Ecommerce.Amazon Keyword Share Of Voice logo

Ecommerce.Amazon Keyword Share Of Voice

Organization
nexscope-ai
ecommerce.amazon-keyword-share-of-voice

Nexscope keyword Share of Voice analysis, returning brand visibility share across the first 3 pages of Amazon search results (organic/ad/combined), 30-day exact search volume, median PPC bid, and TOP3 ASIN click and conversion data, covering 10 marketplaces. Trigger when the user mentions brand market share, brand voice share, search result brand distribution, Share of Voice, SOV analysis, brand competitive landscape, ad slot share, organic ranking brand share, PPC bid analysis, brand monopoly analysis, keyword share of voice, brand visibility, organic vs sponsored share, brand dominance, PPC bid analysis, search result brand distribution, competitive landscape, weighted SOV, top ASIN clicks conversions. Even if the user does not explicitly mention "Share of Voice" or "SOV", if their need involves analyzing brand market share or competitive landscape in Amazon keyword search results, this skill should also be triggered.

Overview

Publishernexscope-ai
Repositorynexscope-ecommerce-skills
Skill nameecommerce.amazon-keyword-share-of-voice
Stars
104
Forks
14
Bundled files
3
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by nexscope-ai on GitHub. Read the source before you install it.

Installation

Install the Ecommerce.Amazon Keyword Share Of Voice AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/nexscope-ai/nexscope-ecommerce-skills/tree/main/ecommerce-amazon-keyword-share-of-voice
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/nexscope-ai/nexscope-ecommerce-skills.git /tmp/nexscope-ecommerce-skills
mkdir -p .claude/skills
cp -r /tmp/nexscope-ecommerce-skills/ecommerce-amazon-keyword-share-of-voice .claude/skills/ecommerce.amazon-keyword-share-of-voice
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ecommerce.Amazon Keyword Share Of Voice in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ecommerce.Amazon Keyword Share Of Voice on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ecommerce.Amazon Keyword Share Of Voice is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Nexscope -- Keyword Share of Voice

This skill queries Share of Voice (SOV) data for Amazon keywords via the Nexscope data source, returning brand visibility distribution across the first 3 pages of search results, along with search volume, PPC bid estimates, and top ASIN click/conversion metrics across 10 Amazon marketplaces.

Core Concepts

Share of Voice measures how much of the search results real estate a brand occupies for a given keyword. Nexscope analyzes the first 3 pages of Amazon search results and calculates each brand's presence in three dimensions:

  • Organic SOV: Brand visibility from organic (non-sponsored) search result positions
  • Sponsored SOV: Brand visibility from sponsored/advertising placements
  • Combined SOV: Overall brand visibility merging both organic and sponsored results

Each dimension has two calculation methods:

  • Basic SOV: Simple product count ratio -- number of a brand's products / total products on the 3 pages
  • Weighted SOV: Position-adjusted ratio that gives higher weight to top positions and factors like Amazon's Choice badge; this is the more meaningful metric for competitive analysis

The tool also returns:

  • 30-day exact search volume: Total estimated searches in the past 30 days
  • PPC bid median: Median suggested bid for this keyword, useful for advertising cost estimation
  • TOP3 ASIN click & conversion data: The top 3 ASINs by clicks, with click count, conversion count, and conversion rate

Data Fields

brands (Brand SOV Breakdown)

FieldAPI NameDescriptionExample
Brand NamebrandBrand name as shown in search resultsAnker
Organic ProductsorganicProductsNumber of organic listings in the first 3 pages5
Sponsored ProductssponsoredProductsNumber of sponsored listings3
Combined ProductscombinedProductsTotal listings (organic + sponsored)8
Organic Basic SOVorganicBasicSovOrganic simple ratio (0-1)0.083
Organic Weighted SOVorganicWeightedSovOrganic position-weighted ratio (0-1)0.112
Sponsored Basic SOVsponsoredBasicSovSponsored simple ratio (0-1)0.15
Sponsored Weighted SOVsponsoredWeightedSovSponsored position-weighted ratio (0-1)0.18
Combined Basic SOVcombinedBasicSovCombined simple ratio (0-1)0.133
Combined Weighted SOVcombinedWeightedSovCombined position-weighted ratio (0-1)0.152
Organic Avg PositionorganicAveragePositionAverage ranking position in organic results12.4
Sponsored Avg PositionsponsoredAveragePositionAverage ranking position in sponsored results5.0
Combined Avg PositioncombinedAveragePositionAverage ranking position across all results9.5
Organic Avg PriceorganicAveragePriceAverage price of organic products29.99
Sponsored Avg PricesponsoredAveragePriceAverage price of sponsored products25.99
Combined Avg PricecombinedAveragePriceAverage price of all products28.49

topAsins (TOP 3 ASIN Click & Conversion)

