En este modulo

  1. Prospecting has changed
  2. Defining your ICP with AI
  3. LinkedIn Sales Navigator + AI
  4. Lead enrichment: data that sells
  5. Personalized outreach with AI
  6. Intelligent cold email
  7. Multichannel outreach sequences
  8. Prospecting tools
  9. Errores comunes
  10. Ejercicio practico
  11. Puntos clave

Prospecting has changed

Traditional prospecting was a numbers game: call 100 people to get 3 meetings. Send 500 generic emails to get 10 replies. That model still exists, but its effectiveness drops every year. Decision makers receive dozens of prospecting messages daily. Most ignore them.

AI changes prospecting in two fundamental ways. First, it allows you to research each prospect in depth before the first contact. Second, it allows you to personalize each message at scale. The result: fewer messages sent, but each one is relevant to the person receiving it.

The new prospecting paradigm has 4 phases:

  1. Define ICP (Ideal Customer Profile): who is your ideal customer, with data, not intuition.
  2. Identify and enrich: find people who fit your ICP and obtain relevant data about them.
  3. Personalize: create a message that demonstrates you've researched and that your solution is relevant to their specific situation.
  4. Execute multichannel: contact via email, LinkedIn and phone in a coordinated way.

AI can participate in all 4 phases.

Defining your ICP with AI

The ICP (Ideal Customer Profile) defines the characteristics of companies and people most likely to buy your product. Without a clear ICP, you'll prospect anyone who looks like a company. With an ICP, every commercial effort is directed at those most likely to convert.

Company-level ICP

Person-level ICP (buyer persona)

Using AI to define ICP

"We are [type of company] and sell [product/service]. Our best current customers are: [list 5-10 clients with industry, size, buyer title, problem we solved]. Analyze these customers and generate an ICP that includes: ideal company profile (industry, size, technology, buying signals), buyer persona (title, responsibilities, motivations, objections), disqualification criteria (what type of company is NOT our ideal customer)."

If you don't have customers yet, you can use market data: "Analyze the [your sector] market. Identify segments with the highest propensity to adopt [your type of solution]. For each segment: estimated market size, competition level, willingness to pay, ease of access. Suggest the ICP with the highest conversion probability for an early-stage startup."

The ICP is not static

Review your ICP every quarter with real data: who converted, who didn't, what was the reason for loss. AI can analyze your pipeline from the last 90 days and suggest ICP adjustments based on data, not assumptions.

LinkedIn Sales Navigator + AI

LinkedIn Sales Navigator is the most powerful tool for B2B prospecting. It lets you search prospects with advanced filters: title, company, industry, tenure, recent activity, shared connections.

Sales Navigator AI features

Sales Navigator + AI workflow

  1. Define filters based on your ICP: title, industry, company size, location.
  2. Save the results as a "lead list."
  3. For each prospect, review their profile, recent activity and posts.
  4. Use AI to generate a personalized connection message or InMail based on their profile.
  5. Monitor buyer intent signals to contact at the optimal moment.

Pricing: Sales Navigator Core from 80 EUR/month. Advanced from 130 EUR/month (with CRM sync and Smart Links).

Personalizing InMails with AI

"Generate a LinkedIn InMail for [name], [title] at [company]. Information from their profile: [paste profile summary, recent posts, recent changes]. My product: [brief description]. The InMail must: mention something specific from their profile or recent post, connect with a problem they likely have given their title, propose a brief meeting (15 min) with clear value. Maximum 300 characters in the subject, 500 in the body. No generic formulas like 'I hope this message finds you well'."

Lead enrichment: data that sells

Lead enrichment is the process of adding data to a contact to personalize the message and better qualify them. A name and email are not enough. You need to know what the company does, what technology they use, what challenges they face, whether they have budget.

Enrichment data

Enrichment tools

Enrichment with AI (without dedicated tools)

If you don't have access to enrichment tools, AI can do basic research:

"Research the company [name] and their [title] [person name]. Search for: what the company does, approximate size, whether they've received recent investment, what technologies they use (check their website), recent news, LinkedIn posts from the contact. Summarize in a 1-paragraph brief I can use to personalize my first contact."

This works best with tools that have search access (Perplexity, ChatGPT Search, Gemini).

Personalized outreach with AI

Outreach is the first contact with a prospect. The difference between outreach that gets a reply and one that gets ignored is personalization. Not fake personalization ("I saw you work in marketing" is obvious and adds nothing). Real personalization: demonstrating you've researched and that your message is relevant to their specific situation.

