---
title: Setting your first subscription price
slug: setting-initial-subscription-price
summary: Start higher than feels comfortable — Ravi Mehta's $20–30/month "high waterline" doubles as a PMF test — then anchor on competitors, cost-plus-perceived-value (AI apps), ROAS/payback math and the value of the user's whole problem; text-AI wrappers cluster at $30–40/year, niche custom-prompt chat apps get $20+/month.
domain: mobile-apps
tags: [monetization, pricing, product-market-fit, ai-apps]
related: [paywall-test-velocity-and-arpu-margin, differentiating-in-saturated-app-categories, freemium-vs-hard-paywall-free-tier, subscription-price-increase, tiered-pricing-and-consumables, weekly-vs-yearly-plans-and-trial-placement, paywall-price-display-and-plan-count, app-break-even-cpi-and-revenue-per-install, indie-pricing-one-time-vs-subscription]
sources: [yt:AWI3rofh0BA, yt:24QMRDXck70, yt:lkwX_kc0NS8, yt:-5zgc14t2gc, yt:OxE79rpGioI, yt:s8Rped5LuWw, yt:_KilixPWX-c]
updated: 2026-10-24
---

# Setting your first subscription price

## TL;DR
- **Founders under-monetise.** Someone using your app is already highly motivated; start with a "high waterline" (e.g. $20–30/month where the market frames that price) and optimise down/around it.
- If **nobody pays at a market-framed price, you have a PMF problem**, not a pricing problem — paying is the most revealing PMF signal.
- Price against the **value of the whole system** the user is in: Tinder whales spending $100+/month saw it as cheap vs $400 for a couple of dates.
- Practical inputs (Vahe Bagdasarian): competitors' prices; a ROAS-positive / ~1-month-payback price from your CAC; for AI apps, per-user cost + perceived-value margin; optional Van Westendorp survey later.
- Market anchors (Jonathan Parra, early 2026): **text-AI wrapper apps ~$29.99–40/year**; image/video AI higher; niche custom-prompt chat apps charge **$20–22/month**.
- Non-round prices can feel more honest: $3.33/month (≈ $40/yr) reads as "$3" yet earns more than $2.99.
- **Jake Castillo's quick rule (Cal AI):** benchmark competitors, then go ~20% cheaper to undercut, ~20% higher for a prestige position, or match — and start testing. Broad mass-market app → price low; narrow niche (small TAM, "this is for me") → charge more.[^18][^19]

## Details
**High waterline.** Ravi Mehta argues users have endless alternatives, so if they're in your app they're motivated and have willingness to pay; set the first tier high ($20–30/month framing), not a system of $1 items that needs extreme engagement for decent ARPU. If no one will pay that where the market already frames such prices, work on PMF.[^1][^2] Jacob Eiting adds: pricing in the market at a competitive rate is the best way to measure PMF; early founders often think "it's not worth that much yet".[^3]

**Price the system, not the feature.** Tinder found Platinum-type users rationalised $100–200/month because dates cost ~$400; think about the value of the system around the need, not "$20 because everyone charges $20".[^4] Under-priced examples cited: Granola (Ravi uses it daily, never paid — vs Wispr Flow's paid trial), Riverside (~$100–200/month vs RevenueCat's ~$100 mics per guest).[^5][^6] Scanner apps make real money by layering workflow value (storage, OCR, sharing) on a commodity scan — Adobe's scanner app ~$6.3M/month per David Barnard.[^7]

**Vahe's methods.** (1) Copy competitor price points (most common); (2) if running paid UA, compute the price that keeps you ROAS-positive or pays back within about a month at current conversion; (3) for compute-heavy AI products, estimate annual cost per user (e.g. $20) and add perceived value (e.g. to $40/year); (4) price-sensitivity surveys are optional when starting. Then run price tests.[^8][^9][^10]

**AI app anchors.** Parra: $30–40/year is standard for text-inference AI wrappers; $29.99/year became the copied market price that's still profitable. Image/video generation costs more, so prices are higher.[^11][^12] A niche chat app billing $20–22/month works because its prompt and flow are tailored to one problem — users pay for the "custom prompt" and not having to build it; apps targeting an insecurity (looksmaxxing, dating-reply apps) can charge most.[^13][^14]

