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Local pack ranking factors that actually matter

Map pack ranking is driven by a short list of inputs, and proximity dominates several of them in ways no amount of content will change. This skill separates what you can influence from what you cannot, and stops spend on the latter.

CATEGORY
Local SEO
FORMAT
local-pack-ranking-factors.md
STEPS
6
PRICE
Free - no account
WHEN TO REACH FOR THIS

Use when local visibility has plateaued and effort is being spread evenly across tactics instead of concentrated on the few inputs that move map pack position.

The skill file

local-pack-ranking-factors.md 
---
name: local-pack-ranking-factors
description: Use when local visibility has plateaued and effort is being spread evenly across tactics instead of concentrated on the few inputs that move map pack position.
---

# Local pack ranking factors that actually matter

Map pack ranking is driven by a short list of inputs, and proximity dominates several of them in ways no amount of content will change. This skill separates what you can influence from what you cannot, and stops spend on the latter.

## What you need first

- Grid-based rank tracking across the service area
- The profile configuration and category set
- Review velocity and count versus competitors
- The linked website and its local relevance

## Method

1. Run a geo grid rather than a single-point check, and read the shape of the result: a tight ring around the pin means you are proximity-bound and only entity strength expands it.
2. Confirm the primary category first, because category eligibility gates everything downstream and is the single highest-leverage change.
3. Assess the linked website page, since the destination page relevance and its authority feed the profile - pointing every profile at the homepage wastes this.
4. Weigh review signals by velocity and recency rather than lifetime count, and check whether review text contains the service terms you are targeting.
5. Treat citation quantity as a hygiene floor, not a lever: once the major aggregators and category directories are correct, additional citations return almost nothing.
6. Ignore engagement metrics you cannot verify, and re-run the grid after each single change so you can attribute movement to one input.

## What this produces

A ranked list of the inputs affecting this profile, with the proximity-bound portion of the service area identified and excluded from effort.

## Where this goes wrong

- Buying more citations after the top sources are already correct, which is the most commonly sold and least effective local tactic
- Changing several inputs at once so no movement can be attributed
- Chasing rankings in areas the grid shows are proximity-locked to a competitor with a closer premises

---

From the QuQi skill library - https://www.quqi.io/skills/local-pack-ranking-factors
Free to download · no account, no email

What you need first

  • Grid-based rank tracking across the service area
  • The profile configuration and category set
  • Review velocity and count versus competitors
  • The linked website and its local relevance

Method

  1. 01 Run a geo grid rather than a single-point check, and read the shape of the result: a tight ring around the pin means you are proximity-bound and only entity strength expands it.
  2. 02 Confirm the primary category first, because category eligibility gates everything downstream and is the single highest-leverage change.
  3. 03 Assess the linked website page, since the destination page relevance and its authority feed the profile - pointing every profile at the homepage wastes this.
  4. 04 Weigh review signals by velocity and recency rather than lifetime count, and check whether review text contains the service terms you are targeting.
  5. 05 Treat citation quantity as a hygiene floor, not a lever: once the major aggregators and category directories are correct, additional citations return almost nothing.
  6. 06 Ignore engagement metrics you cannot verify, and re-run the grid after each single change so you can attribute movement to one input.

What this produces

A ranked list of the inputs affecting this profile, with the proximity-bound portion of the service area identified and excluded from effort.

Where this goes wrong

  • Buying more citations after the top sources are already correct, which is the most commonly sold and least effective local tactic
  • Changing several inputs at once so no movement can be attributed
  • Chasing rankings in areas the grid shows are proximity-locked to a competitor with a closer premises

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/local-pack-ranking-factors/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 the right exercise rather than working through a local checklist?

When visibility has plateaued and effort is spread evenly across tactics. A checklist treats every item as equally weighted, and in the pack they are not: category eligibility and proximity dominate, while citations beyond the major sources return close to nothing. This separates the inputs you can move from the ones no budget will change.

What do I need in hand before starting?

Grid-based rank tracking across the service area, the profile configuration and category set, review velocity and count against the pack competitors, and the page each profile links to. The grid is not optional here. A single-point check from the office cannot show which parts of the area are proximity-bound and therefore not worth funding.

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

A ranked list of the inputs affecting this profile, with the proximity-locked part of the service area marked and excluded from effort. That exclusion is what changes spend. It turns a vague instruction to rank better across the region into a smaller area where entity strength can plausibly move you, and stops reporting failure against ground you were never going to hold.

What ruins this most often?

Changing several inputs at once, so nothing can be attributed and the next decision is a guess. Re-run the grid after each single change. The commercial version of the mistake is buying more citations once the aggregators and category directories are already correct, which is the most heavily sold local service and the one with least left to give.

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