Personalization framework

  1. Trigger: something concrete motivating your contact now (role change, recent post, company news, hiring a specific profile).
  2. Relevance: connect the trigger with a problem or need your solution addresses.
  3. Credibility: a data point, case study or reference proving you can help.
  4. CTA: a concrete, low-commitment action ("15 minutes to explore if this makes sense," not "schedule a 1-hour demo").

Generating personalized outreach at scale

The challenge: personalizing each message for 50 different prospects takes hours. AI reduces it to minutes:

"I have 10 prospects. For each one, generate a personalized first-contact email. Each prospect's data: [paste name, title, company, trigger, relevant data point]. Structure for each email: 1 opening sentence mentioning the trigger, 1 connection paragraph (their problem + my solution), 1 credibility line (similar case study), CTA. Maximum 150 words per email. Tone: direct, professional, without excessive flattery."

Real personalization vs fake personalization

"I saw you work at [company]" is not personalization. "I read your Tuesday post about the difficulty of attributing LinkedIn leads and thought it was spot-on. We solved exactly that for [similar client]" is personalization. The difference: specific data proving you've researched.

Intelligent cold email

Cold email works. The average response rate in well-executed B2B cold email is between 5-15%. The key is the balance between volume and quality.

Anatomy of an effective cold email

Generating cold emails with AI

"Write a cold email for a [title] at a [type] company. Context: they just [trigger]. My product solves [problem]. Case study: we helped [similar company] achieve [concrete result with number]. The email must be maximum 100 words. No 'I hope you're doing well'. No 'Let me introduce myself'. Start directly with something relevant to the prospect."

Follow-up sequences

The first email rarely gets a response. Most replies come on the second or third follow-up. A typical sequence:

Multichannel outreach sequences

Multichannel outreach combines email, LinkedIn and phone in a coordinated sequence. Data shows multichannel sequences have 3x more responses than single-channel ones.

Typical multichannel sequence

  1. Day 0: Send LinkedIn connection request with personalized note.
  2. Day 1: First personalized email.
  3. Day 3: Interact with a prospect's LinkedIn post (like + value-adding comment).
  4. Day 5: Second email with added value.
  5. Day 7: LinkedIn message (if they accepted the connection).
  6. Day 10: Third email with a different angle.
  7. Day 14: Phone call (if you have their number).
  8. Day 18: Breakup email.

AI can design the entire sequence and generate the content for each touchpoint.

Prospecting tools

Errores comunes

  1. Prospecting without an ICP. Contacting "any company that might buy" is inefficient. Define your ICP with data before sending a single message.
  2. Generic emails at scale. AI enables scale, but without real personalization, scale = more spam. Every email must show you researched the prospect.
  3. Not following up. 80% of sales require 5 or more contacts. If you send 1 email and give up, you're losing 80% of opportunities.
  4. Selling on the first contact. The goal of the first email is not to sell. It's to generate interest and get a meeting. Don't include pricing, demos or 30-page PDFs in the first contact.
  5. Ignoring compliance. GDPR in Europe requires a legal basis for sending commercial emails. Inform yourself about your obligations before launching mass campaigns.

Ejercicio practico

Ejercicio MV06: Your prospecting with AI
  1. Define your ICP with AI using data from your current customers (or market data if you don't have customers yet). Generate the ideal company profile + buyer persona.
  2. Find 20 prospects matching your ICP using LinkedIn (or Sales Navigator if you have access). Save their data in a spreadsheet.
  3. Enrich 5 of those prospects: search their recent LinkedIn activity, company news, technologies they use. Use Perplexity or ChatGPT Search.
  4. Generate 5 personalized cold emails with AI, one for each enriched prospect. Use the trigger-relevance-credibility-CTA framework.
  5. Design a 4-email follow-up sequence with AI. Schedule sends with 3-5 days apart.

Bonus: Set up Apollo.io (free plan) or Lemlist and load your first automated sequence of 5 prospects. Measure: open rate, response rate and meetings booked.