FieldAPI NameDescriptionExample
ASINasinAmazon Standard Identification NumberB09V3KXJPB
Product NamenameProduct titleAnker Portable Charger...
BrandbrandProduct brandAnker
ClicksclicksClick count (30-day window)15200
ConversionsconversionsConversion count (30-day window)4560
Conversion RateconversionRateConversion rate (0-1)0.30

Top-Level Summary Fields

FieldAPI NameDescriptionExample
IDidResource identifier--
TypetypeFixed valueshare_of_voice
30-Day Search Volumeestimated30DaySearchVolumeExact search volume over 30 days125000
PPC Bid MedianexactSuggestedBidMedianMedian suggested PPC bid (USD)1.25
Product CountproductCountTotal products in the first 3 pages60
Updated AtupdatedAtData freshness timestamp2026-04-10T00:00:00
Top ASINs Start DatetopAsinsModelStartDateClick/conversion data window start2026-03-11
Top ASINs End DatetopAsinsModelEndDateClick/conversion data window end2026-04-10
Cost TokencostTokenTokens consumed by this call1

Supported Marketplaces

us (United States), uk (United Kingdom), de (Germany), in (India), ca (Canada), fr (France), it (Italy), es (Spain), mx (Mexico), jp (Japan)

Default marketplace is us. Use us when the user doesn't specify a marketplace.

How to Invoke

  • API Endpoint: POST /tool-jungle-scout/keywords/share-of-voice (complete params/response/error codes in references/api.md)
  • Python Script: python scripts/amazon_keyword_share_of_voice.py '<JSON params>' [--inline]
  • Cost constraint: This tool consumes credits; the same session and parameter combination is called only once by default, with a 24h local cache in the script. On failure or empty results, do not automatically retry with different keywords, pagination, or postal codes; inform the user about additional consumption before continuing to search.

Output strategy (script default behavior):

  • Always write the full response to <cwd>/nexscope/<YYYY-MM-DD>/<session>/data/nexscope-junglescout-keyword-share-of-voice-<timestamp>.json (<cwd> is the working directory at script execution time, i.e. the current project directory in Claude Code; <session> is taken from the SESSION_ID env var, auto-grouped by user task; do not write to /tmp, error if current directory is not writable)
  • Response body <= 8 KB: print full JSON to stdout after saving
  • Response body > 8 KB: print only summary to stdout after saving (top-level fields, common counts like total/costToken, length of largest list field + first 3 samples)
  • Add --inline to force full output to stdout (still saves to disk)

Data reading tip: Check the summary first to decide if it's enough; when specific fields are needed, prefer using jq or ConvertFrom-Json to extract from the saved json file on demand, avoiding loading the entire JSON into context.

How to Build Queries

Only two parameters are needed: marketplace and keyword.

Principles for Building API Calls

  1. Marketplace mapping: "US marketplace" -> us, "Japan marketplace" -> jp, "Germany marketplace" -> de; default to us when unspecified
  2. Keyword: Pass the user's keyword as-is (lowercase English preferred)
  3. One keyword per call: Each request analyzes one keyword; for multi-keyword comparison, make separate calls

Common Query Scenarios

1. Brand dominance check -- Who owns this keyword?

json
{
  "marketplace": "us",
  "keyword": "portable charger"
}

Focus on combinedWeightedSov to see which brands dominate the search results page.

2. PPC competitive analysis -- Is this keyword worth bidding on?

json
{
  "marketplace": "us",
  "keyword": "wireless earbuds"
}

Compare exactSuggestedBidMedian with the keyword's search volume to gauge cost-efficiency. Check sponsoredWeightedSov to see how heavily competitors invest in ads.

3. Conversion efficiency of top ASINs

json
{
  "marketplace": "de",
  "keyword": "kopfhorer kabellos"
}

Examine the topAsins array to find whether the top-clicked products convert well. High clicks + low conversion rate may indicate opportunity.

