WorkNet Career Translation Lens

4.30

Derivation Chain

Step 1 Experience-based re-employment matching

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Step 2 Translating hands-on experience into job keywords

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Step 3 Problem of getting zero or irrelevant results when searching WorkNet/Saramin with translated keywords

Problem

Corporate retirees aged 52-58 who search WorkNet (Korea's public job portal) with '25 years in sales management' only get results like 'Sales rep wanted (no experience required)' — a clear downgrade. Their actual competencies — key account relationship management, revenue forecasting, channel strategy — need to be translated into market-relevant job keywords, but they've never structured their careers this way and don't know which keywords resonate in today's job market. They waste 2-3 weeks on average and suffer declining self-confidence.

Solution

Users enter their job title, responsibilities, and achievements as free text, and the platform automatically translates them into 5-10 job keywords currently used in the Recruitment market. For each translated keyword, it crawls WorkNet and Saramin (Korea's leading job portal) to show actual job posting counts and average salary ranges, plus provides sentence templates like 'Here's how to put this keyword in your resume.'

Target: Ages 50-58, within 1 year of leaving large or mid-sized corporations, white-collar professionals motivated to find re-employment but stuck on resume writing

Revenue Model: Keyword translation Free for up to 3 uses. Detailed Report with resume sentence templates at 9,900 KRW (~$7.50) Per Transaction. Monthly Subscription (unlimited translations + job alert notifications) at 19,900 KRW (~$15).

Ecosystem Role: Infrastructure

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

4.0/5

U Urgency

4.0/5

M Market

4.0/5

R Realizability

5.0/5

V Validation

4.0/5

NUMR-V Scoring System

N Novelty	1-5	How uncommon the service is in market context.
U Urgency	1-5	How urgently users need this problem solved now.
M Market	1-5	Market size and growth potential from proxy indicators.
R Realizability	1-5	Buildability for a small team with realistic constraints.
V Validation	1-5	Validation signal quality from competition and demand data.

SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (70%)

Tech Complexity

29.3/40

Data Availability

20.8/25

MVP Timeline

20.0/20

API Bonus

0.0/15

Feasibility Breakdown

Tech Complexity	/ 40	Difficulty of core implementation stack.
Data Availability	/ 25	Practical availability and cost of required data.
MVP Timeline	/ 20	Expected time to ship a usable MVP.
API Bonus	/ 15	Bonus for viable public API leverage.

Market Validation (59/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

14.0/20

Revenue Signals

10.5/15

Pick-Axe Fit

10.5/15

Solo Buildability

10.0/10

Validation Breakdown

Competition	/ 20	Signal quality from competitor landscape.
Market Demand	/ 20	Demand proxies from search and mention patterns.
Timing	/ 20	Fit with current shifts in tech, behavior, and regulation.
Revenue Signals	/ 15	Reference evidence for monetization viability.
Pick-Axe Fit	/ 15	How well the concept serves participants in a trend.
Solo Buildability	/ 10	Practicality for lean-team implementation.

Technical Requirements

Frontend [low] Backend [medium] Data Pipeline [medium]

Dashboard