Roi Calculator
aaron-he-zhu/aaron-marketing-skills
A skill your agent uses when the user asks to "calculate influencer ROI", "prove campaign value", or "what was our ROAS"; produces direct ROI/ROAS, earned media value, attribution-modeled revenue…
Calculate and analyze promotional ROI including incremental sales lift, margin impact, and promo type comparison.
MITAuto-check passed
Install Ecom Promo Roi
$ npx skills add asgard-ai-platform/skills --skill ecom-promo-roi -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install asgard-ai-platform/skills ecom-promo-roi --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/ecom-promo-roi .claude/skills/ecom-promo-roi && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "ecom-promo-roi" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/ecom-promo-roi into .claude/skills/ecom-promo-roi/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ecom-promo-roi", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/asgard-ai-platform/skills/tree/main/ecom-promo-roiType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add asgard-ai-platform/skills --skill ecom-promo-roi -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install asgard-ai-platform/skills ecom-promo-roi --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/ecom-promo-roi .agents/skills/ecom-promo-roi && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ecom-promo-roi" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/ecom-promo-roi into .agents/skills/ecom-promo-roi/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ecom-promo-roi", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add asgard-ai-platform/skills --skill ecom-promo-roi -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install asgard-ai-platform/skills ecom-promo-roi --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/ecom-promo-roi .cursor/skills/ecom-promo-roi && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ecom-promo-roi" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/ecom-promo-roi into .cursor/skills/ecom-promo-roi/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ecom-promo-roi", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/asgard-ai-platform/skills.git --path ecom-promo-roi--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add asgard-ai-platform/skills --skill ecom-promo-roi -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install asgard-ai-platform/skills ecom-promo-roi --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/ecom-promo-roi .gemini/skills/ecom-promo-roi && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ecom-promo-roi" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/ecom-promo-roi into .gemini/skills/ecom-promo-roi/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ecom-promo-roi", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install asgard-ai-platform/skills ecom-promo-roiInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add asgard-ai-platform/skills --skill ecom-promo-roi -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/ecom-promo-roi .github/skills/ecom-promo-roi && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ecom-promo-roi" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/ecom-promo-roi into .github/skills/ecom-promo-roi/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ecom-promo-roi", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add asgard-ai-platform/skills --skill ecom-promo-roi -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install asgard-ai-platform/skills ecom-promo-roi --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/ecom-promo-roi .opencode/skills/ecom-promo-roi && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ecom-promo-roi" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/ecom-promo-roi into .opencode/skills/ecom-promo-roi/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ecom-promo-roi", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
ecom-promo-roi- GitHub stars
- 242
- Token cost
- ~1.1k tokens
- SKILL.md length
- 387 words
- Files
- 3 (incl. references)
- Skills in repo
- 207
- Repo updated
- First seen
- Licence
- MIT
At a glance
Calculate and analyze promotional ROI including incremental sales lift, margin impact, and promo type comparison.
- The user needs to evaluate whether a promotion was profitable
- SKILL.md covers Framework, Output Format, Gotchas and References
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Compare promotion types
What it does
Ecom Promo Roi is an agent skill from asgard-ai-platform/skills. Calculate and analyze promotional ROI including incremental sales lift, margin impact, and promo type comparison. Use this skill when the user needs to evaluate whether a promotion was profitable, compare promotion types, simulate promo scenarios, or optimize promotional spending — even if they say 'was this sale worth it', 'which promo type works best', 'are we giving away too many discounts', or 'plan our next promotion'.
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `examples/sample_scenario.md` and `references/promo-testing.md`).
The repository describes itself as: 301 open-source coding agent skills across 22 domains — methodology, judgment & gotchas packaged as Claude Agent Skills for the Asgard AI Platform. The licence is MIT.
When your agent uses it
- The user needs to evaluate whether a promotion was profitable
- Compare promotion types
- Simulate promo scenarios
- Optimize promotional spending — even if they say was this sale worth it
Example prompts
- “was this sale worth it”
- “which promo type works best”
- “are we giving away too many discounts”
- “/ecom-promo-roi”
What it can do on your machine
Read from SKILL.md and the folder at commit 4e7f4f8. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Ecom Promo Roi loads about 1.1k tokens when it runs, and up to ~3.7k if it reads all its reference files. Until then it costs about 111 tokens; SKILL.md has 387 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 387 words, ~1,116 tokens.