4. Identify market gaps -- Are there underserved positions?

json
{
  "marketplace": "jp",
  "keyword": "yogamatto"
}

If no single brand has a combinedWeightedSov above 0.15, the keyword is fragmented and may be easier to enter. Combine with search volume to assess market size.

5. Compare organic vs sponsored presence

json
{
  "marketplace": "uk",
  "keyword": "running shoes"
}

A brand with high sponsoredWeightedSov but low organicWeightedSov relies heavily on ads; this can inform competitive strategy.

Display Rules

  1. Brand table: Show the brands table sorted by combinedWeightedSov descending; highlight the top 5 brands for quick comprehension
  2. SOV as percentage: Display SOV values as percentages (multiply by 100), e.g., 0.152 -> 15.2%
  3. Context header: Before the table, show the keyword's 30-day search volume (estimated30DaySearchVolume) and PPC bid median (exactSuggestedBidMedian) as context
  4. Top ASINs section: Show the TOP 3 ASIN table separately with click count, conversion count, and conversion rate
  5. Competitive summary: After the data, provide a brief competitive landscape summary: whether the keyword is dominated by a few brands or fragmented, and note any large gaps between organic and sponsored presence
  6. Error handling: When a query fails, explain the reason based on the error response and suggest adjusting parameters

Important Limitations

  • Coverage: Only the first 3 pages of Amazon search results are analyzed (typically ~48-60 products)
  • Single keyword: One keyword per API call; multi-keyword comparison requires separate calls
  • SOV is a snapshot: Data reflects a point-in-time crawl, not a historical trend
  • No historical SOV: This tool does not provide SOV changes over time; use the keyword history tool for volume trends

User Expression & Scenario Quick Reference

Applicable -- Brand market share and competitive analysis on Amazon search results:

User SaysScenario
"Who has the largest share for this keyword"Brand dominance analysis
"How competitive is this keyword"Competitive landscape assessment
"Who occupies all the ad slots"Sponsored SOV analysis
"Does any brand monopolize this keyword"Monopoly detection
"What's the approximate PPC bid for this keyword"PPC bid estimation
"Which brands rank at the top in search results"Brand visibility ranking
"How high is the conversion rate for this keyword"Top ASIN conversion analysis

Not applicable -- Beyond keyword Share of Voice scope:

  • Historical search volume trends (use keyword history tool)
  • Keyword suggestions / keyword mining (use ABA or keyword explorer tools)
  • Product-level sales estimation or review analysis
  • Listing optimization or copywriting advice
  • Non-Amazon platform data

Boundary judgment: When users say "competition analysis", "brand analysis", or "market landscape", if the intent is to understand which brands occupy the search results page for a specific keyword (share of voice / brand distribution), this skill applies. If they want product-level sales data, profit margins, or historical trends, it does not apply.

Authentication

Set the NEXSCOPE_API_KEY environment variable. If credentials are missing or expire, visit https://www.nexscope.ai/help/skills-external-access?co-from=skillNS to top up credits.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ecommerce.Amazon Keyword Share Of Voice AI skill do?

Nexscope keyword Share of Voice analysis, returning brand visibility share across the first 3 pages of Amazon search results (organic/ad/combined), 30-day exact search volume, median PPC bid, and TOP3 ASIN click and conversion data, covering 10 marketplaces. Trigger when the user mentions brand market share, brand voice share, search result brand distribution, Share of Voice, SOV analysis, brand competitive landscape, ad slot share, organic ranking brand share, PPC bid analysis, brand monopoly analysis, keyword share of voice, brand visibility, organic vs sponsored share, brand dominance, P...

Why use Ecommerce.Amazon Keyword Share Of Voice on TypingMind?

Because you install it once and use it with any model. Ecommerce.Amazon Keyword Share Of Voice is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ecommerce.Amazon Keyword Share Of Voice in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nexscope-ai/nexscope-ecommerce-skills/tree/main/ecommerce-amazon-keyword-share-of-voice. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ecommerce.Amazon Keyword Share Of Voice?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ecommerce.Amazon Keyword Share Of Voice?

As many as you like. As long as a model supports skills, you can use Ecommerce.Amazon Keyword Share Of Voice with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ecommerce.Amazon Keyword Share Of Voice AI skill free?

It is published on GitHub by nexscope-ai. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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