neon-rutger/b2b-revops-skills/marketing-operations

SUBSCRIBER:  Email captured (form, event, content). No validation yet.
LEAD:        Email confirmed or enriched. Basic company data validated.
MQL:         Meets engagement + fit criteria (your scoring rules).
SAL:         Sales reviewed and accepted. Now tracked as pipeline.
SQL:         In an open opportunity. Discovery scheduled or completed.

FIT SCORE (Account-Level, 0-100)            ENGAGEMENT SCORE (Behavior-Level, 0-100)
├─ Company size (employee count, ARR)       ├─ Website visits (decay weekly)
├─ Geography (in-market?)                   ├─ Email clicks (not just opens)
├─ Industry / vertical match                ├─ Content consumption depth
├─ Technology stack (ICP signals)           ├─ Event attendance
└─ Growth stage fit                         └─ Trial activation (if applicable)
 
MQL = Fit ≥40 AND Engagement ≥30
 
This prevents routing "right customer, wrong time" and "active bad-fit" leads.
In practice, teams implementing this split report MQL acceptance improvements of 5-15 percentage points; one high-growth platform reported 62% to 81% (practice-based).

WHO OWNS SCORING:  One owner (often RevOps Manager or MarOps Lead). All
                   changes route through this person.
 
CHANGE CONTROL:    New scoring model = new version (v1, v2, v3).
                   Tag each version with date + what changed.
                   Never edit a live model; always create new version.
 
TESTING PROTOCOL:  Challenger model starts at 10-15% of inbound for 7 days.
                   Monitor: acceptance rate, SAL rate, rejection reasons.
                   If metric swing > 5%, hold or roll back.
                   If stable, expand to 50% for 7 days, then 100%.
 
ROLLBACK CRITERIA: Acceptance rate drops >10% below prior model
                   Rejection % changes >15% (new model calibration issue)
                   Inbound quality metrics trend down for 3+ days
                   → Rollback to prior model + open post-mortem
 
MONTHLY REVIEW:    Plot SAL rate, rejection %, lead source mix.
                   Spot degradation before quarterly calibration.
                   Early warning: if SAL% down trend-line, investigate
                   before waiting for quarter-end (source decay,
                   qualification creep, sales load change, etc).

MARKETING DELIVERS:
  MQL to sales within 1 hour (business hours)
  Data: name, email, company, title, fit score, engagement score, source
 
SALES COMMITS:
  Review + accept/reject within 24 hours
  Every rejection categorized: bad fit | low intent | wrong timing | duplicate | wrong role
 
HEALTHY ACCEPTANCE RATE: 60-80%
  Below 50% = scoring broken, audit fit/engagement thresholds or sales definition mismatch
  Above 85% = threshold too low, qualifying too broad; risk of routing unqualified leads
  Variance drivers: product type (niche software → higher acceptance), ACV (high-ACV → lower acceptance due to stricter fit), sales process maturity (defined process → lower acceptance due to clear criteria)
 
SPEED-TO-LEAD: Target <4 hours median (capture → first sales contact)
  Median win rates: 21% within 5 minutes, 2.3% when contact delayed 2+ hours (MIT/InsideSales, 2007).
  Speed-to-lead explains most variance in MQL→SQL conversion; formal SLA teams hit target 54.9% vs 29.5% without (Blazeo, 2026).

ROUND-ROBIN:     Simple rotation. Fair for new teams. Poor for territories.
TERRITORY-BASED: Geographic or segment assignment. Clear accountability.
ACCOUNT-BASED:   Route to AE owning parent account. Requires clean hierarchy.
CAPACITY-BASED:  Route to whoever has bandwidth. Prevents overload.
 
RECOMMENDATION (high-growth): Start territory-based. Add capacity weighting.
Migrate to account-based only with mature account hierarchy + TALs.

DISQUALIFY (hard remove):     No budget 12+ months | already using competitor
                              and happy | not involved in buying | 18+ month timeline
 
RECYCLE (back to nurture):    Not disqualified, just "not now"
                              Mark "nurture hold"; re-engage 1-2 week cadence
                              Re-score after 60 days; re-activate if engagement returns
 
Recycled leads show 8-15% reactivation rates within 6 months when re-engaged on trigger events (e.g. product update, budget cycle, practice-based).

1. FIRST TOUCH (awareness):       What brought them to you?         → 30% credit
2. LEAD CREATION (consideration):  What made them raise their hand?  → 20% credit
3. OPPORTUNITY CREATION (eval):    What triggered deal opening?      → 30% credit
4. CLOSE (decision):               Last marketing touch before buy   → 20% credit
 
Example: LinkedIn ad (first) → blog reads → webinar (MQL) → retarget (opp) → close $95K
  LinkedIn: 30% = $28.5K | Organic: 20% = $19K | Email: 30% = $28.5K | Retarget: 20% = $19K

MARKETING-SOURCED:    MQL created by marketing scoring → accepted by sales (SAL)
                      Usually 30-50% of total pipeline for inbound-heavy companies
 
MARKETING-INFLUENCED: Deals where marketing touched account at any point
                      Typically 70-90% of total pipeline for B2B SaaS
 
Use both. Sourced = lead generation. Influenced = pipeline development.
Different stakeholders care about different ones.

UTM TAXONOMY (standardize or attribution is theater):
  utm_source:   channel type (google, linkedin, email, event, partner)
  utm_medium:   media type (cpc, display, social, organic, referral)
  utm_campaign: structured ID (camp-2026-q1-demand-gen-eu)
  utm_content:  variant (ebook-v1, hero-image-v2)
 
GOVERNANCE: Enforce 20-30 campaign values per quarter max.
A high-growth firm had 847 different utm_campaign values. Useless.
 
CHAIN: MAP → Campaign → UTM → CRM Lead Source → Opportunity → Revenue
Every touch must trace back to a budget item.