Why ChatGPT Never Mentions Your Company: Porovnání verzí
(Založena nová stránka s textem „Test it rather than assuming. Load your key pages with JavaScript disabled and see what survives. If the product specifications, pricing, service areas and…“) |
m |
||
| Řádek 1: | Řádek 1: | ||
| − | + | Discontinued products deserve deliberate handling rather than deletion. Removing a page severs the connection between existing reviews and coverage and your catalogue, and it leaves stale third party listings pointing at nothing. Keeping the page, marking it clearly as discontinued and naming the replacement preserves the accumulated evidence and redirects the recommendation rather than losing it.<br><br>The Baseline Is Worth More the Earlier You Take It A baseline taken today lets you attribute change later. Without one, when something moves you will be reduced to guessing whether it was the assistants, a search update, a competitor's campaign, seasonality or your own site changes.<br><br>You asked it to recommend a supplier in your category. It named four companies, two of which you consider inferior to yours, and one you had never heard of. Your name did not come up, and it did not come up on the follow up question either.<br><br>There is almost always a specific, findable reason for this, and it is rarely that the model dislikes you. Here are the causes worth checking, roughly in the order that they tend to be responsible. [https://www.88pianists.com/ how to get recommended by AI assistants]<br><br>Making Yourself Easy to Write About Journalists and analysts write from what they can find quickly. A press page carrying your canonical name, founding details, leadership with verifiable profiles, plain descriptions of what you do and concrete figures they can quote removes the friction that produces vague coverage.<br><br>This is the whole argument in one sentence, and it is why the audit is worth running even if you intend to do nothing with the findings for six months. The measurement is cheap. Reconstructing a baseline you never took is impossible.<br><br>What to Do First Run five prompts describing a purchase your best customer would be making, from a signed out session, and see what gets named and cited. Then check whether your product data survives with scripts disabled, and whether your name and identifiers are consistent across every listing you can find.<br><br>Reviews Do Disproportionate Work For products more than for services, review content is the evidence base. Volume matters, recency matters more, and detail matters most, because a review that describes a specific use gives a model something to match against a specific question.<br><br>There is also a straightforward test that costs nothing and tends to end the debate internally. Ask an assistant the question your best customer would have asked before they found you, and read the answer out in the next management meeting. how to get recommended by AI assistants<br><br>Why the Direction Is Plausible Anyway Set the numbers aside and the mechanism is straightforward. Somebody arriving from an assistant has already had their question answered, has already seen a comparison, and has been given your name as a recommendation.<br><br>The Data Has to Exist as Text The most common failure is mechanical. Specifications live in an image of a table, sizing sits in a downloadable PDF, and the price appears only after a script runs or after a variant is selected.<br><br>This is why marketplace listings, review sites and roundups dominate product citations while brand product pages appear less often. It is also why a product page that states what it is worse at is unusually valuable, since it can be quoted as an impartial constraint rather than a claim.<br><br>Check your robots file, then check your server logs for the relevant agents and see what status codes they receive. A site that returns a challenge to every non-browser request is invisible to this entire channel, and nobody involved will have thought of it as a marketing decision.<br><br>It is also worth doing while your category is boring. An audit run during a period of stability produces a clean baseline. One run in the middle of a competitor's campaign or immediately after a site migration measures the disruption rather than the position, and you will not know which you have unless you took the earlier reading.<br><br>The Cheapest Fixes Have a Deadline That Already Passed Audits routinely surface mechanical problems that have been quietly costing visibility for months. Crawlers blocked in robots.txt. A bot management product returning challenges to legitimate retrieval agents. Key content rendering only after JavaScript executes. Specifications trapped in a PDF.<br><br>Product recommendations are a harder case than service recommendations, because the answer has to be specific enough to act on. A model naming a product is committing to a name, usually a price band and often a comparison, and it needs sources confident enough to support that.<br><br>One brief worth writing once and reusing is a factual sheet for anyone writing about you: canonical name, what you do in a sentence, who you serve, where you operate, when you were founded, who leads it, and three concrete figures you are happy to see quoted. Writers use what is easy to find, and supplying this removes the friction that otherwise produces a paragraph of adjectives.<br><br>Fragmented identity produces a specific symptom worth recognising: an assistant knows facts about you but attributes them vaguely, or confuses you with a similarly named business. The fix is dull consistency work across every place your name appears. | |
Verze z 12. 8. 2026, 18:16
Discontinued products deserve deliberate handling rather than deletion. Removing a page severs the connection between existing reviews and coverage and your catalogue, and it leaves stale third party listings pointing at nothing. Keeping the page, marking it clearly as discontinued and naming the replacement preserves the accumulated evidence and redirects the recommendation rather than losing it.
