Funnel: Conversion
Upstream: Martech Stack & Automation — instrumentation, tooling, and data plumbing. This page covers measurement execution.
The decision this page enables: whether traffic becomes revenue — or stalls between signup, activation, pricing, and the Sales handoff.
What conversion measurement is (and why it matters)
Section titled “What conversion measurement is (and why it matters)”Conversion measurement covers everything from first meaningful action (activation) through becoming a paying customer or qualified sales opportunity. It is the middle of the A→C→R funnel — where most leakage happens and where Marketing, Product, and Sales argue if definitions aren’t shared.
Conversion is not a single metric. It’s a stack of micro-funnels:
- Signup → activated user
- Activated user → paid (PLG / self-serve)
- Visitor → MQL → SQL (sales-led)
- Pricing page → checkout complete
If Acquisition measures who arrives, conversion measures who becomes real.
Core concepts
Section titled “Core concepts”The conversion micro-funnel (signup → paid)
Section titled “The conversion micro-funnel (signup → paid)”Self-serve and PLG motions share the same skeleton. Name each step; instrument each step; review weekly.
flowchart TD
s1[Signup / account created] --> s2[Onboarding started]
s2 --> s3[Activation event<br/>first value achieved]
s3 --> s4[Intent signal<br/>pricing view, limit hit]
s4 --> s5[Checkout started]
s5 --> s6[Paid / subscription active]
s3 --> s7[Churned before pay<br/>measure separately]
Activation is the hinge. Without a stable activation definition, signup→paid rate is unactionable noise. Activation should describe first value, not “logged in twice.” See Place: Logistics for time-to-first-value design patterns.
Activation funnel
Section titled “Activation funnel”| Stage | Example B2B event | Example B2C event | Why it matters |
|---|---|---|---|
| Signup complete | Work email verified, workspace created | Account + profile created | Top of conversion; segment by source |
| Onboarding started | Setup wizard step 1 | First-run tutorial opened | Detect drop-off before value |
| Activation (canonical) | ≥3 members + ≥1 doc in 14 days | ≥1 workout completed in 72h | Predicts retention and paid conversion |
| Habit / aha follow-on | 5+ docs in 30 days | 4+ workouts in 14 days | Expansion and upgrade predictor |
| Intent | Pricing page 2× in 7 days | Trial day 10 return | Sales-assist or paywall trigger |
Activation rate = activated users ÷ signups in cohort window (usually 7 or 14 days). Do not change the window mid-quarter.
Marketing-to-Sales handoff (MQL → SQL)
Section titled “Marketing-to-Sales handoff (MQL → SQL)”In sales-led and hybrid motions, conversion includes the boundary between Marketing and Sales. Treat it as a measured subprocess, not a meeting topic.
| Step | Definition | System of record | Owner |
|---|---|---|---|
| MQL | Meets firmographic + behavioral score | Marketing automation / CRM | Marketing |
| SAL / accepted | SDR acknowledges within SLA | CRM | Sales |
| SQL | Discovery confirms need, budget, authority, timeline | CRM | Sales |
| Disqualified | Rejected with reason code | CRM | Sales |
| Recycled | Enters nurture; may re-MQL later | MAP + CRM | Marketing |
SLA template:
| Handoff | Target | Escalation |
|---|---|---|
| MQL → first touch | ≤4 business hours | Manager alert at 8h |
| MQL → accept/reject | ≤48 hours | RevOps weekly report |
| SQL → discovery held | ≤5 business days | Pipeline review flag |
| Reject reason code | 100% required | Block save without code |
Alignment detail and PQL overlap in hybrid motions: PLG vs Sales-Led Measurement.
Pricing-page funnel
Section titled “Pricing-page funnel”Pricing is a conversion surface, not a Price strategy page. Measure it as a funnel:
Pricing page view → Plan selected (or toggle annual/monthly) → Checkout / upgrade modal opened → Payment info entered → Payment succeededTrack drop-off between each step and segment by:
- Acquisition source (paid vs organic quality differs)
- Plan tier viewed vs purchased
- Device (mobile checkout friction is common in B2C)
- Experiment variant (see Experimentation (A/B))
Pricing strategy lives under Price; this page is about measuring whether the pricing experience converts.
How to measure conversion — step by step
Section titled “How to measure conversion — step by step”- Write the activation definition jointly with Product and Marketing. One sentence + one SQL or event rule.
- Instrument the signup→paid micro-funnel in product analytics; verify with test accounts.
