Skip to content
cccskills
FreePublished on GitHub

roi-calculator

Calculate returns from influencer campaign spending and results, including ROI, revenue per advertising dollar, media value estimates, and customer lifetime value scenarios. Get formulas, clearly labeled assumptions, and a summary for stakeholders.

OriginalShow the original description

Use 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, LTV-based ROI, and a stakeholder-ready summary. Not for building the full slide/written report — use report-generator. 达人营销ROI计算/投资回报测算

Run score Not tested

See how to install

Good for

  • Calculate campaign ROI and revenue per advertising dollar
  • Compare returns using direct revenue, media value, and lifetime value
  • Compare returns across influencers and tiers
  • Prepare return figures for budget discussions

Files included (2)

  • SKILL.md14.3 KB
  • references/roi-templates.md18.9 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

ROI Calculator

This skill helps you calculate and communicate the return on investment for influencer marketing campaigns using various methodologies appropriate for your goals and available data.

Cross-discipline (paid ads): this is the shared return-math engine for paid ads — paid-measurement-loop, attribution-reconciler, and budget-optimizer delegate ROAS/CPA/payback ratios here rather than recomputing them. Save paid runs under memory/ad/roi-calculator/.

Quick Start

Shortest invocation:

Calculate ROI for our influencer campaign: $25K spend, $72K revenue, 2.1M reach

Common scenario — compare methods before reporting:

What's the ROI of our campaign using direct revenue, EMV, and LTV-based methods?

Skill Contract

  • Reads: campaign ID, complete opaque creator scope when creator-level math is requested, spend/cost-basis breakdown, deduplicated results data (reach, impressions, engagements, clicks, conversions, attributed revenue, new customers), the predeclared attribution model/window/decision rule, AOV and economic LTV inputs if LTV is in scope, and prior performance output from performance-analyzer. Reuse authorized opaque creator_ref values; raw handles/names/URLs/provider IDs stay transient and never identify a saved row.
  • Writes: return the ROI calculation and summary inline by default; save them to memory/influencer/roi-calculator/YYYY-MM-DD-<topic>.md (or the declared paid path) only with exact WARM-save authorization. Saved output uses campaign_id, complete opaque creator_ref scope, and opaque evidence/artifact refs—never raw identity locators.
  • Promotes: only with separate exact authorization, promote durable headline numbers with their attribution window, source, and uncertainty to memory/hot-cache.md; a calculation or WARM-save request does not authorize this operation.
  • Done when:
    1. At least one ROI methodology is computed with the inputs and formula shown.
    2. Each headline metric is stated against a declared, source-dated comparison target; no universal benchmark is invented.
    3. A bottom-line arithmetic assessment and 1-3 recommendations are written. Call the campaign profitable only when attributed revenue and a complete campaign cost basis are verified; otherwise state that profitability is unverified.
    4. Every denominator is verified numeric and > 0; zero, negative, missing, or incompatible denominators yield undefined/NEEDS_INPUT, never a ratio.
  • Primary next skill: report-generator

Handoff Summary

Emit the standard shape from skill-contract.md §Handoff Summary Format.

Data Sources

This family is Tier 1 — it works with no live integrations. Ask the user for spend and results data and compute everything from those inputs. Connectors below can pull the numbers automatically when available:

  • ~~social platform analytics — reach, impressions, engagements, video views per platform for EMV and cost-per-metric math.
  • ~~ecommerce / analytics — revenue, conversions, link clicks, and AOV for direct ROI and attribution.
  • ~~CRM — new-customer counts, repeat-purchase rate, and lifetime value for LTV-based ROI.
  • ~~influencer database — per-influencer fees and tier data for by-influencer ROI.

With zero integrations, supply the investment and results tables by hand and the skill still produces every calculation. See CONNECTORS.md for the free/keyless recipe per category.

Instructions

When a user requests ROI calculation, work the steps below. Each step has a fill-in template in references/roi-templates.md — link the step number to its block there.