**Charm pricing.** Vahe: $14.99 usually beats $15 in A/B tests, but consumers increasingly see .99 as a trick; an odd number like $3.33 feels authentic. Joseph Choi's math: $3.33/month ×12 = ~$40/year vs $36 at $2.99 — $4 more per user to spend on ads.[^15][^16]

**Cheap for mindshare vs niche premium ([[people/jake-castillo]], Sep 2026).** Cal AI priced below every competitor on purpose: the calorie-tracking TAM was enormous, the goal was mindshare, the audience was young and "chronically online" with little disposable income, and being the cheaper equal let it convert other apps' users. A general app "talking to everyone" should make sure price is never the reason someone hesitates; a niche app (his example: a workout planner for new moms) can and must charge more.[^18][^20] The starting price is only a starting point — keep running paywall tests ([[paywall-test-velocity-and-arpu-margin]]).[^19]

**Category benchmark as a first stab.** Gleam ([[people/kelvin-zhang]]) copied a 7-day trial from other apps and priced around **$69.99/year** from education-app benchmarks, which proved a good initial price.[^21]

**Don't freeze copied prices (2022).** [[people/dan-burcaw]] warns that many apps copy their competitive set's prices and never change them for years; competitors' choices aren't proof of an optimum.[^22]

**Start simple.** BoldVoice launched with just ~$10/month + 7-day trial to keep focus on product; today it leads with ~$150/year.[^17]

## Disagreements / caveats
- Ravi's $20–30 waterline suits high-value problems (dating, health, careers); Parra's AI-wrapper anchors are ~$3/month — category and perceived value dominate.
- Jake's "go cheap" and Ravi's "high waterline" conflict; Jake ties it to TAM and demographic (young, broad audience), Ravi to high-value problems. Cal AI also had creator-driven reach that low price amplified.
- Apple shows the billed amount most prominently; odd monthly breakdowns are secondary display ([[paywall-price-display-and-plan-count]]).

## See also
- [[subscription-price-increase]]
- [[tiered-pricing-and-consumables]]
- [[app-break-even-cpi-and-revenue-per-install]]

[^1]: yt:AWI3rofh0BA @ 22:06 — Ravi Mehta
[^2]: yt:AWI3rofh0BA @ 23:31 — Ravi Mehta
[^3]: yt:AWI3rofh0BA @ 26:24 — Jacob Eiting
[^4]: yt:AWI3rofh0BA @ 26:24 — Ravi Mehta
[^5]: yt:AWI3rofh0BA @ 23:31 — Ravi Mehta, David Barnard
[^6]: yt:AWI3rofh0BA @ 25:04 — Jacob Eiting
[^7]: yt:AWI3rofh0BA @ 27:59 — David Barnard
[^8]: yt:24QMRDXck70 @ 36:47 — Vahe Bagdasarian
[^9]: yt:24QMRDXck70 @ 37:38 — Vahe Bagdasarian
[^10]: yt:24QMRDXck70 @ 38:28 — Vahe Bagdasarian
[^11]: yt:lkwX_kc0NS8 @ 14:32 — Jonathan Parra
[^12]: yt:lkwX_kc0NS8 @ 20:39 — Jonathan Parra
[^13]: yt:lkwX_kc0NS8 @ 22:13 — Jonathan Parra
[^14]: yt:lkwX_kc0NS8 @ 23:23 — Jonathan Parra
[^15]: yt:24QMRDXck70 @ 30:37 — Vahe Bagdasarian
[^16]: yt:24QMRDXck70 @ 31:49 — Joseph Choi
[^17]: yt:-5zgc14t2gc @ 14:35 — Anada Lakra
[^18]: yt:OxE79rpGioI @ 36:41 — Jake Castillo
[^19]: yt:OxE79rpGioI @ 38:42 — Jake Castillo
[^20]: yt:OxE79rpGioI @ 37:49 — Jake Castillo
[^21]: yt:s8Rped5LuWw @ 33:34 — Kelvin Zhang
[^22]: yt:_KilixPWX-c @ 30:42 — Dan Burcaw