Opportunities › Progressive vocabulary building for language learners › Proposed app
Stairword
Vocabulary lessons that build on every word you already know
- Score
- 32
- confidence 27
- Evidence
- 2
- items on the page
- Rivals
- 2
- named in sources
- First version
- 40 d
- estimate
- Type
- Mobile app
- PWA: installs on iPhone and Android
- Market since
- 2011
- Mature market · AI estimate
ScreensConcept
Mobile app: Language learners engage with short vocabulary lessons on the go, review their word map, and reinforce learning in casual, bite-sized sessions. Sample screens on a phone, in the proposed brand. Their numbers are sample data.
Lesson 42
6 new
- Known words used31
- New words6
- Builds onLessons 38-41
- Exercises12
- Estimated time8 min
About this appAI proposal
Stairword teaches vocabulary as a staircase. Every lesson is made only from words you have already learned plus a few new ones, so each step rests on the one before. It starts with the simplest characters and builds from there.
It is for self-directed learners on their phones, especially those learning Chinese or another language with a large character set, who feel other apps repeat what they know or jump between unrelated topics.
A personal word map shows what you know, what comes next and why. Review draws on your known words, so new material reinforces the old. Lessons work offline.
- Tagline
- Every new word stands on one you already know.
- Voice
- ClearCalmMethodical
- Why this name
- Stair for steps, word for the thing learned. It says each step rests on the one below, in two plain words.
In the first version
Members say which features they would use. It tells PWAS what people want; it changes no score.
Strict word-by-word progression
Each lesson uses only words you have learned plus a small set of new ones, so nothing arrives without a foundation.
No member yet
Personal word map
See every word and character you know, and which new words they unlock next.
No member yet
Reinforcing review
Review sentences are built from your known words, so old material returns inside new context.
No member yet
Skip what you know
A quick placement check marks words you already know so you do not repeat them.
No member yet
Brand identityAI proposal
Check the name against trademark registers before using it.
Palette
#14524FInk Teal · primary#FAF6ECRice Paper · surface#1F2623Charcoal · text#E4572EPersimmon · accent#7FA37AMoss · data
Typography
Aa
Stairword
ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
Every new word stands on one you already know.
PricingAI proposal
The material gives no competitor prices. These tiers follow the freemium idea in the opportunity and are a starting point to test.
Free
Free
- First units of the curriculum
- Word map
- Daily review
Full
$9 a month
- Complete curriculum
- Offline lessons
- Placement check
- Unlimited review
Full yearly
$69 a year
- Everything in Full
- Save compared with monthly
Would you pay Full yearly · $69 a year?
Your answer tells PWAS which prices people accept. It changes no score.
No answers yet.
What it could be worthEstimate
What a software business making this much sells for today, from real deals. Pick a monthly revenue.
If it makes
Worth about
$194,000
Sale range $132,000 to $263,000
$120,000 a year in revenue
From 87 software businesses listed and sold on Empire Flippers in the last year, revenue vetted by the broker: they sell for about 19× their monthly revenue, most between 13× and 26×.
Measured on profit, the middle deal is 32× monthly net profit: about 2.7 years of profit.
An estimate, not an offer or financial advice. A real price depends on profit, growth, churn, how much of the work is the owner's, and the buyer.
How it would growAI proposal
How the product would reach new customers through its own use, and how the first ones would be found. A plan to test, not a result.
- Built-in loop
- No loop in the product. Learners study alone on their phones. Nothing the app makes is naturally sent to others, so it reaches new users through content, community posts and search.
- Do they become customers?
- Reach comes from learner communities and content. Test whether visitors who try the free units convert to paid, and whether progress screenshots prompt any sharing.
- First customers
- Adult self-taught beginners learning Mandarin on their phones who have tried a gamified app and want a stricter, cumulative sequence.
- Where to reach them
- Language learning communities: Share the approach and a free sample unit in Chinese-learning forums and subreddits, and ask for feedback.
- Short tutorials: Publish videos and posts showing how a word is built from known parts, linking to the free tier.
- First milestone
- Fifty learners finish the free units, and ten of them pay for the full curriculum within 60 days.
Why people already pay for this
- AI inferenceLanguage learners are switching from Duolingo to alternatives that build vocabulary progressively
- Public claimProgressive vocabulary building, where new material builds on previously learned content, is valued by learners
Tech stack
Every proposal builds on the same PWA base, installable from the browser on any phone or computer. Dashed boxes are what this app adds.
- AppNext.js and TypeScript
- PWAManifest and service worker
- UITailwind CSS
- Data and authSupabase Postgres
- PaymentsStripe
- EmailResend
- HostingVercel
- This app · Content engineWord dependency graph and lesson sequencerLessons must use only known words plus a few new ones, which needs a stored graph of words and their parts.
- This app · Spaced reviewOpen-source scheduling algorithmSchedules review of known words without building a scheduler from scratch.
RisksAI inference
- CommercialLarge incumbent apps are free and well known. Learners may not pay for a stricter sequence unless they feel the difference within the first lessons.
- DataA graded word list, sentences and audio must be written or licensed. Quality and rights of this content decide whether the progression holds.
- TechnicalGenerating natural sentences from only known words is hard. Early lessons may feel stilted or run out of material.
- AIIf AI helps write sentences, errors in meaning or tone could slip in and need native-speaker review.
Everything marked AI proposal or AI inference was written by a model from the evidence on the opportunity page. The proposed name must be checked against trademark registers before it is used.