AIプロンプト: リード獲得

リードを見つけることが難しいのではなく、正しいリードを見つけることが難しいのです。これらのプロンプトは、ターゲットを絞った見込み客リストの構築、返信が来るアウトリーチの作成、無駄な時間を使う前のリード選別を手助けします。ChatGPT、Gemini、Claudeでテスト済みなので、見込み客開拓力を高めるモデルがわかります。

最終テスト日 Feb 15, 2026 · モデル: GPT-4o, Gemini 2.0, Claude 3.5 Sonnet, Grok 2

ICPビルダー

理想的な顧客プロファイルを定義する

Help me build an ideal customer profile for [product/service].

What I sell: [describe your offering]
Current best customers: [describe 3-5 of your most profitable/happiest customers]
Deal size: [average contract value]
Sales cycle: [how long deals typically take]
Channels that work: [where you currently find customers]

Build a comprehensive ICP:
1. Firmographic profile: industry, company size, revenue range, geography
2. Technographic profile: tools they use, tech maturity level
3. Trigger events: what happens in their business that creates buying urgency
4. Buyer personas: 2-3 decision-maker profiles with titles, goals, and frustrations
5. Disqualification criteria: red flags that signal a bad-fit prospect
6. A scoring rubric (1-10) to rank incoming leads against this ICP

プロのコツ

最も優れた3社の顧客にインタビューし、「購入する前の月に、ビジネスで何が起きていましたか?」と聞きましょう。トリガーイベントが本当のICPの金脈です。デモグラフィックは単なる最初のフィルターです。

テスト済み Feb 15, 2026

見込み客リサーチ

アウトリーチ前に見込み客をリサーチする

I'm about to reach out to [prospect name/company]. Help me prepare.

Their company: [name, industry, size if known]
Their role: [job title]
What I sell: [your product/service]
What I know so far: [any existing information]
My goal: [book a meeting / get a referral / start a conversation]

Research and prepare:
1. Key business challenges this type of company likely faces right now
2. Industry trends affecting their decision-making
3. 5 personalization angles I can use in my outreach
4. Potential internal priorities based on their role
5. Questions to ask that show I've done my homework
6. A pre-call one-pager I can review 5 minutes before reaching out

プロのコツ

通話前に見込み客のLinkedInアクティビティを確認しましょう。彼らがあなたの製品が解決する課題について投稿していたら、自然に言及しましょう。AIはフレームワークを提供しますが、リアルタイムのパーソナライズがギャップを埋めます。

テスト済み Feb 15, 2026

アウトリーチシーケンス

マルチタッチアウトリーチキャンペーンを構築する

Build a multi-touch outreach sequence for [target persona].

Product/service: [what you're offering]
Channel mix: [email, LinkedIn, phone, video — what you'll use]
Sequence length: [number of touches over how many days]
Value proposition: [main benefit]
Social proof: [case studies, numbers, logos]

Create the full sequence:
1. Touch 1: First email with subject line and body (under 100 words)
2. Touch 2: LinkedIn connection request with personalized note
3. Touch 3: Follow-up email with new value angle
4. Touch 4: Video message script (under 60 seconds)
5. Touch 5: Breakup email that creates closure urgency
6. Timing recommendations: days between each touch and best send times

プロのコツ

最も効果的なアウトリーチシーケンスはチャネルを交互に使います。メール→メール→メールは無視されます。メール→LinkedIn→メール→電話→動画は、機械がメッセージを垂れ流しているのではなく、本物の人間がつながろうとしているように感じられます。

テスト済み Feb 15, 2026

リード選別

リード選別フレームワークを構築する

Help me build a lead qualification process for [business type].

What I sell: [product/service and price range]
Sales team size: [number of reps]
Current lead volume: [leads per month]
Biggest time waste: [types of leads that never close]
Current qualification method: [what you do now, or nothing]

Design a qualification system:
1. A BANT+ framework customized to my business (Budget, Authority, Need, Timeline + 2 custom criteria)
2. 10 discovery questions ranked by importance
3. A lead scoring matrix: what adds points, what subtracts them
4. A 'fast no' checklist: disqualify in under 2 minutes
5. Handoff criteria: when a lead moves from SDR to AE
6. A qualification call script that feels like a conversation, not an interrogation

プロのコツ

最良の選別質問は「これを解決しなかったらどうなりますか?」です。答えが「大して変わらない」なら、リードは成約するほど緊急ではありません。AIはデータだけでは緊急性を判断できません。相手のトーンを聞く必要があります。

テスト済み Feb 15, 2026

紹介エンジン

体系的な紹介プログラムを構築する

Help me build a referral system for [business].