Download SKILL.mdSave it as
.claude/skills/ecom-promo-roi/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- ecom-promo-roi
- description
- Calculate and analyze promotional ROI including incremental sales lift, margin impact, and promo type comparison. Use this skill when the user needs to evaluate whether a promotion was profitable, compare promotion types, simulate promo scenarios, or optimize promotional spending — even if they say 'was this sale worth it', 'which promo type works best', 'are we giving away too many discounts', or 'plan our next promotion'.
- metadata.category
- WP-01 電商
- metadata.tags
- e-commerce, promotion, roi, marketing
Promotion ROI Analysis
Framework
IRON LAW: Measure INCREMENTAL Sales, Not Total Sales During Promo
A promotion that generates $100K in revenue during a sale week looks great —
until you realize $80K would have happened anyway (baseline). The incremental
lift is only $20K. If the discount cost $25K in margin, the promo LOST money.
Promo ROI = (Incremental Revenue × Margin - Promo Cost) / Promo CostKey Metrics
| Metric | Formula |
|---|---|
| Incremental Revenue | Promo period revenue - Baseline revenue (what would have happened without promo) |
| Promo Cost | Discount amount + marketing spend + operational cost |
| Promo ROI | (Incremental Gross Profit - Promo Cost) / Promo Cost |
| Cannibalization Rate | % of promo sales that would have occurred at full price |
| Pull-Forward Rate | % of promo sales that are just earlier purchases (customers would have bought next week anyway) |
Promo Type Comparison
| Type | Mechanism | Pros | Cons |
|---|---|---|---|
| % Discount | 20% off everything | Simple, high traffic | Erodes brand, trains discount-waiting |
| $ Off | NT$200 off orders >NT$1000 | Drives AOV up | Less exciting for low-AOV customers |
| BOGO | Buy one get one free | Moves inventory fast | 50% margin hit, attracts deal-seekers |
| Gift with purchase | Free item with min spend | Protects price perception | Cost of gift, may not drive incremental |
| Flash sale | Time-limited deep discount | Urgency, high engagement | Operational stress, cannibalization |
| Loyalty points | Earn/redeem points | Builds retention, deferred cost | Complex to manage, redemption liability |
Analysis Steps
Phase 1: Establish Baseline
- What would revenue have been without the promo? (prior period, prior year same period, or control group)
- Account for seasonality, day-of-week effects, and trend
Phase 2: Calculate Incremental Impact
- Total promo revenue - baseline = incremental
- Subtract cannibalization and pull-forward estimates
- Calculate gross profit on incremental (not revenue)
Phase 3: Calculate Full Cost
- Discount dollars given up
- Marketing spend (ads, email, creative production)
- Operational cost (warehouse overtime, customer service spike)
Phase 4: Compute ROI and Decide
- ROI > 0: Promo was profitable
- ROI < 0 but strategic (new customer acquisition, inventory clearance): May still be justified
- ROI < 0 with no strategic rationale: Don't repeat
Show full SKILL.md (127 more words)Show less
Output Format
# Promo ROI Report: {Promotion Name}
## Promo Summary
- Type: {discount type}
- Period: {dates}
- Offer: {details}
## Results
| Metric | Value |
|--------|-------|
| Total Revenue (promo period) | ${X} |
| Baseline Revenue (estimated) | ${X} |
| **Incremental Revenue** | **${X}** |
| Incremental Gross Profit | ${X} |
| Promo Cost (discount + marketing + ops) | ${X} |
| **Promo ROI** | **{X%}** |
## Profitability Assessment
{Profitable / Unprofitable — with context}
## Recommendation
{Repeat / Modify / Discontinue — with rationale}Gotchas
- Baseline estimation is the hardest part: The accuracy of your ROI depends on how well you estimate what would have happened without the promo. Use prior year same period as a starting point, adjust for trend.
