marketing-experimentation-and-channel-strategy

marketing-experimentation-and-channel-strategy is a skill for Claude Code, Codex from the-nam-shub/e5-real-skills. It costs 52 tokens per session (4,800 once invoked), scanned C, original, no licence file.

A guide to choosing marketing channels and running structured experiments. An experiment is a planned test used to compare approaches and learn what works.

In plain words
What is it for?
Use it to select channels, design marketing tests, interpret results, and adjust B2B marketing programs.
Why use it?
It helps teams evaluate new channels, compare results fairly, and decide where to spend time and effort next.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Use it to select channels, design marketing tests, interpret results, and adjust B2B marketing programs.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/the-nam-shub/e5-real-skills/marketing-experimentation-and-channel-strategy
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add the-nam-shub/e5-real-skills --skill marketing-experimentation-and-channel-strategy
Clone the repo
git clone --depth 1 https://github.com/the-nam-shub/e5-real-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for marketing-experimentation-and-channel-strategy

README.md
[![agentmods](https://agentmods.dev/badge/skills/the-nam-shub/e5-real-skills/marketing-experimentation-and-channel-strategy/github.svg)](https://agentmods.dev/skills/the-nam-shub/e5-real-skills/marketing-experimentation-and-channel-strategy)
Your own site
<a href="https://agentmods.dev/skills/the-nam-shub/e5-real-skills/marketing-experimentation-and-channel-strategy"><img src="https://agentmods.dev/badge/skills/the-nam-shub/e5-real-skills/marketing-experimentation-and-channel-strategy/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for marketing-experimentation-and-channel-strategy

Your own site · 80×15
<a href="https://agentmods.dev/skills/the-nam-shub/e5-real-skills/marketing-experimentation-and-channel-strategy"><img src="https://agentmods.dev/badge/skills/the-nam-shub/e5-real-skills/marketing-experimentation-and-channel-strategy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,800 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00052 $0.04800
Opus 5 $0.00026 $0.02400
Sonnet 5 $0.00010 $0.00960
Haiku 4.5 $0.00005 $0.00480

Measured 9d ago against content hash 3214ac4273d5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade C, and why

marketing-experimentation-and-channel-strategy scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Tells the agent never to refusehighAnti-refusal

Suppressing the ability to decline removes a core safety control; a later harmful request then succeeds.

- **Don't refuse all risk in experimentation.** You cannot refuse to cut spend, refuse to increase spend, and still expect to learn what works. Risk is the cost of learning. (Source: Pranav Piyush, Episode #259)
skills/marketing-experimentation-and-channel-strategy/SKILL.md · 198 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 198 lines · 52 tokens per session scan C 3214ac4273d5

Subscribe to this mod's changes

marketing-experimentation-and-channel-strategy is a skill published in the GitHub repository the-nam-shub/e5-real-skills (8 stars, last pushed yesterday), with no licence file. It adds 52 tokens to every session and 4,800 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 1 finding (tells the agent never to refuse). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

Other skills, from other repositories

abx-strategy

Build Account-Based Everything (ABX) GTM strategies for complex B2B sales. Use when working on ABM strategy, ICP scoring, messaging architecture, product launches, or pipeline acceleration for companies with <500 accounts, $100K+ deals, and 6+ month sales cycles.

yannickYamo/skills · 64 tokens

ai-native-product

Build AI-native products with agency-control tradeoffs, calibration loops, and eval strategies. Use when building AI agents, LLM features, or products where AI handles user tasks autonomously. Part of the Modern Product Operating Model collection.

yannickYamo/skills · 50 tokens

product-architecture

Structure what you're building and why now. Use when organizing products into capability blocks, creating bet backlogs, building roadmaps, or writing solution briefs. Part of the Modern Product Operating Model collection.

yannickYamo/skills · 43 tokens

product-delivery

Ship, measure, and learn effectively. Use when planning staged rollouts, setting up metrics hierarchies, running bet retrospectives, or executing GTM launches. Part of the Modern Product Operating Model collection.

yannickYamo/skills · 46 tokens

product-discovery

Run continuous discovery to find problems worth solving. Use when setting up weekly discovery rhythm, building Opportunity Solution Trees, creating interview snapshots, exploring solutions, or testing assumptions before committing engineering resources. Part of the Modern Product Operating Model collection.

yannickYamo/skills · 50 tokens

product-leadership

Operate as a Director or CPO leading product organizations. Use when managing product portfolios, aligning with executives, communicating to boards, designing team structures, or establishing operating rhythms. Part of the Modern Product Operating Model collection.

yannickYamo/skills · 48 tokens