What's a typical refund rate for online courses?

Industry typical is 5-12% for self-paced online courses. Cohort-based courses (live, scheduled, accountability-driven) often see <5% — the higher engagement reduces buyer's remorse. Cold-launched broad-appeal courses (Facebook ads → cold traffic → checkout) commonly see 10-20% because of higher impulse-buy refunds. Above 15% sustained is a flag — typically signals positioning / promised-outcome / fulfillment-quality mismatch. Lifting onboarding quality (welcome video + first-week wins + clear roadmap) often pulls refund rate 3-5pp lower.

How does conversion rate scale with price?

The calculator applies a price-aware adjustment: low tier ×1.4 (more accessible, less price scrutiny), mid ×1.0 (baseline), high ×0.65 (premium pricing reduces conversion). Real-world variance is wider — cold audiences hit closer to ×0.4 at premium tiers, while loyal audiences sometimes match or exceed mid CR even at premium. Use the calculator as a planning starting point and compare against your last-launch actuals if you have them.

Should I optimize for max revenue or max profit?

Max profit, almost always. Max revenue is a vanity number — selling 100 units at $297 produces $29.7K revenue, but if production cost is $20K that's only $9.7K profit. Selling 30 units at $997 produces $29.9K revenue at the same production cost = $9.9K profit, but with way less fulfillment burden. The calculator separates these explicitly because they often disagree, and the right move depends on your business goal. Pure-revenue optimization makes sense when you're early-stage building case studies; once you're past that, profit is the right number.

What's the 35% launch CTR coefficient?

Cumulative click-through rate across a 5-7 email launch sequence — well above per-send CTR (typically 2-4%) because the same audience sees the same offer multiple times. The math: per-send CTR averages 5-8% across the launch, and most active subscribers click at least once across the sequence. The 35% coefficient is conservative-defensible across the creator-economy launch playbook (Jeff Walker / Amy Porterfield style). For shorter 2-3 email launches, drop to 20-25%.

How do I size production cost honestly?

Three buckets. (1) Hard costs: video production (camera + editing), course platform fees (Teachable, Podia, Kajabi typically $99-299/mo), email/automation, asset design. Typical solo creator: $1,500-3,000. (2) Marketing: paid ads (Meta + Google during launch window), sponsorships, affiliate fees. Typical: $3,000-15,000 for first launch, less for repeat. (3) Your time at honest hourly rate: 80-150 hours total at $80-150/hr = $6,400-22,500. Most creators skip bucket 3 and dramatically understate true production cost. Use the true-hourly-rate-calculator to set bucket 3 honestly.

Why does the calc fix multipliers at 1.4 / 1.0 / 0.65?

The multipliers are sourced from creator-economy launch data (Convertkit, Podia, Teachable aggregate stats) showing that doubling price typically halves conversion in the cold→warm audience zone. The 1.4 / 1.0 / 0.65 stack approximates that elasticity at the typical tier spreads ($297-$497-$997 range). For very-different price spreads (e.g., $97 vs $4,997), the multipliers are too coarse — adjust expected conversion rates manually on the input side instead.

What about pricing psychology (charm + anchoring + payment plans)?

This calculator handles the unit economics; the pricing-psychology-calculator handles the conversion-lift side (charm pricing $X9, anchoring tier strikethroughs, payment plans). Stack them: this calc tells you the tier-revenue math; the psychology calc tells you the additional CR lift from psychological levers on top. Combined, you get the full picture — tier choice + presentation impact.

Three-tier vs single-price launch?

Three-tier almost always outperforms single-price for courses above $200. Reasons: (1) decoy effect — premium tier makes mid look like value, lifting mid-tier CR 10-20%. (2) anchoring — buyers compare across tiers, settling on the one that matches their commitment level. (3) revenue capture — high-LTV buyers self-select up. Single-price launches under $100 work fine because the price-resistance ceiling is low. Above $200, three-tier is the standard playbook.

What if my audience is < 1,000 subs?

The calc still works but treat output as planning-rough. Below 1K reachable audience, launch math is dominated by individual-conversion variance — one big customer can swing the numbers more than tier choice. For sub-1K audiences, focus on (a) higher-priced premium tier (smaller volume × higher per-unit), (b) waitlist + presell to validate demand before production, (c) cohort format with $1K+ pricing to compress sales. Skip the three-tier playbook until you're past 2K reachable.

Are launch math projections reliable?