  1. Gather ROI inputs — campaign details, the investment (total spend) table, and the results-data table. (template)

  2. Calculate direct ROI — Simple ROI = (Revenue − Investment) / Investment × 100; ROAS = Revenue / Investment. Call the difference net return under the declared formula, not profit, unless the revenue attribution and complete cost basis are verified. State positive/zero/negative arithmetic return and a separate profitability-verification status. (template)

  3. Calculate Earned Media Value (EMV) — impression-based (Impressions × comparable CPM / 1000) or engagement-based (Engagements × comparable CPE) only from supplied or cited, source-dated comparators. Report applicable methods separately and use a predeclared selection/weighting rule; never average or add overlapping methods by default. If no valid comparator exists, return NEEDS_INPUT for EMV. (template)

  4. Calculate cost-efficiency metrics — CPM, CPR, CPE, CPV, CPC, CPA, and CAC. Compare only against a declared, source-dated target with a compatible market, window, and attribution basis; otherwise report the metric descriptively and mark the comparison pending. (template)

  5. Apply attribution modeling — use one predeclared model only after the complete conversion universe, order/event dedupe key, journey touchpoints, eligible channels, and allocation rule are supplied. Optional alternative models are visibly non-additive sensitivity scenarios over the same deduplicated conversion set; never select the most favorable model after seeing results. Missing inputs or model-selection authority returns NEEDS_INPUT, not attributed revenue. (template)

  6. Calculate customer lifetime value impact — label the result LTV-Based ROI only when New Customers is deduplicated against the controlling attribution universe and the supplied LTV is a complete contribution-margin basis with cohort, horizon, retention/churn, refunds, margin, discount/timing, first-order inclusion, source/date, and a positive compatible investment denominator. Then use ((New Customers × contribution-margin LTV) − Investment) / Investment × 100. A revenue-LTV input produces only an Estimated revenue-basis scenario with its basis/horizon/status; it is not economic ROI or profit and is never added to direct attributed revenue or another LTV horizon. Missing fields return NEEDS_INPUT. (template)

  7. Calculate by-creator ROI — only for a complete locked creator scope with resolved opaque refs, compatible windows/cost bases, and deduplicated attributed revenue. Per-creator and tier aggregate ROAS is sum(attributed revenue) / sum(spend), never a simple mean; rank only under a predeclared rule. (template)

  8. Generate the ROI report summary — investment, returns, ROI by methodology, key metrics vs. benchmark, bottom line, and 1-3 recommendations. (template)

  9. Qualify candidate Return (R) evidence for the gate

    The financial outputs from steps 1–8 are candidate Return (R) evidence for STAR: ROI/ROAS read against the declared target (R1) and the alternative-channel baseline (R3), CPE/CPM/CPA benchmarked on a normalized window (R2), KPI attainment versus the pre-registered target (R4), conversions attributed with a stated method and rigor (R5), and incremental impact separated from baseline where measurable (R6). A field is Measured only when its exact source, entity, observation window, and attribution basis are verified; arithmetic on User-provided or Estimated inputs is Calculated, not Measured. Return evidence applies only at assessment_time: actual; a forecast read has no R1–R6.

    Hand this Return evidence to the creator-content-auditor gate — it folds R into the full actual STAR run and computes the profile-weighted SQS. This skill does not run the scorer or emit the composite. Unverified conversions emit results-unverified: report R1/R2/R5 as low-confidence and make no attributable-return claims. These financial numbers are consumed as R evidence; they are not themselves an SQS.

    For a multi-creator campaign, the gate scores each creator partnership separately; a budget-weighted mean of the per-partnership SQS values may summarize the campaign but never replaces the per-partnership diagnosis. This skill supplies the per-partnership Return evidence; it does not aggregate or roll up a composite.

  10. Persist only with permission — save under memory/influencer/roi-calculator/ (or the paid path) only after authorization; request separate authorization for hot-cache promotion.

For every formula in this skill, verify the denominator is numeric and strictly greater than zero. If investment, impressions, reach, engagements, views, clicks, acquisitions, customers, or another required denominator is zero, negative, missing, or incompatible with the numerator window, report the ratio as undefined and return NEEDS_INPUT for that metric. Never silently divide by zero, coerce it, or substitute a nominal value.

Example

User: "Calculate ROI for our influencer campaign: $25K spend, $72K revenue, 2.1M reach"

Output:

# ROI Calculation Summary

## Investment & Returns

| Item | Value |
|------|-------|
| Total Investment | $25,000 |
| Revenue used in calculation | $72,000 (User-provided; source/window unverified) |
| Total Reach | 2,100,000 |

## ROI Results

### Direct ROI — calculated on User-provided revenue basis
- **Net return under the declared formula**: $47,000
- **ROI**: 188%
- **ROAS**: 2.88:1

The supplied revenue implies $2.88 per $1 spent. `results-unverified`: no attribution source, method, or window was supplied, so this is not an attributable, causal, or incremental-return claim.

