PlaybookGTM / SaaS Systems

How I’d Build an Account Research Workflow

How to automate pre-call company research, hiring trends, and financial news extraction using web scrapers and LLMs to feed sales prep.

#Sales Enablement#Research#n8n#AI Agents

➔ Core System Framework Map

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People

Account Executives (AEs) and Sales Development Representatives (SDRs) preparing for initial prospect calls.

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Process

When a new lead books a meeting, the sales rep spends 15-20 minutes searching LinkedIn, Google News, and the prospect's company website to find relevant business triggers, recent press releases, and executive priorities.

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Pain

Research is highly manual, leading to inconsistent prep quality. Reps often default to generic messaging because they run out of prep time between back-to-back calls.

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Measure

A representative team of 10 AEs booking 20 meetings per week spends over 50 hours a week on manual copy-paste research. Call open rates and relevance scores drop due to generic templates.

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Solution

A workflow triggered automatically by a Calendar booking. It scrapes the prospect's company website, queries Google News API for recent press releases, fetches active job postings on LinkedIn, and passes this context to an LLM to generate a clean, bulleted 1-page briefing sheet sent to the rep's Slack or email 30 minutes before the call.

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Impact

Reduces prep time from 20 minutes to 2 minutes per call. SDRs and AEs enter meetings with verified, real-time context on the prospect's current initiatives, increasing call relevance and booking rates.

Entering a meeting cold is a recipe for a low-conversion call. However, manually scraping the web for every lead is a poor use of a sales rep's time.

Here is how we turn pre-call research into a structured utility using LLM scraping and low-code integrations.

The Workflow Breakdown

People

  • User: Account Executives (AEs) & Sales Development Reps (SDRs).
  • Stakeholder: Sales Enablement (ensuring uniform prep quality across the team).

Process

  1. Trigger: A prospect books a meeting via Calendly/HubSpot Meetings.
  2. Current Steps: Rep copies company name ➔ opens Google ➔ searches for recent news ➔ opens LinkedIn ➔ checks open jobs ➔ reads company 'About' page ➔ writes notes in notepad.
  3. Delivery: The notes sit in a personal notepad, invisible to the CRM.

Pain

  • Manual Overhead: The rep spends the first 10 minutes of their prep time just hunting for links rather than analyzing the business.
  • Data Expiry: News and hiring trends change daily; manual research done on Monday is stale by a Thursday meeting.
  • Inconsistency: Some reps do deep research, while others do none.

Measure

  • Time Spent: 15 mins per lead * 8 leads/week = 2 hours/week per AE. For a 12-AE team, that is 24 hours/week of search activity.
  • Direct Cost: $1,200/month of sales rep salary spent searching Google.

Solution

We build an automated pipeline using n8n and Claude 3.5 Sonnet:

  1. Listen: n8n listens for new Calendar events containing prospect email domains.
  2. Lookup: Resolves the domain using Clearbit/Enrichment APIs to get the company name.
  3. Scrape: Uses Tavily Search API to fetch:
    • Top 3 news articles from the past 30 days.
    • Company product pages.
    • Active job listings mentioning "system," "operations," or "AI."
  4. Synthesize: Claude receives the raw text and runs a structured prompt:
    • Identify top 3 pain points.
    • Match company news with our product value proposition.
    • List key executives on the call.
  5. Output: Formats into a markdown card and sends it to the AE's Slack channel 30 minutes before the calendar event starts.

Impact

  • Prep Time Saved: Reduced by 90% (from 20 mins to 2 mins).
  • Meeting Quality: Reps lead with value: "I saw you recently expanded your RevOps team to focus on enterprise search..." rather than "So, tell me about your business."