Puntos clave

Puntos clave from MV06

  1. Effective prospecting in 2026 is: less volume, more personalization. AI enables researching and personalizing at scale without losing quality.
  2. The ICP is the foundation of all prospecting. Without a clear ICP, any commercial effort dilutes. Define it with data and review it every quarter.
  3. LinkedIn Sales Navigator + AI to identify prospects. Enrichment tools (Apollo, Clay) for data. AI to generate personalized messages.
  4. Cold email works if: the subject is relevant, the body is short, personalization is real and there's systematic follow-up.
  5. Multichannel sequences (email + LinkedIn + phone) have 3x more responses than single-channel ones.
Guia de estudio — Conceptos clave de MV06

La prospeccion ha cambiado

  • Definir ICP (Ideal Customer Profile):quien es tu cliente ideal, con datos, no con intuicion.
  • Identificar y enriquecer:encontrar personas que encajan en tu ICP y obtener datos relevantes sobre ellas.
  • Personalizar:crear un mensaje que demuestre que has investigado y que tu solucion es relevante para su situacion concreta.
  • Ejecutar multicanal:contactar por email, LinkedIn y telefono de forma coordinada.

Definicion de ICP con IA

  • Industria:en que sector opera (SaaS, fintech, retail, manufactura).
  • Tamano:numero de empleados, facturacion anual.
  • Geografia:mercados donde operas.
  • Tecnologia:que stack usan (se puede verificar con herramientas como BuiltWith o Wappalyzer).
  • Senales de compra:estan contratando (crecimiento), acaban de recibir inversion, han publicado un RFP, tienen un problema visible que tu resuelves.
  • Cargo:CMO, VP Sales, Director de Marketing, Head of Growth.

LinkedIn Sales Navigator + IA

  • Lead Recommendations:sugiere prospects similares a los que ya tienes guardados.
  • Account Mapping:identifica a los decision makers dentro de una empresa objetivo.
  • Buyer Intent signals:detecta cuando un prospect ha cambiado de cargo, su empresa ha publicado noticias relevantes o ha interactuado con contenido de tu sector.
  • Smart Links:envia contenido rastreable (presentaciones, PDFs) y ve quien lo abrio, cuanto tiempo y que paginas vio.
  • Define filtros basados en tu ICP: cargo, industria, tamano de empresa, ubicacion.
  • Guarda los resultados como "lead list".

Lead enrichment: datos que venden

  • Firmograficos:industria, tamano, facturacion, ubicacion, ano de fundacion.
  • Tecnograficos:que herramientas y tecnologias usa (stack de marketing, CRM, ERP).
  • Intent data:que temas esta investigando online (a traves de proveedores de intent data como Bombora o G2).
  • Actividad social:que publica en LinkedIn, que comparte, que comenta.
  • Noticias:financiacion reciente, expansion, cambios de liderazgo, lanzamientos de producto.
  • Apollo.io:base de datos de contactos B2B con email y telefono. Enrichment automatico. Plan gratis con limites. Pro desde 49 USD/mes.

Outreach personalizado con IA

  • Trigger:algo concreto que motiva tu contacto ahora (cambio de cargo, publicacion reciente, noticia de su empresa, contratacion de un perfil especifico).
  • Relevancia:conecta el trigger con un problema o necesidad que tu solucion aborda.
  • Credibilidad:un dato, caso de exito o referencia que demuestre que puedes ayudar.
  • CTA:una accion concreta y de bajo compromiso ("15 minutos para explorar si tiene sentido", no "agenda una demo de 1 hora").
  • > Personalizacion real vs personalización falsa: "He visto que trabajas en [empresa]" no es personalización. "Vi tu post del martes sobre la dificultad de atribuir leads de LinkedIn y me parecio acertado. Nosotros resolvimos exactamente eso para [cliente similar]" es personalizacion. La diferencia: datos especificos que demuestran que has investigado.

Cold email inteligente

  • Asunto:corto (3-7 palabras), personalizado, sin clickbait. "Pregunta sobre [problema especifico]" o "[Nombre], [referencia concreta]".
  • Primera linea:demuestra que sabes algo sobre el prospect. No vendas aqui. Genera curiosidad.
  • Cuerpo:2-3 frases que conecten su problema con tu solucion. Un dato de credibilidad.
  • CTA:pregunta cerrada de bajo compromiso. "Tiene sentido dedicar 15 minutos?" o "Es esto relevante para tu equipo?".
  • Firma:nombre real, cargo, empresa, telefono. Sin imagenes ni HTML excesivo (mejora deliverability).
  • ### Secuencias de follow-up

Siguiente: MV07 - Intelligent CRM and Lead Scoring

You're generating leads. Now you need to manage them: CRM with AI, predictive lead scoring, pipeline automation and deal prediction.

Ir al modulo MV07