELPS AND CONTENT THAT DOES NOT<\/p>\n Worth publishing<\/p>\n Not worth publishing<\/p>\n Publishing at volume without review.<\/strong> The pattern: four thousand descriptions generated, spot-checked at first, then trusted. One invented certification, across the whole catalogue.<\/p>\n Filling a content schedule.<\/strong> Twenty thin articles because somebody decided on weekly publishing. They do not rank and they dilute the pages that would have.<\/p>\n Copying competitor structure.<\/strong> Asking it to write about a topic produces something resembling everything already published on it.<\/p>\n Losing your voice.<\/strong> If your differentiation is how you talk to customers, generated text flattens it. Notice if your site starts sounding like everyone else’s.<\/p>\n No fact list.<\/strong> Decide what it must never claim \u2014 certifications, guarantees, compatibility \u2014 and check against that list.<\/p>\n Predictable, and worth planning against.<\/p>\n Week one, everything is read carefully. Month three, output has been consistently good and reading becomes skimming. Then one error publishes at scale.<\/p>\n Two safeguards:<\/strong><\/p>\n Spot-check a fixed percentage<\/strong>, deliberately, permanently.<\/p>\n Never remove review from anything published in volume.<\/strong> The volume that makes generation worthwhile is the same volume that makes one error expensive.<\/p>\n Six steps.<\/p>\n 1. Start with the facts.<\/strong> Pull real attributes from your product records. Do not let it guess.<\/p>\n 2. Give it three examples<\/strong> of what good looks like for you.<\/p>\n 3. Generate a batch of ten<\/strong>, not four hundred.<\/p>\n 4. Review those ten properly.<\/strong> Learn where it gets things wrong \u2014 usually specifications and claims.<\/p>\n 5. Adjust the prompt<\/strong> based on what you found.<\/p>\n 6. Then scale<\/strong>, with a permanent spot-check.<\/p>\n Step 3 is the one people skip.<\/strong> Generating everything at once means you discover the systematic error after it is everywhere.<\/p>\n FIGURE 3: HOW TO SCALE SAFELY<\/p>\n Supply real facts<\/p>\n Generate ten<\/p>\n Review properly<\/p>\n Adjust and scale<\/p>\n If your site runs on the same database as your products, generated descriptions can use the actual attributes<\/strong> \u2014 dimensions, materials, variants, real availability.<\/p>\n Less is invented, because less is missing. That reduces the error rate meaningfully.<\/p>\n It does not remove the need to read the output. It does mean there is less wrong to find.<\/p>\n Legal pages.<\/strong> Terms, privacy policies, disclaimers. These need a professional.<\/p>\n Anything with contractual weight.<\/strong> Warranty terms, service commitments, guarantees.<\/p>\n Case studies with invented details.<\/strong> If you are describing a real customer, use real facts and get their permission.<\/p>\n Anything you cannot verify.<\/strong> If nobody in your company can confirm a claim is true, do not publish it.<\/p>\n AI solves the volume<\/strong> problem in website content, and it does that well.<\/p>\n It does not decide what is worth publishing, and it will produce confident specifications it has no source for.<\/p>\n Give it your real data. Give it examples. Add what only you have. Review for truth.<\/strong><\/p>\n And generate ten before you generate four hundred \u2014 that one habit prevents most of the expensive mistakes.<\/p>\n A catalogue of products with no descriptions?<\/p>\n Get in touch. We will set it up using your real product data and a review process that catches the errors before they publish at scale.<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":" Where the volume problem is Most business websites are not short of ideas. They are short of hours. A product catalogue with four thousand items needs four thousand descriptions. A services company knows it should be publishing regularly and does not. A site launch stalls because nobody has written the About page. AI solves the […]<\/p>\n","protected":false},"author":3,"featured_media":9172,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[26],"tags":[],"class_list":["post-9171","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai"],"yoast_head":"\nWhat it does well<\/h2>\n
Product descriptions<\/h3>\n
Blog posts and articles<\/h3>\n
Page copy<\/h3>\n
Meta descriptions and titles<\/h3>\n
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The search engine question<\/h2>\n
What makes generated content good enough<\/h2>\n
Give it your facts<\/h3>\n
Give it examples<\/h3>\n
Add what only you have<\/h3>\n
Review for truth, not style<\/h3>\n
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The mistakes that cost most<\/h2>\n
The review habit that decays<\/h2>\n
A workable process<\/h2>\n
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Where Odoo helps<\/h2>\n
What not to generate<\/h2>\n
The short version<\/h2>\n