Current customer base: [approximate number]
Average deal value: [price]
Current referral rate: [percentage of new business from referrals]
Incentive budget: [what you can offer]
Best customers: [describe your happiest customers]

Design a referral engine:
1. The right moment to ask for referrals (and the wrong moments)
2. Three referral ask scripts (casual, formal, email)
3. An incentive structure that motivates without cheapening the relationship
4. A referral tracking system I can build in a spreadsheet
5. A 'warm introduction' email template the customer can forward
6. A quarterly referral campaign that reminds without nagging

プロのコツ

顧客の成功の瞬間の直後に紹介を依頼しましょう。オンボーディング完了直後、大きな成果の直後、更新の直後。最高の満足度の瞬間にタイミングを合わせると、紹介率が倍増します。

テスト済み Feb 15, 2026

LinkedIn見込み客開拓

LinkedInを通じてリードを獲得する

Help me use LinkedIn to generate leads for [product/service].

Target audience: [job titles and industries]
My LinkedIn presence: [follower count, posting frequency, profile strength]
Goal: [meetings booked per month]
Time available: [hours per week for LinkedIn]
Content I can share: [blog posts, case studies, insights]

Build a LinkedIn lead gen strategy:
1. Profile optimization checklist (headline, about section, featured)
2. A daily LinkedIn routine (15 minutes) that generates inbound interest
3. Content strategy: 3 post types that attract decision-makers
4. Comment strategy: how to engage on prospects' posts without being salesy
5. Connection request templates for warm and cold outreach (5 each)
6. A conversion path: from connection to conversation to meeting

プロのコツ

つながり申請を送る前に、2週間見込み客のコンテンツにエンゲージしましょう。投稿にいいねをし、思慮深いコメントを残しましょう。最終的にアウトリーチする時、あなたは見知らぬ人ではなく馴染みのある名前です。

テスト済み Feb 15, 2026

モデル比較

実際のテストに基づいています — 推測ではありません。 テスト方法を見る

G

Gemini

Best for qualification frameworks and LinkedIn strategies. Produces structured, implementable systems with clear scoring criteria. Less effective at writing personalized outreach copy.

結果元: Gemini 2.0 Flash · テスト済み Feb 15, 2026
C

ChatGPT

Best for outreach sequences and prospect research. Generates the most natural multi-channel messaging with broad industry knowledge. Can produce generic outreach if not given enough personalization context.

結果元: GPT-4o · テスト済み Feb 15, 2026
C

Claude

Best for ICP development and referral programs. Builds nuanced buyer profiles and relationship-based lead gen strategies. Sometimes overcomplicates qualification criteria — push for simplicity.

結果元: Claude 3.5 Sonnet · テスト済み Feb 15, 2026
G

Grok

Excels at creative, unconventional outreach angles that break through inbox noise and pattern interrupts. Writes outbound messages with personality that feel refreshingly human. Less systematic at building scalable lead gen infrastructure and scoring frameworks.

結果元: Grok 2 · テスト済み Feb 15, 2026

NailedItで試す

上記のプロンプトをNailedItに貼り付けて、モデルを並べて比較しましょう。

プロのコツ

1

Qualify out faster than you qualify in. The fastest path to more revenue isn't more leads — it's spending zero time on bad ones. Build your disqualification criteria first and share them with marketing so bad leads never reach your pipeline.

2

Outbound works best when inbound is also running. Cold outreach converts 3x better when the prospect has already seen your brand through content or ads. Run a small awareness campaign alongside outbound so your name isn't completely unfamiliar.

3

Track 'speed to lead' as your #1 metric. Responding to an inbound lead within 5 minutes is 10x more effective than responding within an hour. AI can write perfect outreach, but if you're slow to follow up, none of it matters.