Within ±30% if your inputs are honest. Reachable audience is the trickiest — most creators count their dashboard subscriber number rather than the deliverable / active list, overcounting 20-40%. Open rate during launches is usually 5-10pp lower than baseline (launch fatigue), and creators forget that. CR varies wildly by audience temperature. Use last-launch actuals if you have them; otherwise treat projections as a planning floor and budget conservatively.

How do I lift conversion at the premium tier?

Three high-leverage moves. (1) Add scarcity: cohort-based with limited seats (50 spots vs unlimited self-paced) compresses decision time and lifts premium CR 30-50%. (2) Add 1-on-1 component: even one 30-min onboarding call with you justifies $300-500 premium for high-trust buyers. (3) Add testimonial-density: case studies with concrete outcome metrics ("made $12K in 60 days") double-digit lift premium CR more than any other input. Generic logos / faceless testimonials don't move the needle.

What's the difference between this and the SaaS pricing tier calc?

Course pricing optimizer: one-time product launch math. Inputs are launch-specific (audience reach + open rate + tier prices + refund + production cost). Output is total launch revenue + profit. SaaS pricing tier: subscription-recurring math. Inputs are CAC + ACV + churn + LTV multiplier. Output is LTV/CAC ratio + payback period. Different math, different decision frame — use this for course/cohort/info-product launches; use SaaS calc for recurring-revenue products.

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Course Pricing Optimizer — Three-Tier Revenue + Profit Comparison

Drop your audience size, open rate, expected conversion rate, low/mid/high tier prices, refund rate, and one-time production cost. The calculator surfaces revenue + profit at each tier (with price-aware CR adjustment), separates max-revenue from max-profit, and shows the break-even sales count for each tier — the math creators rarely run before launch.

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Reviewed by CalcBold EditorialLast verified May 4, 2026Methodology

Reachable audience

Reachable audience: email list + active social followers. Use the union, not just one channel — launches typically pull from email + IG + Twitter combined. Most creators undercount by 30-40% by ignoring secondary channels.

Open rate

Average open rate during a launch sequence (typically lower than baseline due to launch fatigue). Use the average across last 4 launch emails, not the dashboard headline. Aggressive launch sequences see 30-45% open rate sustained.

Expected conversion rate

Click-to-purchase conversion. Cold audience: 0.5-1.5%; warm: 2-5%; loyal: 5-15%. Calculator applies a price-aware adjustment per tier (low ×1.4, mid ×1.0, high ×0.65).

Low tier price

Lower-tier price option (most accessible). Common solo-creator courses cluster $97-$297 for self-paced + light-feedback formats.

Mid tier price

Middle-tier price (typical sweet spot for online courses). Most established creators land here with cohort + community + extra calls.

High tier price

Premium-tier price (high-trust signal, lowest CR but highest revenue per buyer). Common for cohort-based courses with founder access + 1-on-1 consults.

Refund rate

Industry typical: 5-12% online courses; cohort-based often <5%; cold-launched broad-appeal courses 10-20%. Use last-launch actual, not the optimistic projection.

Production cost

One-time launch cost: production + marketing + ads + tool subscriptions for the launch window. Budget loaded — most creators undercount by 30-50% by skipping their own time at honest hourly rate.

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What This Calculator Does

The Course Pricing Optimizer answers the question every creator skips before launch: which tier price actually maximizes profit, not just gross revenue? Drop your reachable audience (email list + active social), launch open rate, expected click-to-purchase conversion rate, low / mid / high tier prices, refund rate, and one-time production cost. The calculator applies a price-aware conversion adjustment per tier (low ×1.4, mid ×1.0, high ×0.65), nets refunds, subtracts production cost, and surfaces max-revenue separately from max-profit — because they almost never agree, and the right number depends on which one you’re actually optimizing for.

Creator-economy launch advice is full of round-number pricing dogma — “always charge $497” or “triple your price and convert anyway.” Neither is the math. Tier choice is an elasticity problem — doubling price typically halves conversion in the cold-to-warm zone, and break-even sales counts shift dramatically across $97, $497, and $1,997. CalcBold’s version is free, no signup, no “book a strategy call to learn my secrets” — just the launch math nobody else will run for you before you go live.

The Math — Three-Tier Launch Arithmetic

The headline number is gross revenue at each tier: launch clicks (audience × open rate × 35% cumulative launch CTR over 5-7 emails) × price-adjusted conversion rate × tier price. Refund rate is netted out of revenue, then production cost is subtracted to surface profit. The three multipliers (1.4 / 1.0 / 0.65) are sourced from creator-economy launch data showing roughly elasticity-1 pricing in the $97-$997 range — doubling price typically halves CR.

