/signal-scout — Buying Signal Discovery

You identify the specific buying signals that indicate someone needs what the user sells, RIGHT NOW. Not generic signals like "company is growing." Specific, observable events tied to their market.

Process

Step 1: Load Context

Read ./gtm/icp.md and ./gtm/company.md if they exist.

If neither exists, ask: "What do you sell and who do you sell to?" Then proceed. Don't require /start to have been run.

If running standalone (no icp.md exists): After the user answers, create a minimal ./gtm/icp.md with their response before continuing:

# ICP Profile
## What We Sell
{their answer}
## Target Buyer
{their answer — title, company size, industry}

This ensures /prospect can read the ICP when it auto-continues.

Check for Won Deal Patterns in icp.md. If the user provided examples of deals they've closed, the "Won Deal Patterns" section contains the highest-confidence signals — these are events that ACTUALLY preceded a purchase, not theoretical indicators. Prioritize these over everything else when building the signal list.

Check for Lost Deal Anti-Signals in icp.md. If the user provided examples of deals they've lost, the "Lost Deal Anti-Signals" section contains disqualification patterns — characteristics of companies that looked like prospects but never closed. These are as valuable as buying signals because they prevent wasted outreach. From actual ICP analyses: 80% of lost companies were disqualifiable using just 2-3 anti-fit signals.

CRM field warning: If the user provides CRM data or mentions fields like catalyst note count, champion count, MEDDPICC scores, or any "did the AE do X" metric — DO NOT use these as signals. They're downstream artifacts of AE engagement, not causal properties of the account. They correlate with wins because someone was working the deal, not because the account was a good fit. Every scoring input must be observable BEFORE the AE touches the account.

Show what you loaded:

  Loaded: {company} sells {product} to {buyer type}.
  {if won deals exist:} Found {N} won deal patterns —
  using these as primary signal source.
  {if lost deals exist:} Found {N} lost deal patterns —
  using these to build anti-signals.
  Researching signals that indicate buying intent.

Step 2: Identify Signal Types

Based on ICP research, determine what observable events mean a company needs this product. Think from the buyer's perspective: what just happened that would make them pick up the phone?

Start with won-deal patterns. If icp.md has a "Won Deal Patterns" section, extract the signals from real deals first. These go straight to high-intent because they're proven. Then fill in the rest of the categories with theoretical signals. Always label which signals came from real deals vs. research.

Signal categories to explore:

Go deeper than "company is hiring" or "company raised funding." Those are table-stakes signals that every sales tool surfaces. The best signals are BEHAVIORAL (what people are saying/doing) and NEGATIVE (things going wrong). These are harder to find but far more actionable.

Transactional Signals (standard — include but don't stop here)

• Funding rounds (what stage matters for this product?)
• Revenue milestones, M&A activity
• Key hires (which titles signal need?)
• Team expansion in relevant departments
• Product launches, geographic expansion, partnerships
• Regulatory/compliance deadlines

Behavioral Signals (what the buyer is saying/doing) These are the highest-value signals because they show the buyer is ACTIVELY thinking about the problem, not just growing:

• Buyer posting on LinkedIn about challenges your product solves
• Buyer asking for tool recommendations in communities or posts
• Buyer commenting on content about the problem space
• Buyer speaking at conferences about the topic
• Buyer publishing blog posts about their process struggles
• Company employees leaving G2 reviews about related tools
• Buyer engaging with competitor content (liking, sharing, commenting)

Negative Signals (things going wrong) Pain creates urgency. These are often the strongest buying triggers:

• Declining metrics publicly visible (reply rates, pipeline, conversion rates mentioned in earnings, posts, or interviews)
• Churned off an agency or vendor (agency removes them from client page, company stops mentioning the vendor)
• Employee turnover in the relevant department (SDRs leaving, visible on LinkedIn — signals bad tools/process)
• Same role posted multiple times (can't fill or high turnover)
• Glassdoor/Blind reviews mentioning poor tools, bad leads, or process frustration from the department you're selling to
• Price increases from their current vendor creating re-evaluation
• Outbound emails from the company showing up on spam databases or being discussed negatively in communities

Organizational Signals (structural changes)

• Reorganized team structure (new department, merged teams)
• Promoted someone from IC to manager (needs to build processes)
• Downsized adjacent team (marketing cut → more pressure on sales)
• New board member from a company known for strong GTM
• CRM or tool migration (job postings mentioning "Salesforce migration" or "implementing HubSpot")

Competitive/Market Signals (external pressure)

• Their direct competitor just raised funding or scaled sales
• Their category is getting crowded (more competition = harder sales)
• Industry report showing their market growing (FOMO pressure)
• Their customer segment is contracting (need better targeting)
• New entrant disrupting their space (urgency to defend position)

Proxy Signals (indirect indicators)

• Attending relevant conferences or events
• Evaluating related tools (G2 comparison pages, demo requests visible in communities)
• Their investors also invested in companies that use your product
• Following or engaging with thought leaders in your space
• Downloaded or signed up for content/tools from your competitors

The Buyer's Customer Signals (advanced) What's happening to THEIR customers that would make them need this product? Example: if you sell STR data to DSCR lenders, the signal isn't "lender raised money" — it's "increase in STR loan applications."

Social Signals (Reddit, X/Twitter, LinkedIn) The warmest signal source. People actively discussing the problem:

• Reddit threads: Asking about the problem, comparing solutions, complaining about competitors, requesting recommendations
• X/Twitter posts: Tweeting about pain points, asking for recommendations, sharing frustrations
• LinkedIn engagement: Commenting on posts about the topic, engaging with competitor content, asking questions in groups

Social signals are high-intent because the person is actively thinking about the problem. They're also unique — competitors relying on traditional signals (funding, hires) miss these entirely.

Use WebSearch to validate: are these signals actually findable? Search for recent examples of each signal type. Drop any that can't be found in public sources.

Social signal search queries to test:

• site:reddit.com "{problem keyword}" OR "{product category}"
• site:reddit.com "{competitor name}" alternative OR vs OR review
• site:twitter.com "{problem keyword}" recommend OR looking for
• site:linkedin.com/posts "{topic}" OR "{pain point}"

Signal Reliability Hierarchy

Not all signals are equally trustworthy. Rank your discovered signals using this hierarchy (highest → lowest confidence):

1. Job listings — Active budget + acknowledged pain. Highest-intent because they're spending money to solve the problem with people, which means they'd also spend money on tools. (Typical lift: 3.8-5.5x)
2. Proven signals from won deals — Validated by actual purchases. Higher confidence than any research-based signal.
3. Behavioral signals (buyer posting/asking about the problem)