### Earned Media Value
- **EMV**: `NEEDS_INPUT` — no source-dated comparable CPM/CPE or declared valuation rule was supplied
- **EMV Multiple**: `NEEDS_INPUT`

### Cost Efficiency
- **CPM**: $11.90
- **CPA**: Unknown (conversion count was not supplied)

## Assessment: Positive arithmetic return on the supplied basis; profitability and causality unverified

Supplied revenue exceeds supplied investment under the declared formula, but no complete cost basis, attribution source/window, source-dated peer target, or incrementality evidence was provided. Do not infer profit, benchmark outperformance, or causal lift, and do not authorize a scale decision from this read alone; obtain verified conversions, attribution evidence, complete costs, and the campaign owner's precommitted decision rule first.

The source-dated benchmark evidence template lives in references/roi-templates.md#benchmark-evidence-template.

Reference Materials

Next Best Skill

Primary: report-generator — turn the ROI numbers into a stakeholder-ready report.

Alternates (same Report family):

  • performance-analyzer — go back for deeper performance breakdowns if the ROI math exposed gaps.
  • budget-optimizer — feed by-influencer and by-tier ROI into the next budget allocation.

Termination note: keep a visited-set of skills invoked this session. If the primary next skill was already run, stop and report the chain complete rather than re-invoking it. Stop after at most 3 hops in a single chain.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Audit paid advertising accounts before increasing spend by comparing campaign exports with your own sales or lead records. Review 20 criteria covering measurement, spending, and safety, then receive a decision and prioritized fixes.

  • Review an ad account before increasing its budget
  • Check reported ad returns against sales and lead records
  • Identify wasted spend and prioritize measurement fixes
aaron-he-zhu/aaron-marketing-skills3KUpdated Oct 25, 2026

Create paid-ad headlines, descriptions, and opening hooks that match the destination page. Build a matrix of messaging angles and variants, check format limits, and flag unsupported claims or policy risks before handing the set off for review.

  • Drafting responsive search ad headlines and descriptions
  • Comparing ad angles and opening hooks
  • Replacing weak headlines while keeping successful ones
aaron-he-zhu/aaron-marketing-skills3KUpdated Oct 25, 2026

ad-test-designer

FreeSummary

Plan advertising and landing page experiments with a clear hypothesis, controlled variants, sample sizes, and duration. Interpret exported results by separating statistical evidence from meaningful business impact, applying an action rule only when its owner approved it in advance.

  • Plan an A/B test for landing page headlines
  • Estimate sample size and duration for an ad test
  • Assess effect size and uncertainty in exported test results
aaron-he-zhu/aaron-marketing-skills3KUpdated Oct 25, 2026

Design employee and founder sharing programs with voluntary participation, personalized share kits, disclosure lines, and staggered posting windows. Get roster and Slack or Teams distribution specifications, plus safeguards against identical coordinated posts and organized engagement exchanges.

  • Designing a voluntary employee sharing program
  • Preparing personalized launch share kits
  • Planning founder posts and disclosure lines
aaron-he-zhu/aaron-marketing-skills3KUpdated Oct 25, 2026

Reconcile paid advertising conversions with GA4 or ecommerce order records. Identify duplicate and unmatched claims, align attribution windows and currencies, compare how models assign credit, and assess additional orders when test and control data are available.

  • Find sales claimed by both Meta and Google
  • Build a monthly conversion reconciliation workbook
  • Compare results across attribution models
aaron-he-zhu/aaron-marketing-skills3KUpdated Oct 25, 2026

Turn customer interviews and won or lost deal notes into a map of buyer beliefs, recurring objections, and reasons to switch or stay. Each finding includes its evidence, with suggested ways to address objections and clear labels for assumptions.

  • Map buyer beliefs from customer interviews
  • Organize recurring sales objections and response angles
  • Identify reasons buyers switch or stay
aaron-he-zhu/aaron-marketing-skills3KUpdated Oct 25, 2026

See all skills by aaron-he-zhu

Report a problem with this skill