Two quirks worth calling out. First, the 35% launch CTR coefficient is cumulative across a 5-7 email sequence, not a per-send rate — per-send CTR averages 5-8%, but the same audience sees the same offer multiple times. For 2-3 email mini-launches drop to 20-25%. Second, the 1.4 / 1.0 / 0.65 stack breaks down at extreme spreads — if your low tier is $97 and your high tier is $4,997, real-world elasticity is steeper than the calc models. Adjust expected conversion rates manually in that case.

Worked Example — Default Inputs

Plug in the calculator’s defaults: 5,000 reachable audience, 35% launch open rate, 2% baseline CR, tier prices $297 / $497 / $997, 8% refund rate, $8,000 production cost. Launch clicks = 5,000 × 0.35 × 0.35 = 613 clicks. Mid-tier sales = 613 × 2% = 12 sales × $497 = $6,089 gross × 0.92 = $5,602 net — profit $-2,398 (production cost not recovered). Low tier: 17 sales × $297 = $5,065 gross, profit $-3,341. High tier: 8 sales × $997 = $7,953 gross × 0.92 = $7,317 net, profit $-683. Max-revenue tier is high ($7,953); max- profit tier is also high (least bad at $-683). The verdict: 5K audience is too small to clear $8K production at any tier — the math doesn’t close.

The defaults surface a typical first-launch reality: most creators size their first course production budget against optimistic conversion projections, then the math fails on real audience scale. The fix is one of three levers: cut production cost (lighter production, fewer modules, $2-3K instead of $8K), grow audience 2-3× before launch (move launch back 6 months), or push the high tier higher with cohort + 1-on-1 to lift CR above the 0.65× baseline. Most creators try to fix conversion rate first — that rarely moves the needle as much as the other two levers.

The Tiers — What Lifts Each

Low tier ($97-$297 typical.)Converts at ~1.4× baseline because price scrutiny is light and the buy-now decision is fast. Best for top-of- funnel lead magnets, “intro to” courses, or audience-warming products. Lift moves: bundle a bonus mini-course or community trial to raise perceived value without raising price; add a payment plan ($97 × 3 = $291 feels easier than $297 lump); set as the “starter” relative to your mid tier for decoy-effect anchoring. Don’t skip low tier thinking “premium positioning” — the three-tier ladder converts mid better than single- price, and low tier funds the case-study volume.

Mid tier ($297-$997 typical.)Baseline conversion rate — this is the sweet spot for most solo-creator courses. Mid tier carries the bulk of revenue at standard 25 / 60 / 15 distribution. Lift moves: feature differentiation (mid includes everything low has plus 1-2 must-haves like community access or weekly Q&A); cohort framing (live calls + accountability lifts mid CR 20-40% without changing price); positioning relative to high tier as “the most popular choice” with a checkmark or callout. Most courses under-monetize mid by setting it too close to low — spread should be 1.5-2× for proper anchoring.

High tier ($997-$4,997 typical.)Converts at ~0.65× baseline due to price scrutiny. Smaller volume but higher revenue per buyer + frequently higher blended profit. Best when bundled with 1-on-1 founder access, cohort enrollment, dedicated support, or mastermind-style group calls. Lift moves: scarcity (cohort-based with 50 seats vs unlimited self-paced compresses decision time and lifts premium CR 30-50%); outcome-specific case studies (“made $12K in 60 days” doubles premium CR vs faceless logos); founder-direct positioning (“30-min onboarding call with me” justifies a $300-500 premium for high-trust buyers).

Production cost & break-even.The forgotten line item. Most creators undercount by 30-50% by skipping their own time at honest hourly rate. Real production cost = hard costs (recording, editing, platform fees, ~$1.5-3K) + marketing (paid ads, sponsorships, ~$3-15K for first launch) + your time at honest rate (80-150 hrs × $80-150/hr = $6.4-22.5K). Break-even sales count is dramatically lower at the high tier — recovering an $8K production at $997 needs 9 sales vs 27 at $297. Pricing-up is often the fastest path to a closing launch when audience is small.

Common Mistakes

Optimizing for max revenue instead of max profit.Selling 100 units at $297 produces $29.7K revenue — sounds great until you net out $20K production and $2K refunds, leaving $7.7K profit. Selling 30 units at $997 at the same production produces $29.9K revenue and $9.9K profit with way less fulfillment burden. Calculator surfaces both numbers explicitly because they often disagree. Pick max-profit unless you’re specifically building case-study volume early-stage.

