Zhihe GrowthAn error in an AI answer does not necessarily mean the official website is wrong. The answer may draw on an old cache, a distributor's account, a company with the same name, another model, or an incorrect synthesis of several accurate sources. Corrections should start with the evidence chain, not an immediate title rewrite or keyword stuffing.
Classify the Error First
| Type | Typical Symptom | First Check |
|---|---|---|
| Entity identity | Confusing the business with a same-name company or partner | Legal entity, official website,sameAs |
| Product facts | Mixing of models, packaging, power or units | Product pages, manual versions, regions |
| Applicable conditions | Turning suitability for a scenario into a guarantee of effectiveness | Limitations, test conditions |
| Currency | Old prices, old qualifications, old case results | Effective date and older pages |
| Source mismatch | The displayed link does not support the answer's conclusion | Final URL after clicking and the supporting passage |
For every test, retain the original question, platform, time, mode, complete answer, source-card title, and final URL obtained by clicking or hovering. Mark whether the link actually supports the statement. A source card showing only a title must not be recorded as no citation; a URL alone does not prove the citation is accurate. Zhihe Growth's AI Measurement Method counts brand mentions, official-site URL citations, and factual accuracy separately, so an incorrect brand mention is not treated as success.
Trace the Answer Back to the Fact Version
Check whether the cited URL is on the official website, redirects elsewhere, declares a newer canonical URL, or is actually an old directory. If official-site facts conflict, return to the SSOT Master Table to verify approved values and correct body text, tables, FAQs, Schema, downloads, and internal links. If third-party information is wrong, contact its owner and publish a verifiable official version on the website. If the cited source does not support the erroneous conclusion, classify it as a generation or attribution error; do not alter a correct page merely to accommodate it.
For multiple similar URLs, Google's canonical URL troubleshooting guidance recommends checking the canonical URL actually selected by the platform, then investigating conflicting content and signals. This helps explain page selection in Google Search; it does not establish that other AI platforms use the same canonicalization logic.
For example, answers about automotive tool models must distinguish an exact model's packing list from a product family's common configurations. The latter must not be presented as the former's official list. Likewise, recommendations for cleaning equipment must not turn nominal specifications into guaranteed results at a particular site. The public case studies for SuperPDR and ELEREIN show only approved interim results; they do not replace first-party product information on each client's official website.
Retesting After Corrections
Record each changed URL and field, old and new values, effective date, and responsible owner. Confirm status 200, visible content, and consistency between the canonical URL and sitemap, then allow time for recrawling. Repeat tests with the same questions, comparable time windows, and the same mode. Track whether errors persist, whether the official site is cited, whether the cited URL matches the facts, and whether other sources replace it. Retain unresolved samples. Platform answers fluctuate, so one correct answer does not establish a permanent fix.
Zhihe Growth can provide diagnosis, page corrections, and retest reports, but cannot instantly update a platform model's internal knowledge. For high-risk safety, legal, or medical content, prioritize corrections through authoritative first-party channels and consider the platform's feedback mechanisms. The site's Editorial policy provides a route for content corrections. Access and crawling issues also require technical access checks.
Criteria for Judging a Correction Successful
First establish whether the error is reproducible by testing the same question several times in the same mode, recording errors and sources each time. After publishing the correction, test the original question and two reasonable variants. If the answer is still wrong but cites the correct official-site version, classify it as a platform synthesis or stale-cache issue and continue observing rather than rewriting the page indefinitely. If sources still point to outdated URLs, check redirects, canonical tags, sitemaps, and third-party republications. If errors occur only in one language or region, check that market's product facts and localized version.
Report three separate milestones: the factual page was corrected, the platform revisited it, and answer errors decreased. These may be days or more apart, and regressions are possible. Preserve original evidence and the next review date for unresolved questions rather than deleting failed results. This approach turns a one-off copy edit into a bounded correction process: clients can see which steps are complete and which depend on platform retrieval or third-party corrections.