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SI-1 · Signal Intelligence · 100 XP · ~18 min
A signal is any observable event that indicates a company or person may be more receptive to your outreach right now than they were yesterday. The key word is “observable.” You can’t know what someone is thinking — but you can observe what they’re doing. A company posting 8 sales job listings, announcing a $20M Series B, and onboarding a new VP of Sales is observable. It’s also a strong, time-sensitive buying signal.

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Signal Taxonomy

Signals exist on two axes: strength (how predictive they are of buying intent) and latency (how quickly you need to act before the signal goes cold).
Signal CategoryStrengthLatencyExamples
First-party directVery highHoursPricing page visit, demo request, free trial
Job changeHighDaysNew executive hire in a relevant role
Funding eventHighDays–weeksSeries A/B/C announcement
Hiring surgeMedium-highDays–weeksPosting 5+ SDR/sales/growth roles
Product launchMediumDaysNew product, new market, partnership announcement
Competitive displacementMediumDays–weeksJob posting requires competitor tool, G2 review comparing competitors
Content engagementLow-mediumDaysDownloaded a relevant resource, attended a webinar
Tech stack changeMediumWeeksAdded or removed a tool from their stack
News & eventsVariableDaysConference speaking slot, press coverage, award

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Signal Decay

Every signal has a half-life. Wait too long to act and the signal is worthless.
Signal TypeOptimal Outreach WindowWhy
Pricing page visitSame dayBuyer is actively comparing
Funding announcementWithin 3 daysBudget decisions made immediately post-close
Executive hireWithin 7 daysNew hire is in “make my mark” mode
Job posting (sales roles)Within 2 weeksHiring cycle in progress
Product launchWithin 1 weekCompany is in growth mode
Content downloadWithin 48 hoursInterest is highest immediately
After the optimal window, you can still act — but the signal is weaker. The personalization becomes “I noticed you hired a new VP of Sales last month” which sounds less timely than “I saw you just announced [Name] as your new VP of Sales.”

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Signal vs. Noise: The Quality Filter

Not every signal is worth building a workflow around. Apply this three-question filter:
  1. Is it specific? — “Company is in SaaS” is noise. “Company just hired a VP of Sales from Salesforce” is a signal.
  2. Is it timely? — Can you act on it within the optimal window?
  3. Is it actionable? — Does it give you something specific to say in your outreach?
A signal passes all three filters. Anything else is data, not a signal. Examples:
  • “They’re a B2B SaaS company” → Data (useful for filtering, not for triggering)
  • “They raised a $15M Series B announced yesterday” → Signal (specific, timely, actionable)
  • “They use Salesforce” → Data (useful for personalization, not for triggering — unless they just added it)
  • “Their VP of Revenue posted 3 times this week about pipeline generation” → Signal (specific, very timely, actionable)

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Building a Signal Detection System

Signal detection in Bitscale is a combination of scheduled workflows that check for events and trigger enrichment when a signal fires. The architecture has three layers: Layer 1: Signal sources — where you monitor for events
  • LinkedIn (job postings, executive hires, company updates)
  • Crunchbase / PitchBook (funding events)
  • Google News API / Bing News (press coverage)
  • Job boards (Indeed, Glassdoor, Lever, Greenhouse APIs)
  • Your CRM (first-party behavioral signals)
Layer 2: Signal detection — the Bitscale grid that processes raw events
  • Imports new events from signal sources
  • Classifies signal type and strength
  • Filters for your ICP
Layer 3: Signal activation — the enrichment + outreach trigger
  • Enriches the company and contact when a signal fires
  • Generates personalized copy using the signal as context
  • Routes to sequencer or creates a task for manual review

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Signal Quality Scoring Column

Evaluate the quality of this signal for B2B outbound:

Signal: {{signal_description}}
Source: {{signal_source}}
Date: {{signal_date}}
Company: {{company_name}}

Score the signal on:
- Specificity (0-30): Is it specific and unique to this company? Generic = 0, highly specific = 30
- Timeliness (0-30): Is it recent? Older than 30 days = 0, within 3 days = 30
- Actionability (0-40): Does it give you something specific to reference in outreach?

Return: {"specificity": N, "timeliness": N, "actionability": N, "total": N, "recommendation": "act_now / act_this_week / note_for_nurture / ignore"}
Quick Check: What are the two axes that define signal quality? What’s the optimal outreach window for a funding announcement? What three questions separate signals from noise?

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SI-1 Challenge: Build a Signal Quality Scoring Grid (+100 XP)

Collect 20 real signals from any combination of sources (LinkedIn, Crunchbase, news) for companies in your ICP. Requirements:
  • All 20 signals documented with: signal description, source, date, company
  • Signal quality score column (specificity, timeliness, actionability, total)
  • Recommendation column (act_now / act_this_week / note_for_nurture / ignore)
  • Distribution summary: how many in each recommendation bucket?
  • A short paragraph on which signal type had the highest average quality score and why

Submit SI-1 Challenge →

Share your grid + analysis paragraph. +100 XP on approval.

Next: SI-2 — Job Change Detection →

Job changes are among the highest-converting signals in B2B outbound. SI-2 covers how to detect, qualify, and activate them at scale.