Commission Calculator

Commission Calculator

Project realistic monthly affiliate earnings based on traffic estimates, platform conversion rates, and program commission structures. Helps affiliates decide which programs are worth their time before investing months of content creation.

Stage

This skill belongs to Stage S1: Research

When to Use

• User wants to project income before choosing a program
• User wants to compare the earnings potential of 2+ programs
• User is setting income goals and needs realistic benchmarks
• User is deciding whether a niche is worth entering based on earning potential
• User asks "how many page views / subscribers / followers do I need to make X"

Input Schema

{
  programs: [
    {
      name: string            # (required) "HeyGen"
      reward_value: string    # (required) "30%" or "$50"
      reward_type: string     # (required) "cps_recurring" | "cps_one_time" | "cpl" | "cpa"
      reward_duration: string # (optional) "12 months" | "lifetime" | "first purchase"
      cookie_days: number     # (optional, default: 30) 30
      avg_product_price: number # (optional) Monthly plan price in USD. Needed for % commissions
    }
  ]
  traffic: {
    monthly_visitors: number  # (optional) Estimated monthly website visitors or video views
    email_subscribers: number # (optional) Email list size
    social_followers: number  # (optional) Followers on primary platform
  }
  platform: string            # (optional) "blog" | "youtube" | "tiktok" | "email" | "twitter"
  scenario: string            # (optional, default: "realistic") "conservative" | "realistic" | "optimistic"
  goal: string                # (optional) Target income, e.g., "$500/mo" or "$1000/mo"
  time_horizon: string        # (optional, default: "90 days") "30 days" | "90 days" | "12 months"
}

Workflow

Step 1: Gather Program Details

If program details are missing, pull from openaffiliate.dev (see references/openaffiliate-api.md in affiliate-program-search).

Key fields to extract: reward_value, reward_type, cookie_days.

If avg_product_price is not provided and reward_type is percentage-based, estimate it:

• Use web_search "[program name] pricing" to find the most common paid plan price
• For SaaS: use the mid-tier plan (e.g., $49/mo on a $19/$49/$99 structure)
• Note the assumption in output so user can adjust

For cps_recurring programs, establish payout duration:

• "Lifetime" = commissions paid as long as customer stays (most valuable)
• "12 months" = commissions paid for customer's first year
• "First purchase only" = functionally the same as one-time despite being subscription

Step 2: Gather Traffic Estimates

If traffic data is not provided, prompt the user OR use platform benchmarks:

If user won't provide traffic, use "realistic" scenario benchmarks for their stated platform and growth stage.

Step 3: Apply Conversion Rate Assumptions

Use these industry-standard conversion rates as defaults. Adjust based on traffic quality ("buyer intent" content converts 5-10x better than informational content):

For scenario multipliers:

• Conservative: use lower bound of each range
• Realistic: use midpoint
• Optimistic: use upper bound

Step 4: Calculate Monthly and Projected Earnings

Formula:

Monthly clicks = Monthly visitors × Click-through rate
Monthly conversions = Monthly clicks × Affiliate conversion rate
Monthly commission = Monthly conversions × Commission per sale

Commission per sale:
  - Percentage-based: avg_product_price × (reward_value / 100)
  - Fixed: reward_value (as number)

For recurring (monthly SaaS) over time_horizon:
  Month 1 revenue = Month 1 conversions × commission_per_sale
  Month 2 revenue = (Month 1 conversions + Month 2 conversions) × commission_per_sale
  Month N = sum of all active subscribers × commission_per_sale
  [Cap at reward_duration if not lifetime]

Calculate for each program:

• Monthly commission at current traffic
• Cumulative commission at 30, 90, 180, 365 days
• Visitors needed to hit user's income goal (if provided)
• Time to first commission (assuming current traffic growth)

Step 5: Side-by-Side Comparison (Multiple Programs)

If 2+ programs are provided, produce a comparison table:

• Sort by 12-month projected earnings (highest first)
• Flag programs where recurring vs. one-time makes a dramatic difference
• Call out programs with short cookie windows — lower conversion rates assumed
• Note programs with minimum payout thresholds that could delay first payment

Step 6: Reverse Calculation (If Goal Provided)

If user states an income goal (e.g., "I want $500/mo"), calculate:

• Visitors/month needed to hit that goal with each program
• Number of sales/leads needed per month
• How long to reach that traffic level (using typical affiliate blog growth curves: months 1-6 = slow, months 7-12 = acceleration, year 2 = compounding)

Step 7: Sanity Check and Context

Add context so user isn't misled by numbers:

1. These are projections, not guarantees. Real results vary significantly.
2. High-quality, buying-intent traffic converts 3-5x better than general traffic.
3. First sales often take 2-3 months even with good traffic (cookie window, indecision).
4. Recurring programs feel slow at first but compound — show the Year 1 vs Year 2 difference.