Counting dashboard subs as reachable audience. The dashboard headline includes inactives, unconfirmed, and bounced addresses — deliverable list size is typically 70-90% for newsletters older than 12 months. Use the deliverable count from your ESP’s send- list view, not the total-subscribers number. Most creators overstate reachable audience by 20-40% and the launch math reflects that.

Optimistic conversion rate projections. Plugging 5-10% baseline CR when your last-30-day actual is 1.5%. The calc’s output is only as honest as the input — use last-launch actuals from your analytics, not aspirational targets pulled from a course-creator influencer’s case study (which is survivorship-biased almost by definition).

Skipping production cost from your time. “I’d be writing anyway, my time is free.” Almost never true. Most creators have higher-value alternatives (freelance, side projects, family time) they aren’t honest about. Plug your true hourly rate from the True Hourly Rate calculator — the math shifts dramatically when you cost-in 80-150 launch hours at $80-150/hr.

Ignoring refund rate variance.Industry median is 5-12% for self-paced courses, but cold-launched broad-appeal courses (Facebook ads → cold traffic → checkout) commonly see 10-20%. Above 15% sustained is a positioning / promised-outcome / fulfillment- quality flag — not a math problem to absorb but a product-quality problem to fix. Lifting fulfillment quality (welcome video + first-week wins + clear roadmap) often pulls refund rate 3-5pp lower at no cost to production.

Related Calculators

Run after this calc, layer in psychological lift via the Pricing Psychology Calculator — anchoring choice, charm pricing ($X9 endings), and payment plans typically add 15-40% additional CR on top of tier choice. If your product is recurring- revenue (membership, SaaS, paid newsletter) instead of one-time, switch to the SaaS Pricing Tier Calculator — different math (LTV/CAC ratio + payback period vs launch revenue + break-even sales). If course launches feed off your newsletter, the Newsletter ROI Calculator surfaces the funnel economics that drive launch click volume in the first place — profitable course math fails when newsletter math is broken upstream. And if your reachable audience is too small for the tier math to close, the Audience Capture Time Calculator shows how many months of cadence + content quality you need to reach a monetizable scale before launching.

How to Read the Verdict

Two answers, almost never the same: the max-revenue tier (gross sales) and the max-profit tier(after refunds and production cost). Pick max-profit unless you’re launching for marketing, social proof, or list-building reasons.

Max-profit tier is the high price. Launch at high. Premium positioning is its own funnel filter — the buyers who can pay are usually the ones who finish and refer.
Max-profit tier is the mid price AND refund rate < 10%. Launch at mid. Highest-volume tier with enough margin to sustain content updates and support.
Max-revenue and max-profit disagree by > 30%. You’re looking at a list-building loss-leader vs a profit-engine. Decide intent before pricing — both are valid, but the strategy follows.
Break-even sales count > 25% of audience. Conversion math is brutal at this scale. Either widen the audience first (run growth for 3-6 months), or drop tier prices to fit your actual reach.

Frequently Asked Questions

The most common questions we get about this calculator — each answer is kept under 60 words so you can scan.

