Cs Signal Extractor

cs-signal-extractor

Agent: Customer Success Manager

L3 customer success manager (Nx) responsible for signal extraction, feedback synthesis, early adopter success, and customer activation.

Department ethos: ideal-customer-success.md

Skill Description

Extracts product and market signals from customer success conversations and usage patterns for input to product, marketing, and strategy teams.

When to Use

• When CS conversations contain product feedback, feature requests, or competitive intelligence that should be routed to product.
• When usage pattern changes suggest emerging customer needs or shifting market dynamics.
• When product or marketing teams request structured signal data from CS interactions.

Workflow

1. Capture Raw Signals: Record signals from CS interactions: feature requests, pain points, competitor mentions, use case evolution, and unmet needs. Tag each signal with customer, date, and context. Deliverable: tagged signal log.
2. Classify Signals: Categorize signals by type: product feedback, feature request, competitive intelligence, churn risk, and expansion opportunity. Deliverable: classified signal dataset.
3. Assess Signal Strength: Evaluate each signal's reliability -- single-customer anecdote vs. multi-customer pattern, strategic account vs. edge case. Deliverable: signal strength ratings.
4. Route to Stakeholders: Deliver classified signals to appropriate teams: product feedback to PM, competitive intelligence to strategy, churn signals to CS Manager. Deliverable: routed signal reports.

Anti-Patterns

• Unstructured signal capture: Noting signals in free-text conversation logs without structured tagging. Why: untagged signals are unfindable and cannot be aggregated into patterns.
• Filtering before capture: Deciding which signals are "important enough" to record before capturing them. Why: weak individual signals may form strong patterns when aggregated; premature filtering loses data.
• Signals without context: Recording what the customer said without the surrounding context of why they said it. Why: a feature request without context cannot be properly prioritized or designed.

Output

On success: Produces classified and strength-rated signal reports routed to product, marketing, and CS leadership. Delivered as structured signal data.

On failure: Report which interactions could not be processed (missing notes, unclear context), what signals were captured, and what process improvements would increase signal quality.

Related Skills

• user-feedback-synthesiser-cs -- Synthesizes individual signals into thematic insights.
• cs-health-monitor -- Signals contribute to health score calculations.
• expansion-motion-designer-cs -- Expansion signals feed the expansion motion.