Zhihe GrowthGEO tests often treat an official-site source marker as success. The more important question is whether the page supports the answer's facts. AI may cite the correct domain but apply family-level specifications to one model, call a partner brand a service client, or combine sources into a conclusion none supports. Citation rate alone cannot distinguish these risks.
Record Four Layers Separately
| Level | Evidence to Retain | Verification Question |
|---|---|---|
| Native Answer | Complete question and answer, platform, date, region, and mode | Were contextual conditions omitted? |
| Visible Sources | Screenshots of citation chips, cards, or source areas | Is the source actually present in this response? |
| Final URL | Actual URLs recovered by clicking or hovering, including final destinations after redirects | Does the link lead to the official site and the relevant page? |
| Factual support | Answer claim, original source statement, and applicable scope | Does the source entail the claim, rather than merely relate to it? |
A common recording error is marking no URL when only the source title is visible. Links may be hidden in citation chips, hover interactions, expanded cards, or bottom source lists; recover them individually. Conversely, an official-site card may lead only to the homepage rather than the product page supporting a specification. Check the final page and passage, not just the domain.
A Practical Source-Support Rubric
Mark every high-risk claim: Direct support (the source explicitly states the same fact under the same conditions), Partial support (the source supports only the product family or general mechanism, not the answer's details), Not supported (the source does not contain the fact), or Contradicted (the source explicitly conflicts with the claim). Split multi-source answers into individual claims and score each separately; many references do not establish support for everything. If no citation is visible, record no source separately. Similar wording does not establish a hidden citation.
For example, a page stating that one model runs for 4 hours under specified test conditions does not fully support an answer claiming that all the brand's equipment runs for 4 hours. Even a citation to that page warrants only partial support or no support. Similarly, a logo on the Partner Brands page does not support the claim that Zhihe Growth delivered GEO services for every listed brand. For high-risk certification, medical, safety, or financial claims, use two independent reviewers and retain disagreement records.
Zhihe Growth's Testing Criteria
Zhihe Growth's previous cross-platform retests have shown the need to collect source titles and clickable URLs separately. Citation and Accuracy Rate Definitions specify numerators and denominators. This page further distinguishes correctly used citations from miscitations. SuperPDR and ELEREIN named case studies report visible official-site citations within their respective staged question sets. Do not relabel those rates as all cited answers being accurate or as procurement recommendation rates.
Bing AI Performance provides aggregate cited pages and grounding queries, but its documentation explains that it does not show complete native conversations or exactly why a source was cited. Dashboard trends can identify cited topics; source support still requires sampling actual platform answers. Report visible citation rate, support-score distribution, and factual accuracy together for acceptance, not a synthetic authority score.
Handling Miscitations
Preserve the evidence first, then determine whether the cause is unclear conditions on the official page, conflicting older pages, an erroneous external directory, or model overreach. Correct body text, tables, Schema, and internal links where the site is at fault. Observe platform output beyond your control through repeated testing of the same questions. If published data are no longer valid, update the case or source page and record the revision date. See Correcting AI Factual Errors and Evidence Layers.