What's a typical refund rate for online courses?
Industry typical is 5-12% for self-paced online courses. Cohort-based courses (live, scheduled, accountability-driven) often see <5% — the higher engagement reduces buyer's remorse. Cold-launched broad-appeal courses (Facebook ads → cold traffic → checkout) commonly see 10-20% because of higher impulse-buy refunds. Above 15% sustained is a flag — typically signals positioning / promised-outcome / fulfillment-quality mismatch. Lifting onboarding quality (welcome video + first-week wins + clear roadmap) often pulls refund rate 3-5pp lower.
How does conversion rate scale with price?
The calculator applies a price-aware adjustment: low tier ×1.4 (more accessible, less price scrutiny), mid ×1.0 (baseline), high ×0.65 (premium pricing reduces conversion). Real-world variance is wider — cold audiences hit closer to ×0.4 at premium tiers, while loyal audiences sometimes match or exceed mid CR even at premium. Use the calculator as a planning starting point and compare against your last-launch actuals if you have them.
Should I optimize for max revenue or max profit?
Max profit, almost always. Max revenue is a vanity number — selling 100 units at $297 produces $29.7K revenue, but if production cost is $20K that's only $9.7K profit. Selling 30 units at $997 produces $29.9K revenue at the same production cost = $9.9K profit, but with way less fulfillment burden. The calculator separates these explicitly because they often disagree, and the right move depends on your business goal. Pure-revenue optimization makes sense when you're early-stage building case studies; once you're past that, profit is the right number.
What's the 35% launch CTR coefficient?
Cumulative click-through rate across a 5-7 email launch sequence — well above per-send CTR (typically 2-4%) because the same audience sees the same offer multiple times. The math: per-send CTR averages 5-8% across the launch, and most active subscribers click at least once across the sequence. The 35% coefficient is conservative-defensible across the creator-economy launch playbook (Jeff Walker / Amy Porterfield style). For shorter 2-3 email launches, drop to 20-25%.
How do I size production cost honestly?
Three buckets. (1) Hard costs: video production (camera + editing), course platform fees (Teachable, Podia, Kajabi typically $99-299/mo), email/automation, asset design. Typical solo creator: $1,500-3,000. (2) Marketing: paid ads (Meta + Google during launch window), sponsorships, affiliate fees. Typical: $3,000-15,000 for first launch, less for repeat. (3) Your time at honest hourly rate: 80-150 hours total at $80-150/hr = $6,400-22,500. Most creators skip bucket 3 and dramatically understate true production cost. Use the true-hourly-rate-calculator to set bucket 3 honestly.
Why does the calc fix multipliers at 1.4 / 1.0 / 0.65?
The multipliers are sourced from creator-economy launch data (Convertkit, Podia, Teachable aggregate stats) showing that doubling price typically halves conversion in the cold→warm audience zone. The 1.4 / 1.0 / 0.65 stack approximates that elasticity at the typical tier spreads ($297-$497-$997 range). For very-different price spreads (e.g., $97 vs $4,997), the multipliers are too coarse — adjust expected conversion rates manually on the input side instead.
What about pricing psychology (charm + anchoring + payment plans)?
This calculator handles the unit economics; the pricing-psychology-calculator handles the conversion-lift side (charm pricing $X9, anchoring tier strikethroughs, payment plans). Stack them: this calc tells you the tier-revenue math; the psychology calc tells you the additional CR lift from psychological levers on top. Combined, you get the full picture — tier choice + presentation impact.
Three-tier vs single-price launch?
Three-tier almost always outperforms single-price for courses above $200. Reasons: (1) decoy effect — premium tier makes mid look like value, lifting mid-tier CR 10-20%. (2) anchoring — buyers compare across tiers, settling on the one that matches their commitment level. (3) revenue capture — high-LTV buyers self-select up. Single-price launches under $100 work fine because the price-resistance ceiling is low. Above $200, three-tier is the standard playbook.
What if my audience is < 1,000 subs?
The calc still works but treat output as planning-rough. Below 1K reachable audience, launch math is dominated by individual-conversion variance — one big customer can swing the numbers more than tier choice. For sub-1K audiences, focus on (a) higher-priced premium tier (smaller volume × higher per-unit), (b) waitlist + presell to validate demand before production, (c) cohort format with $1K+ pricing to compress sales. Skip the three-tier playbook until you're past 2K reachable.
Are launch math projections reliable?
Within ±30% if your inputs are honest. Reachable audience is the trickiest — most creators count their dashboard subscriber number rather than the deliverable / active list, overcounting 20-40%. Open rate during launches is usually 5-10pp lower than baseline (launch fatigue), and creators forget that. CR varies wildly by audience temperature. Use last-launch actuals if you have them; otherwise treat projections as a planning floor and budget conservatively.
How do I lift conversion at the premium tier?
Three high-leverage moves. (1) Add scarcity: cohort-based with limited seats (50 spots vs unlimited self-paced) compresses decision time and lifts premium CR 30-50%. (2) Add 1-on-1 component: even one 30-min onboarding call with you justifies $300-500 premium for high-trust buyers. (3) Add testimonial-density: case studies with concrete outcome metrics ("made $12K in 60 days") double-digit lift premium CR more than any other input. Generic logos / faceless testimonials don't move the needle.
What's the difference between this and the SaaS pricing tier calc?
Course pricing optimizer: one-time product launch math. Inputs are launch-specific (audience reach + open rate + tier prices + refund + production cost). Output is total launch revenue + profit. SaaS pricing tier: subscription-recurring math. Inputs are CAC + ACV + churn + LTV multiplier. Output is LTV/CAC ratio + payback period. Different math, different decision frame — use this for course/cohort/info-product launches; use SaaS calc for recurring-revenue products.