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Lead nurture

Skill varunk130/ai-gtm-skill-library/revops-skills/lead-nurture

31 opinionated GTM skills for Claude Code & GitHub Copilot — a complete revenue engine spanning discover, design, position, amplify, launch, optimize, and RevOps phases.

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npx -y skills add varunk130/ai-gtm-skill-library --skill lead-nurture

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Lead nurture orchestration - multi-track nurture design by intent stage, scoring, behavioral triggers, MQL→SQL handoff, and revival of cold leads. Use when: lead nurture, drip campaign, nurture track, lead scoring, MQL to SQL, lifecycle marketing, nurture sequence, behavioral trigger, lead revival, MQL handoff.

SKILL.md

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Lead Nurture (NURTURE Framework)

Design a lead-nurture system that respects buyer intent, routes leads to the right next action, and stops sending eight more emails to people who already raised their hand. NURTURE replaces single-track drip sequences with multi-track journeys gated by behavioral signals.

Core Principle

Nurture fails when it treats time as the trigger. "Send email 3 on day 7" assumes every lead is on the same journey. NURTURE treats signal - not the calendar - as the trigger, and gates progression by demonstrated intent.

The NURTURE Framework

LetterStageThe Question
NNeeds MappingWhat buying-stage needs does the lead currently have evidence of?
UUnderstand IntentWhat behavioral and explicit signals map to which stage?
RRoute to TrackWhich nurture track does the lead enter, and on what entry criteria?
TTrigger ProgressionWhat signal moves the lead to the next step (or back)?
UUpgrade to SalesWhat threshold defines MQL → SQL handoff, and what's the SLA?
RRecycle ColdWhen does the lead exit the active track into long-cycle nurture?
EEngagement RefreshHow is content kept current and personalization kept honest?

Buying-Stage Nurture Tracks

StageLead StateTrack GoalCadence
UnawareDiscovered category, no problem framingFrame the problemBi-weekly
AwareAcknowledges problem, exploringReframe with our POVWeekly
ConsideringEvaluating vendorsDifferentiate + de-risk2-4×/week, behavior-gated
DecisionShort-listedAccelerate to demo / salesDaily during active window
Dormant / LostNo activity 60+ days OR closed-lostReactivate on signalQuarterly check-in + signal trigger

Intent Signals

A robust nurture system reads explicit and behavioral signals together:

TypeExampleImplication
ExplicitForm fill, demo request, pricing page submitHigh-confidence stage signal
Behavioral - highPricing page, comparison page, case study deep readConsidering or Decision
Behavioral - mediumWebinar registration, ebook downloadAware → Considering
Behavioral - lowBlog visit, newsletter openUnaware → Aware
DecayNo engagement 30+ daysRe-route to lighter cadence

Lead Scoring Design

Combine fit (firmographic) and intent (behavioral) into a 2D grid, not a single score:

Fit \ IntentLowMediumHigh
HighMarketing nurtureSales-assistSQL - immediate
MediumStandard nurtureBehavior-gatedSDR-triggered
LowNewsletter onlySelective nurtureManual triage

MQL → SQL Handoff

Failures here cost more pipeline than any other nurture problem. Codify:

ElementSpec
MQL DefinitionFit + intent threshold, with named behavioral triggers
SQL DefinitionSales-acceptance criteria written by sales
Handoff SLAFirst sales touch within X hours of MQL
Disposition LoopSales must reason-code rejected MQLs; feeds scoring tuning
Recycle PathRejected MQLs return to specific track, not a black hole

Output

Save to outputs/lead-nurture-[program]-[YYYY-MM-DD].md

ArtifactDescription
Track MapNamed tracks with entry / exit criteria and goal
Signal CatalogExplicit + behavioral signals with weights
Scoring GridFit × intent matrix with routing rules
Content PlanAsset list per stage, refresh cadence
Handoff SpecMQL / SQL definitions, SLA, disposition loop
Recycle PlanCold-lead criteria and reactivation triggers
KPIsMQL → SQL conversion, SQL → opportunity rate, time-to-handoff, disposition reasons

Process

  1. Map the buying stages for your motion; never assume one-size-fits-all
  2. Catalog the signals and weight them by historical conversion lift
  3. Design tracks per stage with explicit entry / exit, not just send schedules
  4. Build the scoring grid with sales co-sign; align on MQL / SQL definitions
  5. Spec the handoff with SLA, disposition loop, and recycle path
  6. Stand up the engagement refresh cycle - quarterly content audit + signal recalibration

Tips

  1. Time-based drip is anti-nurture - gate progression by signal, not by day
  2. Score is 2D, not 1D - fit and intent must remain separable
  3. A rejected MQL with no reason code is a broken loop - enforce disposition
  4. Refresh content quarterly or the program self-decays
  5. Cold leads aren't dead - long-cycle nurture frequently produces 10-20% of pipeline

Pairs With

  • demand-engine - Channel mix that originates the leads
  • journey-architect - Stages the nurture tracks attach to
  • enablement-forge - Produces the per-stage assets
  • customer-success - Inherits the lead at first value handoff

Keep looking

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