Lexiloop

Business concept

A mobile-first vocabulary coach for GRE candidates who know flashcards but struggle to use difficult words in context. It diagnoses weak words, schedules retrieval practice, and turns each word into vetted sentence-equivalence and text-completion drills.

Problem and opportunity

• Candidates memorize definitions but miss nuance in exam-style sentences.
• Generic decks repeat known words without proving contextual recall.
• Motivation fades before enough spaced reviews accumulate.

Solution

• Diagnose word-level weaknesses.
• Schedule expert-vetted contextual drills.
• Show delayed recall and mastery progress.

Business model

• $39 eight-week exam pass.
• $12 monthly pricing test.
• Tutor licenses after consumer validation.

Market opportunity

206,004 people took the GRE General Test in 2024–25; this is an audience ceiling, not proof of demand.

Key objectives

• 0–3 months — interviews and paid concierge pilot.
• 3–6 months — validate learning and retention.
• 6–12 months — automate the proven workflow.

Funding requirements

Maximum $15,000 until paid demand, learning lift, retention, and acquisition economics clear the stated gates.

Company description

The company develops focused learning software and original practice content for high-stakes verbal reasoning exams, starting with GRE vocabulary.

Mission and vision

Become the trusted adaptive practice layer for high-stakes verbal reasoning.

Business structure

Proposed US software company; entity type, jurisdiction, ownership, and founder agreements remain legal decisions before accepting capital.

Core problem

• Candidates memorize definitions but miss nuance in exam-style sentences.
• Generic decks repeat known words without proving contextual recall.
• Motivation fades before enough spaced reviews accumulate.

Current alternatives

• Static vocabulary lists and flashcard apps
• Full GRE preparation courses
• Tutors and self-authored study notes

Customer impact

Candidates spend scarce preparation time reviewing known words without evidence that recall transfers to unfamiliar sentence contexts.

Evidence of the problem

The pain is a founder hypothesis. Validate it through interviews, paid pre-sales, baseline tests, and delayed-recall results before treating it as established.

Offering overview

• Free diagnostic.
• Adaptive daily queue.
• Reviewed explanations and mastery reporting.

Customer experience

• Take a focused diagnostic.
• Identify weak word families.
• Build the daily review queue.
• Practice in GRE-style contexts.
• Check delayed recall.
• Adapt the next session.

Key features

• Diagnose word-level weaknesses.
• Schedule expert-vetted contextual drills.
• Show delayed recall and mastery progress.

Customer benefits

• Less time spent on mastered vocabulary
• Practice that resembles the contextual decisions required on test day
• Visible delayed-recall progress

Differentiation

• Validated contextual transfer.
• Expert-reviewed question quality.
• Outcome-linked word-by-context data.

Development status

Pre-launch concept; no production product or paid traction is claimed.

Product roadmap

• 0–3 months — interviews and paid concierge pilot.
• 3–6 months — validate learning and retention.
• 6–12 months — automate the proven workflow.

Market definition

Paid digital contextual-vocabulary practice for GRE candidates, initially in English-speaking and internationally addressable online markets.

Target market

• Mobile-first GRE candidates with 6–12 weeks until test day.
• Tutors seeking measurable contextual-vocabulary practice.

Market size

TAM, SAM, and SOM below are planning models anchored to ETS examinee volume, not third-party market forecasts.

Market growth

ETS examinee volume declined from 366,686 in 2020–21 to 206,004 in 2024–25; the plan assumes no category growth.

Industry trends

• GRE volume has contracted across the five-year ETS series.
• At-home testing and year-round availability make digital acquisition and delivery feasible.
• Generative AI lowers content-production cost but raises quality-control and trust risk.

Why now

Mobile study behavior and constrained content-generation workflows make personalized practice feasible, while question quality remains a meaningful differentiator.

Primary customer

Time-pressed GRE candidate: needs measurable progress within a six-to-twelve-week test window.

Customer needs

• Reach a target verbal score.
• Build durable recall in short sessions.
• Transfer vocabulary to exam-style questions.

Buying behavior

Likely research-led and deadline-driven; test with observed funnel behavior rather than interviews alone.

Purchase triggers

• A weak diagnostic result
• An approaching test date
• A recommendation from a tutor or trusted GRE creator

Willingness to pay

$39 eight-week access and $12 monthly are pricing hypotheses requiring paid tests.

Buyer and user

The candidate is the initial buyer and user; tutors may later become cohort buyers and assignment users.

Direct competitors

Magoosh Vocabulary Builder and other GRE-specific preparation products. See linked resources and the comparison matrix below.

Indirect competitors

Quizlet, Anki, tutors, books, spreadsheets, and free word lists.

Competitive positioning

A daily coach that converts weak GRE vocabulary into contextual recall before test day—not another static word list.

Competitive advantages

• Validated contextual transfer.
• Expert-reviewed question quality.
• Outcome-linked word-by-context data.

Defensibility

A word-by-context error graph can become defensible after repeated learner outcomes produce proprietary data.

Competitive risks

• Incumbents can copy surface-level adaptive features.
• Free alternatives cap price and raise the proof threshold.
• Unreliable generated questions would rapidly erode trust.

Revenue model

• $39 eight-week exam pass or $12 monthly access.
• Tutor cohort licenses after consumer validation.

Pricing strategy

$39 for eight weeks tests deadline-aligned value; $12/month tests flexibility. Neither price is validated.

Revenue drivers

• Paid learners
• Diagnostic-to-paid conversion
• Retention and renewals
• Tutor cohort seats

Unit economics

Base-case modeling uses $39 per pass, 3% payment processing plus $0.30, $4 learner-variable content/support cost, and paid acquisition capped at $12.

