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Striking Distance Prioritisation

Most keyword plans start from scratch and ignore the demand a site has already proven it is relevant for. Chasing brand new terms wastes months because ranking from nothing needs links and time. Terms where you already sit in positions eight to twenty move with on-page work alone, because Google has already decided you belong in the consideration set.

CATEGORY
Keyword research
FORMAT
striking-distance-prioritisation.md
STEPS
6
PRICE
Free - no account
WHEN TO REACH FOR THIS

Use when you need traffic in weeks rather than months and already have a site with Search Console history.

The skill file

striking-distance-prioritisation.md 
---
name: striking-distance-prioritisation
description: Use when you need traffic in weeks rather than months and already have a site with Search Console history.
---

# Striking Distance Prioritisation

Most keyword plans start from scratch and ignore the demand a site has already proven it is relevant for. Chasing brand new terms wastes months because ranking from nothing needs links and time. Terms where you already sit in positions eight to twenty move with on-page work alone, because Google has already decided you belong in the consideration set.

## What you need first

- Search Console query export for the last 3 to 6 months
- ability to edit titles and on-page content
- a way to see which URL currently ranks for each query

## Method

1. Export queries with 90 days of data, filtered to impressions above a floor that suits your site - roughly 50 impressions in the window for a small site.
2. Filter to average position between 8 and 20. Below 8 you are already harvesting; above roughly 25 the gap is usually authority, not on-page.
3. Sort by impressions descending, not by position. A term at position 18 with 4,000 impressions is worth more than a term at position 9 with 60.
4. For each candidate, confirm which URL ranks. If two URLs alternate across the period, you have a cannibalisation problem and must fix that before any content edit.
5. Check the query appears in the ranking page's title and first 100 words. Missing title inclusion is the single most common cause of stalling around position 12.
6. Ship changes in batches of ten to fifteen URLs and re-pull the same report at 28 days to measure position change rather than clicks, which are too noisy at low volume.

## What this produces

A ranked worklist of existing URLs with the specific query each should target and the on-page change required.

## Where this goes wrong

- Using average position across a period where the page was re-indexed, which averages two different realities into a meaningless number.
- Adding new paragraphs when the actual fix was the title tag, so you cannot tell what worked.
- Including branded queries in the filter, which sit at position 8 to 20 only for irrelevant long-tail brand variants.

---

From the QuQi skill library - https://www.quqi.io/skills/striking-distance-prioritisation
Free to download · no account, no email

What you need first

  • Search Console query export for the last 3 to 6 months
  • ability to edit titles and on-page content
  • a way to see which URL currently ranks for each query

Method

  1. 01 Export queries with 90 days of data, filtered to impressions above a floor that suits your site - roughly 50 impressions in the window for a small site.
  2. 02 Filter to average position between 8 and 20. Below 8 you are already harvesting; above roughly 25 the gap is usually authority, not on-page.
  3. 03 Sort by impressions descending, not by position. A term at position 18 with 4,000 impressions is worth more than a term at position 9 with 60.
  4. 04 For each candidate, confirm which URL ranks. If two URLs alternate across the period, you have a cannibalisation problem and must fix that before any content edit.
  5. 05 Check the query appears in the ranking page's title and first 100 words. Missing title inclusion is the single most common cause of stalling around position 12.
  6. 06 Ship changes in batches of ten to fifteen URLs and re-pull the same report at 28 days to measure position change rather than clicks, which are too noisy at low volume.

What this produces

A ranked worklist of existing URLs with the specific query each should target and the on-page change required.

Where this goes wrong

  • Using average position across a period where the page was re-indexed, which averages two different realities into a meaningless number.
  • Adding new paragraphs when the actual fix was the title tag, so you cannot tell what worked.
  • Including branded queries in the filter, which sit at position 8 to 20 only for irrelevant long-tail brand variants.

Use this skill in your own AI

The download is a plain markdown file with the name and trigger in its frontmatter. Where an assistant supports skills it can load itself, that frontmatter is what it reads to decide this one applies.

Claude Code Save it as ~/.claude/skills/striking-distance-prioritisation/SKILL.md and Claude loads it on its own when what you are doing matches the trigger line. Put it in .claude/skills inside a project instead if the whole team should have it.
Claude Upload the file in the skills section of your settings. Once it is there it applies itself in any conversation where the trigger fits, so you do not have to remember it exists.
ChatGPT There is no skills format to install into, so paste the file contents into a Project instruction or a Custom GPT instead. It then applies to every chat in that project rather than only the one you paste it into.
Anything else Paste the markdown into the chat before your question. It works in any assistant, it just has to be pasted again each time.

Questions about this skill

When is this better than planning new keywords from scratch?

When the site already has Search Console history and you need movement in weeks rather than quarters. Brand new terms need links and time before anything happens. Positions eight to twenty mean Google has already put you in the consideration set, so titles and on-page work can move them alone. On a site with no impressions above the noise floor there is nothing here to work with.

What do I need in hand before starting?

Ninety days of query data, the URL that currently ranks for each query, and the ability to edit titles and copy yourself. Without the per-URL view you cannot see two URLs alternating across the period, so you edit one page while Google keeps serving the other. Without edit access the list becomes a request queue and the twenty-eight day re-pull that proves anything never happens.

What do I end up with, and which part gets used?

A ranked worklist of existing URLs, each with the query it should target and the specific on-page change. Sorting is by impressions rather than position, so position eighteen with four thousand impressions outranks position nine with sixty. The change column is what gets used, and if it says anything vaguer than a title rewrite or a phrase missing from the first hundred words, the row is not ready.

What is the mistake that ruins this, and what does it cost?

Changing several things on the same URL at once. New paragraphs shipped alongside a title rewrite mean the re-pull cannot tell you which one moved, so you learn nothing that transfers to the next batch and keep paying for the expensive fix. The cheaper mistake is leaving branded queries in the filter, where odd long-tail brand variants sit at position twelve and pad the list.

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