Competitive Intelligence Claude 4 Prompt — fork
admin
•
21 Jun 2026
•
Deep Research
El prompt sirve para que un analista de inteligencia competitiva realice una investigación profunda sobre un competidor, recopilando más de 200 datos de fuentes públicas y semi‑públicas (tráfico web, ofertas de empleo, stack tecnológico, movimientos de empleados, opiniones de clientes, señales financieras, actualizaciones de producto, estrategia de contenido, patentes, conferencias, etc.). Con esa información se mapean patrones de contratación, cambios de precios, expansión geográfica y otras señales para inferir la hoja de ruta real del rival, sus fortalezas y vulnerabilidades, y se generan estimaciones de ingresos, crecimiento y cuota de mercado. El resultado incluye un resumen ejecutivo en lenguaje claro, listas de posibles movimientos del competidor, oportunidades explotables y acciones concretas a corto y largo plazo para la propia empresa.
**Ejemplo de uso:** una startup de SaaS analiza a su principal competidor y descubre, a través de nuevas contrataciones de ingenieros de IA y cambios en la política de precios, que lanzará una funcionalidad de automatización en los próximos tres meses; con ello decide acelerar su propio desarrollo de integración API y lanzar una campaña de retención dirigida a los clientes insatisfechos del rival.
**Ejemplo de uso:** una startup de SaaS analiza a su principal competidor y descubre, a través de nuevas contrataciones de ingenieros de IA y cambios en la política de precios, que lanzará una funcionalidad de automatización en los próximos tres meses; con ello decide acelerar su propio desarrollo de integración API y lanzar una campaña de retención dirigida a los clientes insatisfechos del rival.
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USER:
You are a competitive intelligence expert who uncovers what companies are actually building, not just what they're announcing.
Conduct deep reconnaissance on {{Competitor name}} to reveal their true strategy, upcoming moves, and vulnerabilities you can exploit.
{{Your company name}}
{{Your company/product for comparison}}
Analyze 200+ data points across public and semi-public sources
- Traffic analytics (Similarweb, SEMrush, Ahrefs)
- Job postings (LinkedIn, Indeed, AngelList, their careers page)
- Tech stack changes (BuiltWith, Wappalyzer, GitHub)
- Employee movements (LinkedIn updates, Twitter)
- Customer feedback (G2, Capterra, Reddit, Twitter complaints)
- Financial signals (funding news, pricing changes, partnership announcements)
- Product updates (changelog, app stores, ProductHunt)
- Content strategy (blog topics, webinar themes, ad campaigns)
- Patent filings and trademark applications
- Conference speaking topics and slide decks
Focus on last 6 months with special attention to last 30 days
Map job postings → product roadmap (e.g., hiring ML engineers = AI features coming)
Identify which channels/features are growing vs declining
Track complaint patterns to find product weaknesses
Connect disparate data points to reveal hidden strategy
- Sudden hiring sprees in specific areas
- New executive hires from specific industries
- Changes in pricing model
- Shifts in target audience messaging
- New technology implementations
- Geographic expansion signals
Map their current position - traffic, revenue estimates, market share
Decode hiring patterns to predict next 6-12 months
Analyze customer churn points and satisfaction gaps
Identify their strategic bets based on resource allocation
Find exploitable weaknesses and timing windows
Revenue: [estimate]
Growth rate: [%]
Team size: [total and by department]
Burn rate: [if applicable]
Main traffic sources: [top 3-5]
[Where they actually stand vs. perception]
[Specific job posts, hires, or signals]
[The feature/product they're developing]
[Estimated based on hiring patterns]
[How much this should worry you]
[Bullet points of likely moves based on evidence]
[Longer-term strategic shifts they're positioning for]
[Possible pivots or bold moves based on weak signals]
[Specific gap or problem]
[Customer complaints, employee reviews, etc.]
[Your opportunity]
[How long before they likely fix this]
[Profile of their happiest customers]
[Common reasons for churn]
[What customers wish they did better]
[What people say about their pricing]
[Notable people who joined recently]
[Important people who left]
[Departments growing fastest]
[Roles they can't fill - reveals weaknesses]
[3-5 things you could do THIS WEEK based on findings]
[Longer-term positioning based on where they're headed]
[What to protect based on their likely attacks]
[Plain English overview: what they're really up to, what it means for you, and what you should do about it]