The Baseline Is Worth More the Earlier You Take It A baseline taken today lets you attribute change later. Without one, when something moves you will be reduced to guessing whether it was the assistants, a search update, a competitor's campaign, seasonality or your own site changes.
You asked it to recommend a supplier in your category. It named four companies, two of which you consider inferior to yours, and one you had never heard of. Your name did not come up, and it did not come up on the follow up question either.
There is almost always a specific, findable reason for this, and it is rarely that the model dislikes you. Here are the causes worth checking, roughly in the order that they tend to be responsible. how to get recommended by AI assistants
Making Yourself Easy to Write About Journalists and analysts write from what they can find quickly. A press page carrying your canonical name, founding details, leadership with verifiable profiles, plain descriptions of what you do and concrete figures they can quote removes the friction that produces vague coverage.
This is the whole argument in one sentence, and it is why the audit is worth running even if you intend to do nothing with the findings for six months. The measurement is cheap. Reconstructing a baseline you never took is impossible.
What to Do First Run five prompts describing a purchase your best customer would be making, from a signed out session, and see what gets named and cited. Then check whether your product data survives with scripts disabled, and whether your name and identifiers are consistent across every listing you can find.
Reviews Do Disproportionate Work For products more than for services, review content is the evidence base. Volume matters, recency matters more, and detail matters most, because a review that describes a specific use gives a model something to match against a specific question.
There is also a straightforward test that costs nothing and tends to end the debate internally. Ask an assistant the question your best customer would have asked before they found you, and read the answer out in the next management meeting. how to get recommended by AI assistants
Why the Direction Is Plausible Anyway Set the numbers aside and the mechanism is straightforward. Somebody arriving from an assistant has already had their question answered, has already seen a comparison, and has been given your name as a recommendation.
The Data Has to Exist as Text The most common failure is mechanical. Specifications live in an image of a table, sizing sits in a downloadable PDF, and the price appears only after a script runs or after a variant is selected.
This is why marketplace listings, review sites and roundups dominate product citations while brand product pages appear less often. It is also why a product page that states what it is worse at is unusually valuable, since it can be quoted as an impartial constraint rather than a claim.
Check your robots file, then check your server logs for the relevant agents and see what status codes they receive. A site that returns a challenge to every non-browser request is invisible to this entire channel, and nobody involved will have thought of it as a marketing decision.
It is also worth doing while your category is boring. An audit run during a period of stability produces a clean baseline. One run in the middle of a competitor's campaign or immediately after a site migration measures the disruption rather than the position, and you will not know which you have unless you took the earlier reading.
The Cheapest Fixes Have a Deadline That Already Passed Audits routinely surface mechanical problems that have been quietly costing visibility for months. Crawlers blocked in robots.txt. A bot management product returning challenges to legitimate retrieval agents. Key content rendering only after JavaScript executes. Specifications trapped in a PDF.
Product recommendations are a harder case than service recommendations, because the answer has to be specific enough to act on. A model naming a product is committing to a name, usually a price band and often a comparison, and it needs sources confident enough to support that.
One brief worth writing once and reusing is a factual sheet for anyone writing about you: canonical name, what you do in a sentence, who you serve, where you operate, when you were founded, who leads it, and three concrete figures you are happy to see quoted. Writers use what is easy to find, and supplying this removes the friction that otherwise produces a paragraph of adjectives.
Fragmented identity produces a specific symptom worth recognising: an assistant knows facts about you but attributes them vaguely, or confuses you with a similarly named business. The fix is dull consistency work across every place your name appears.