lead-nurture

name	lead-nurture
description	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.

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

Letter	Stage	The Question
N	Needs Mapping	What buying-stage needs does the lead currently have evidence of?
U	Understand Intent	What behavioral and explicit signals map to which stage?
R	Route to Track	Which nurture track does the lead enter, and on what entry criteria?
T	Trigger Progression	What signal moves the lead to the next step (or back)?
U	Upgrade to Sales	What threshold defines MQL → SQL handoff, and what's the SLA?
R	Recycle Cold	When does the lead exit the active track into long-cycle nurture?
E	Engagement Refresh	How is content kept current and personalization kept honest?

Buying-Stage Nurture Tracks

Stage	Lead State	Track Goal	Cadence
Unaware	Discovered category, no problem framing	Frame the problem	Bi-weekly
Aware	Acknowledges problem, exploring	Reframe with our POV	Weekly
Considering	Evaluating vendors	Differentiate + de-risk	2-4×/week, behavior-gated
Decision	Short-listed	Accelerate to demo / sales	Daily during active window
Dormant / Lost	No activity 60+ days OR closed-lost	Reactivate on signal	Quarterly check-in + signal trigger

Intent Signals

A robust nurture system reads explicit and behavioral signals together:

Type	Example	Implication
Explicit	Form fill, demo request, pricing page submit	High-confidence stage signal
Behavioral - high	Pricing page, comparison page, case study deep read	Considering or Decision
Behavioral - medium	Webinar registration, ebook download	Aware → Considering
Behavioral - low	Blog visit, newsletter open	Unaware → Aware
Decay	No engagement 30+ days	Re-route to lighter cadence

Lead Scoring Design

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

Fit \ Intent	Low	Medium	High
High	Marketing nurture	Sales-assist	SQL - immediate
Medium	Standard nurture	Behavior-gated	SDR-triggered
Low	Newsletter only	Selective nurture	Manual triage

MQL → SQL Handoff

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

Element	Spec
MQL Definition	Fit + intent threshold, with named behavioral triggers
SQL Definition	Sales-acceptance criteria written by sales
Handoff SLA	First sales touch within X hours of MQL
Disposition Loop	Sales must reason-code rejected MQLs; feeds scoring tuning
Recycle Path	Rejected MQLs return to specific track, not a black hole

Output

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

Artifact	Description
Track Map	Named tracks with entry / exit criteria and goal
Signal Catalog	Explicit + behavioral signals with weights
Scoring Grid	Fit × intent matrix with routing rules
Content Plan	Asset list per stage, refresh cadence
Handoff Spec	MQL / SQL definitions, SLA, disposition loop
Recycle Plan	Cold-lead criteria and reactivation triggers
KPIs	MQL → 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