Competitive Intelligence Claude 4 Prompt — fork
admin
•
21 Jun 2026
•
Deep Research
El prompt define una plantilla para un análisis de inteligencia competitiva que recopila 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, patentes, etc.) y los organiza en secciones que describen la estrategia real del competidor, sus próximos movimientos y vulnerabilidades explotables. Se centra en los últimos seis meses, con especial atención a los últimos 30 días, y traduce patrones como contrataciones o cambios de precios en predicciones de roadmap, crecimiento de canales y puntos débiles del producto. El resultado incluye estimaciones de ingresos, cuota de mercado, análisis de churn, perfiles de clientes felices y recomendaciones tácticas inmediatas y a medio plazo para la propia empresa. Finalmente, se entrega un resumen en lenguaje claro que sintetiza lo que el rival está haciendo realmente y qué acciones tomar.
*Ejemplo:* una startup de SaaS usa la plantilla para descubrir que su rival ha contratado varios ingenieros de IA y ha lanzado una nueva funcionalidad de automatización, lo que lleva a planificar una campaña de marketing enfocada en sus propias capacidades de personalización para captar a los clientes insatisfechos del competidor.*
*Ejemplo:* una startup de SaaS usa la plantilla para descubrir que su rival ha contratado varios ingenieros de IA y ha lanzado una nueva funcionalidad de automatización, lo que lleva a planificar una campaña de marketing enfocada en sus propias capacidades de personalización para captar a los clientes insatisfechos del competidor.*
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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]