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Job Title Normalizer for Career Levels
A SaaS tool that converts inconsistent job titles into comparable career levels using company size, function, team scope, compensation, and management responsibility. It helps candidates and recruiters understand whether a role is actually a step down, lateral move, or upgrade.
これが重要な理由
You are trying to make a career decision in a market where titles no longer mean the same thing from one employer to the next. A specialist title at one company may carry more responsibility and better pay than a manager title somewhere else, but your resume does not explain that automatically. You worry that future employers will judge the label instead of the actual scope. At the same time, you know compensation, flexibility, and brand quality may matter more than prestige. What you need is a way to translate titles into real level, so you can compare offers and explain your choices without guessing how others will interpret them.
- · Mid-career knowledge workers and recruiters, starting with marketers who are evaluating roles across different company sizes and title systems.向けに構築。
- · 最も可能性の高い収益化モデル: SaaS subscription。
痛み · ナラティブ
You are trying to make a career decision in a market where titles no longer mean the same thing from one employer to the next. A specialist title at one company may carry more responsibility and better pay than a manager title somewhere else, but your resume does not explain that automatically. You worry that future employers will judge the label instead of the actual scope. At the same time, you know compensation, flexibility, and brand quality may matter more than prestige. What you need is a way to translate titles into real level, so you can compare offers and explain your choices without guessing how others will interpret them.
スコア内訳
市場シグナル
市場投入
Laid-off or actively interviewing marketing managers and specialists comparing two or more offers from differently structured employers.
25,000-75,000 reachable English-speaking users annually in the initial niche through job-search communities and career newsletters.
LinkedIn organic content targeting job seekers and recruiters in marketing
$19/month
50 users upload roles and complete at least 100 title comparisons within 30 days, with 30% saying the output changed or clarified a decision
MVPの範囲 · 1～2週間
- Define a title ontology for marketing roles across startup, mid-market, and enterprise employers
- Build a simple intake form for title, compensation, team size, direct reports, and decision scope
- Create a rules-based mapping engine before adding AI interpretation
- Design a side-by-side comparison report showing normalized level and confidence score
- Recruit 15-20 test users from marketing job-search communities for feedback
- Add LLM-assisted parsing for resumes and pasted job descriptions
- Launch a web dashboard with saved comparisons and exportable summaries
- Implement confidence explanations showing why a role was mapped to a level
- Add a lightweight recruiter view for candidate title translation
- Run pricing tests with monthly and one-time plan options
差別化
失敗する可能性がある理由
自己反論 — 最も重要な信頼のシグナル
- 1The title mapping may be too ambiguous to earn trust without a proprietary dataset
- 2Users may only need the product briefly during active job transitions
- 3Free AI tools may satisfy enough of the demand unless the product offers stronger data credibility
エビデンスの概要
AIがこのインサイトをどのように統合したか — 逐語的な引用はありません
This was the most discussed theme by far, with roughly 30 mentions across the combined batches. Users repeatedly described titles as unreliable indicators of seniority, citing cases where lower labels came with more money, better employers, or stronger growth. The repeated confusion suggests a meaningful information gap that current job-search tools do not solve.
アクションプラン
コードを書く前に、この機会を検証しましょう
推奨する次のステップ
開発する
強い需要シグナルを検出。本物の課題と支払い意欲を確認 — MVPの開発を始めましょう。
ランディングページ文案キット
実際のRedditコメントから抽出したコピー、そのまま貼り付けられます
見出し
Job Title Normalizer for Career Levels
サブ見出し
A SaaS tool that converts inconsistent job titles into comparable career levels using company size, function, team scope, compensation, and management responsibility. It helps candidates and recruiters understand whether a role is actually a step down, lateral move, or upgrade.
ターゲットユーザー
対象：Mid-career knowledge workers and recruiters, starting with marketers who are evaluating roles across different company sizes and title systems.
機能リスト
✓ Title-to-level normalization engine ✓ Role scope intake using team size, ownership, budget, and reporting lines ✓ Compensation-adjusted level comparison ✓ Public profile wording suggestions ✓ Recruiter-facing candidate level reports
どこで検証するか
r/r/marketing にランディングページのリンクを投稿しましょう — そこがこの課題が発見された場所です。
同じテーマの他の機会
AIが関連する議論から自動クラスタリング