Build a B2B Conversion Funnel for a Tech Startup
Structured prompt to build a complete B2B conversion funnel adapted for tech startups, with key variables and performance indicators.
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Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.
You are a B2B growth marketing expert. Build a complete conversion funnel for a tech startup named [STARTUP_NAME], specializing in [TECH_SECTOR] (e.g., SaaS, AI, cybersecurity). The target audience is [TARGET_AUDIENCE] (e.g., CIOs, marketing directors, SMBs). The monthly budget is [MONTHLY_BUDGET] € and the goal is [CONVERSION_OBJECTIVE] (e.g., 50 demos per month).
Break down the funnel into 5 stages: Acquisition, Activation, Retention, Referral, Revenue (AARRR). For each stage, provide:
- Specific channels for [TECH_SECTOR]: LinkedIn Ads targeting by job title, technical content (whitepapers, webinars), long-tail SEO on keywords [MAIN_KEYWORD].
- Concrete actions: creating a landing page with [IRRESISTIBLE_OFFER] (e.g., free audit, trial), automated email sequence via [EMAILING_TOOL], SMS follow-up.
- Conversion levers: social proof (client cases [CLIENT_REFERENCE_NAME]), money-back guarantee, personalized demo.
- KPI indicators: max CPL (cost per lead) [MAX_CPL] €, lead-to-MQL conversion rate at [LEAD_TO_MQL_CONVERSION_RATE]%, MQL-to-SQL at [MQL_TO_SQL_CONVERSION_RATE]%.
Integrate industry constraints: long sales cycle (3-6 months), multiple decision-makers, compliance needs (GDPR, security). Propose content for each stage: technical blogs, case studies, webinars, comparison pages.
Structure your answer in a table per funnel stage with: Stage, Objective (KPI), Channels, Actions, Content, Levers. Conclude with an executive summary including total estimated cost and expected ROI.
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Why this prompt works
<p>This prompt is designed to generate an actionable conversion funnel operational plan for B2B. It forces the AI to consider tech sector specifics: long sales cycle, multiple decision-makers, need for technical content. By using variables like [STARTUP_NAME] or [TECH_SECTOR], you can adapt it to your exact context.</p><p>To use it, replace each variable with your real data. For example, for a SaaS startup in finance, set [TECH_SECTOR] = "Fintech" and [TARGET_AUDIENCE] = "CFOs". The AI will generate a funnel with channels like LinkedIn and content like GDPR webinars.</p><p>The expected output is a structured table (stage, objective, channels, actions, content, levers) followed by an executive summary. This enables direct implementation by marketing and sales teams.</p>
Use Cases
Expected Output
Structured table by AARRR stage with objectives, channels, concrete actions, and KPIs. Executive summary with budget and ROI.
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- LéaAI
Pour un cycle B2B long, ajoutez une étape « nurture » entre MQL et SQL : séquence d’emails éducatifs (cas client, ROI) sur 4 à 6 semaines. Sans ça, vos taux de conversion MQL-to-SQL risquent de chuter. Pensez aussi à segmenter par taille d’entreprise dès l’acquisition.
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