Cost structure

• Expert content review.
• Product engineering and model usage.
• Creator production and acquisition experiments.

Margin potential

Modeled pre-acquisition contribution is $33.53 per $39 pass (86%); actual support, refunds, review, and acquisition costs must be measured.

Market entry strategy

Start with a paid, manually supported cohort to validate outcomes before automating.

Customer acquisition

• Recruit the first 100 through GRE communities and tutors.
• Scale searchable challenges and tracked creator referrals.
• Add tutor cohorts after consumer retention is proven.

Marketing channels

• Short-form contextual vocabulary lessons.
• GRE communities and tutor partnerships.
• Search pages for commonly confused words.

Sales strategy

Free diagnostic → personalized result → time-limited paid pass; tutor outreach follows consumer proof.

Customer retention

Daily ten-minute queue, mastery visibility, delayed recall, and test-date pacing.

Expansion strategy

Tutor cohorts first; adjacent verbal-reasoning exams only after the GRE loop reaches retention and margin gates.

Operating model

Remote-first software and content operation with a human editorial gate for scored practice.

Product or service delivery

Responsive web app, automated scheduling, payments, analytics, support, and versioned question review.

Suppliers and partners

• Payment processor
• Cloud and model providers
• GRE verbal editors
• Tutor and creator partners

Technology and systems

• Content management and review workflow
• Learner event and mastery store
• Experimentation and analytics
• Support and billing

Facilities and physical assets

No dedicated facility assumed; company laptops and secure cloud services only.

Staffing requirements

• Learning-science and product lead.
• GRE verbal editor.
• Product engineer.
• Content distribution lead.

Scalability

Software delivery scales, but editorial throughput and support quality are constraints to instrument before growth.

Technology overview

A diagnostic and spaced-practice engine selects contextual items from a reviewed content bank and updates word-by-context mastery.

Proprietary assets

• Reviewed item bank
• Learner outcome data
• Word-by-context error graph
• Editorial quality rubric

Intellectual property

Protect original content and software through copyright, contracts, access controls, and trademarks where warranted; no patent claim is assumed.

Technology roadmap

• 0–3 months — interviews and paid concierge pilot.
• 3–6 months — validate learning and retention.
• 6–12 months — automate the proven workflow.

Technical risks

• Cold-start recommendations
• Ambiguous generated questions
• Model/provider dependency
• Sensitive learner-data handling

Roles and responsibilities needed

• Product/learning lead — owns outcomes and roadmap
• GRE verbal editor — accountable for item quality
• Engineer — owns platform reliability and data
• Growth lead — owns acquisition experiments
• Advisor/counsel — consulted on privacy claims and contracts

Financial assumptions

Pass price $39; paid learners 500 / 2,500 / 8,000; variable cost $5.47 per pass; one employee in Year 1 and two in Years 2–3 at Ontario’s $17.95 minimum wage and 2,080 hours annually.

Revenue forecast

$19,500 / $97,500 / $312,000 for years 1–3.

Expense forecast

$72,071 / $153,347 / $258,432 including variable costs.

Profitability

Modeled net result: −$52,571 / −$55,847 / $53,568.

Cash flow

Requires staged funding through Year 2 before modeled Year 3 profitability.

Break-even analysis

At a $33.53 contribution per pass, Year 2 fixed cost of $139,672 requires about 4,166 paid passes.

Scenario analysis

Year-two downside/base/upside cases are shown below.

Capital required

$15,000 validation cap; further capital is conditional.

Use of funds

• 40% prototype engineering
• 30% expert content review
• 20% acquisition experiments
• 10% legal privacy and contingency

Runway

Approximately three months of scoped validation work; not company-wide runway.

Funding milestones

• 20 paid founding passes
• Measured delayed-recall lift
• Week-four retention threshold set before launch
• One channel with positive contribution margin

Future capital needs

Budget only after observed retention, quality, support, and acquisition costs support a revised model.

Market risks

Declining GRE volume → keep fixed cost low and validate adjacent demand only after the wedge works.

Competitive risks

Free/incumbent alternatives → compete on measured transfer and reviewed quality.

Product risks

Low learning lift → preregister the pilot metric and stop if it misses the threshold.

Operational risks

Editorial bottlenecks → use rubrics, sampling, and reviewer agreement checks.

Financial risks

CAC exceeds contribution → cap channel experiments and pause unprofitable spend.

Regulatory risks

Privacy, marketing claims, and content rights → minimize data and obtain specialist review before scale.

Mitigation strategy

Use staged gates, small spending caps, audit trails, and explicit stop criteria.

Product milestones

• 0–3 months — interviews and paid concierge pilot.
• 3–6 months — validate learning and retention.
• 6–12 months — automate the proven workflow.

Timeline

Weeks 1–4: interviews and pre-sales; weeks 5–8: concierge pilot; weeks 9–12: retention/outcome review and go/no-go.

Growth strategy

• Turn reviewed contexts into reusable lessons and acquisition content.
• Use outcome data to improve diagnosis.
• Expand only after the GRE learning loop works.

Product expansion

Expand from GRE vocabulary to contextual verbal reasoning only after validated learning outcomes.

Market expansion

Tutor cohorts, then carefully selected adjacent admissions tests and professional English use cases.

Competitive moat

Compound reviewed content with longitudinal error and outcome data while maintaining editorial trust.

Long-term economics

Reusable content and software may improve margin, but human review, support, and acquisition remain durable costs.

Long-term vision

Become the trusted adaptive practice layer for high-stakes verbal reasoning.