- Post-promo dip is real: Sales often drop BELOW baseline after a promotion (customers pulled purchases forward). Include the dip period in your analysis.
- Discounts are addictive: Customers learn to wait for sales. Track the % of revenue sold at full price over time — if it's declining, you have a discount dependency problem.
- New vs existing customer mix matters: A promo that acquires 500 new customers at negative ROI may be worth it if their LTV justifies the acquisition cost. Track separately.
References
- For A/B testing promotional offers, see
references/promo-testing.md
© asgard-ai-platform, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 2 other files (references) in ecom-promo-roi of asgard-ai-platform/skills.
- SKILL.md
- examples/sample_scenario.md
- references/promo-testing.md
Open the folder on GitHubat commit 4e7f4f8
Compare with similar skills
Ecom Promo Roi next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Ecom Promo Roi this skillasgard-ai-platform/skills | 242 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Roi Calculatoraaron-he-zhu/aaron-marketing-skills | 2.9k | — | ~3.6k | Automated safety check: Pass | Apache-2.0 | |
| Roi CalculatorZJU-REAL/Easel | 3.4k | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Roi Calculatorindranilbanerjee/digital-marketing-pro | 862 | 1 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Roi Calculatoraiskillstore/marketplace | 433 | — | ~3k | Automated safety check: Pass | Apache-2.0 | |
| Promotealirezarezvani/claude-skills | 28k | 1 repos | ~1.1k | Automated safety check: Pass | MIT |
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Questions about Ecom Promo Roi
What does Ecom Promo Roi do?
Calculate and analyze promotional ROI including incremental sales lift, margin impact, and promo type comparison. Ecom Promo Roi is an agent skill from asgard-ai-platform/skills. Calculate and analyze promotional ROI including incremental sales lift, margin impact, and promo type comparison.
When should I use Ecom Promo Roi?
Ecom Promo Roi fits situations like: the user needs to evaluate whether a promotion was profitable; compare promotion types; simulate promo scenarios; optimize promotional spending — even if they say was this sale worth it.
How do I install Ecom Promo Roi in Claude Code?
Run `npx skills add asgard-ai-platform/skills --skill ecom-promo-roi -a claude-code`. Or copy the skill folder (ecom-promo-roi in asgard-ai-platform/skills) into .claude/skills/ecom-promo-roi in your project. Claude Code loads it when a task matches its description.
How do I install Ecom Promo Roi in Codex?
Run `npx skills add asgard-ai-platform/skills --skill ecom-promo-roi -a codex`. Or copy the skill folder (ecom-promo-roi in asgard-ai-platform/skills) into .agents/skills/ecom-promo-roi in your project. Codex loads it when a task matches its description.
Can I use Ecom Promo Roi in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add asgard-ai-platform/skills --skill ecom-promo-roi -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ecom-promo-roi, .gemini/skills/ecom-promo-roi, .github/skills/ecom-promo-roi and .opencode/skills/ecom-promo-roi in your project.
What does Ecom Promo Roi need to run?
SKILL.md names no scripts, command-line tools or credentials: Ecom Promo Roi is instructions for the agent only.
Does Ecom Promo Roi access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Ecom Promo Roi safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Ecom Promo Roi use?
Ecom Promo Roi is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Ecom Promo Roi use?
About 1.1k tokens (SKILL.md is roughly 4.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.6k tokens, read only when the agent opens those files.
What are the alternatives to Ecom Promo Roi?
Skills that share tags, products or a category with Ecom Promo Roi: Roi Calculator (aaron-he-zhu/aaron-marketing-skills, 2.9k stars), Roi Calculator (ZJU-REAL/Easel, 3.4k stars), Roi Calculator (indranilbanerjee/digital-marketing-pro, 862 stars) and Roi Calculator (aiskillstore/marketplace, 433 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Ecom Promo Roi?
asgard-ai-platform (a GitHub organization) maintains it in asgard-ai-platform/skills, which has 242 GitHub stars. The repository holds 207 skills in this directory. The repository was last updated on June 6, 2026.
Source: asgard-ai-platform/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.