Judge Keyword Viability Under AI Answers
Impressions can hold while clicks fall because the answer now sits above the results, so a plan built on volume keeps commissioning pages for queries that no longer send anyone anywhere. How much traffic is actually lost is genuinely disputed, and published figures vary widely by vertical and by who did the measuring, so the verdict has to come from your own data and a live check rather than from a headline statistic. The useful split is between queries a machine can finish and queries where the searcher still has to reach a page to act.
KATEGORIE
Keyword-Recherche
FORMAT
keyword-viability-under-ai-answers.md
PREIS
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WANN SIE DAZU GREIFEN
Use when deciding whether a query still deserves a page now that AI answers and feature blocks sit above the results.
Die Skill-Datei
keyword-viability-under-ai-answers.md
---
name: keyword-viability-under-ai-answers
description: Use when deciding whether a query still deserves a page now that AI answers and feature blocks sit above the results.
---
# Judge Keyword Viability Under AI Answers
Impressions can hold while clicks fall because the answer now sits above the results, so a plan built on volume keeps commissioning pages for queries that no longer send anyone anywhere. How much traffic is actually lost is genuinely disputed, and published figures vary widely by vertical and by who did the measuring, so the verdict has to come from your own data and a live check rather than from a headline statistic. The useful split is between queries a machine can finish and queries where the searcher still has to reach a page to act.
## Was Sie vorher brauchen
- a candidate query list with the page type each would need
- live SERPs checked logged out in the target country, on mobile as well as desktop
- your own Search Console click-through history for comparable queries where an AI answer already appears
## Methode
1. Check each candidate live and logged out and record three things: whether an AI answer appears, whether it cites sources, and how far the first organic result sits below it. Do this on mobile too, where the displacement is far larger.
2. Classify by answer completeness. A definition, a conversion, a date or a single fact can be finished in place; a decision that depends on price, availability, fit, personal circumstances or seeing the thing cannot.
3. For queries you already rank for, compare your click-through rate before and after the AI answer appeared on that query. Your own history is the only measurement that reflects your snippet, your vertical and your market.
4. Keep answerable queries only where being cited has value on its own, and write in the plan that the return is visibility rather than sessions, so nobody measures it as traffic six months later.
5. Prioritise queries the searcher has to complete on a site: pricing, availability, configuration, booking, and comparisons against constraints only they know. Those retain clicks because the answer cannot be finished in a paragraph.
6. Decide the measurement for each retained query before it is published - which number should move, and by when - because impressions and citations will both move without clicks following.
7. Re-check the affected queries quarterly. Feature rollout is uneven across countries and query types, and a term that was safe last quarter can lose its clicks with no ranking change at all.
## Was dabei herauskommt
A per-query verdict of keep, keep for citation only, or drop, with the SERP evidence and the date it was checked.
## Wo es schiefgeht
- Dropping a whole topic because one query in it shows an AI answer, when the commercial queries underneath are untouched.
- Using a published click-loss percentage instead of your own click-through history, when the spread across published studies is wider than the decision you are making.
- Assuming a citation brings traffic - citation frequency and click-through are separate things and need separate tracking.
---
Aus der QuQi-Skill-Bibliothek - https://www.quqi.io/de/skills/keyword-viability-under-ai-answers
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Was Sie vorher brauchen
-
a candidate query list with the page type each would need
-
live SERPs checked logged out in the target country, on mobile as well as desktop
-
your own Search Console click-through history for comparable queries where an AI answer already appears
Methode
-
01
Check each candidate live and logged out and record three things: whether an AI answer appears, whether it cites sources, and how far the first organic result sits below it. Do this on mobile too, where the displacement is far larger.
-
02
Classify by answer completeness. A definition, a conversion, a date or a single fact can be finished in place; a decision that depends on price, availability, fit, personal circumstances or seeing the thing cannot.
-
03
For queries you already rank for, compare your click-through rate before and after the AI answer appeared on that query. Your own history is the only measurement that reflects your snippet, your vertical and your market.
-
04
Keep answerable queries only where being cited has value on its own, and write in the plan that the return is visibility rather than sessions, so nobody measures it as traffic six months later.
-
05
Prioritise queries the searcher has to complete on a site: pricing, availability, configuration, booking, and comparisons against constraints only they know. Those retain clicks because the answer cannot be finished in a paragraph.
-
06
Decide the measurement for each retained query before it is published - which number should move, and by when - because impressions and citations will both move without clicks following.
-
07
Re-check the affected queries quarterly. Feature rollout is uneven across countries and query types, and a term that was safe last quarter can lose its clicks with no ranking change at all.
Was dabei herauskommt
A per-query verdict of keep, keep for citation only, or drop, with the SERP evidence and the date it was checked.
Wo es schiefgeht
-
Dropping a whole topic because one query in it shows an AI answer, when the commercial queries underneath are untouched.
-
Using a published click-loss percentage instead of your own click-through history, when the spread across published studies is wider than the decision you are making.
-
Assuming a citation brings traffic - citation frequency and click-through are separate things and need separate tracking.
Diese Skill in Ihrer eigenen KI nutzen
Die Datei ist einfaches Markdown, mit Name und Auslöser im Frontmatter. Wo ein Assistent Skills selbst laden kann, liest er genau dieses Frontmatter, um zu entscheiden, dass diese hier passt.
Claude Code
Speichern Sie sie als ~/.claude/skills/keyword-viability-under-ai-answers/SKILL.md, dann lädt Claude sie von selbst, sobald Ihre Arbeit zum Auslöser passt. Legen Sie sie stattdessen in .claude/skills im Projekt ab, wenn das ganze Team sie haben soll.
Claude
Laden Sie die Datei im Skills-Bereich Ihrer Einstellungen hoch. Danach greift sie in jedem Gespräch, in dem der Auslöser passt, ohne dass Sie daran denken müssen.
ChatGPT
Es gibt kein Skills-Format zum Installieren, fügen Sie den Dateiinhalt also stattdessen in die Anweisungen eines Projekts oder eines Custom GPT ein. Dann gilt er für jeden Chat in diesem Projekt und nicht nur für den einen.
Alles andere
Fügen Sie das Markdown vor Ihrer Frage in den Chat ein. Das funktioniert in jedem Assistenten, muss aber jedes Mal neu eingefügt werden.
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