- For sales-led: document MQL and SQL criteria in CRM; add required reject reason codes.
- Instrument pricing steps as separate events (
pricing_view,plan_select,checkout_start,payment_success). - Build weekly conversion dashboard — activation rate, signup→paid, MQL→SQL, pricing step conversion.
- Segment every metric by acquisition channel from Acquisition — aggregate conversion hides channel quality.
- Review with Sales weekly on handoff metrics; with Product on activation experiments.
Templates
Section titled “Templates”Activation definition worksheet
Section titled “Activation definition worksheet”Product: [name]Motion: [PLG / sales-led / hybrid]Review cadence: [quarterly]
Activation statement: "A user is activated when they [verb] [object] within [N] days of signup."
Canonical event(s): Primary: [event_name + properties] Supporting: [optional guardrails]
Exclusions: [e.g., internal domains, test accounts, single-user workspaces]
Targets: Signup → activation rate: [___%] Activation → paid (30d): [___%] Activation → PQL (hybrid): [___%]
Validation (last 90 days): Signups: [___] Activated: [___] (rate: ___%) Paid within 30d: [___] (rate: ___% of activated) Correlation check: [activation vs D90 retention — should be positive]MQL → SQL handoff tracker
Section titled “MQL → SQL handoff tracker”Week of: [YYYY-MM-DD]
| Source | MQLs | Touched ≤4h | SQL | Accept % | Top reject reason || --- | --- | --- | --- | --- | --- || LinkedIn paid | | | | | || Organic | | | | | || Webinar | | | | | || Product PQL | | | | | |
SLA breaches (>48h no disposition): [list IDs]Marketing actions: [nurture fix, score tweak, landing change]Sales actions: [capacity, script, ICP clarification]Pricing funnel worksheet
Section titled “Pricing funnel worksheet”Period: [month]Segment filter: [all / mobile / channel X]
| Step | Users | Step conversion | Cumulative || --- | --- | --- | --- || Pricing page view | | — | 100% || Plan selected | | | || Checkout started | | | || Payment submitted | | | || Payment succeeded | | | |
Largest drop: [step → step] at [__%]Hypothesis: [friction, trust, price shock, mobile UX]Experiment backlog: [link to A/B test doc]Metrics to track
Section titled “Metrics to track”| Metric | B2B SaaS (healthy) | B2C app (healthy) | Notes |
|---|---|---|---|
| Signup → activation (14d) | 25–45% | 35–55% | Below 20% → onboarding or wrong traffic |
| Activation → paid (30d) | 8–18% freemium | 15–30% trial | Segment by channel |
| Time to activation | Median 1–3 days | Median <24 hours | Long tail kills trial conversion |
| Pricing view → paid | 5–12% | 8–20% | Depends on paywall placement |
| MQL → SQL acceptance | 25–40% | N/A (B2B partnerships only) | <20% → definition or targeting broken |
| SQL → opportunity | 60–80% | — | Discovery quality |
| Trial → paid (before expiry) | 15–25% B2B trial | 40–70% mobile trial | Clock starts at signup or first open — pick one |
| Checkout abandonment | Track absolute drop | Mobile often 2× desktop | Payment errors in separate bucket |
Pipeline and win rate downstream: Sales Analytics & Forecasting.
Conversion diagnostics cheat sheet
Section titled “Conversion diagnostics cheat sheet”When a metric moves, check the most likely layer first:
| Symptom | Check first | Then |
|---|---|---|
| Activation down, traffic flat | Onboarding flow, Place: Logistics | Acquisition channel mix shift |
| Pricing views up, paid flat | Price anchoring, plan clarity, Price | Payment errors, mobile UX |
| MQL up, SQL flat | MQL score too loose, SLA breaches | Sales capacity, ICP drift |
| Trial→paid up, NRR flat | Wrong users converting early | Retention quality by channel |
| Checkout starts up, success flat | Stripe/billing failures, tax fields | Trust signals on payment page |
Worked examples
Section titled “Worked examples”SaaS workspace (B2B) — hybrid conversion
Section titled “SaaS workspace (B2B) — hybrid conversion”Context: Freemium workspace; SMB self-serve, 50+ employees routed to sales. Activation = ≥3 members + ≥1 doc in 14 days.
PLG conversion funnel (monthly):
| Stage | Volume | Rate |
|---|---|---|
| Signups (work email) | 4,200 | — |
| Activated | 1,260 | 30% |
| Viewed pricing (2× in 7d) | 378 | 30% of activated |
| Started checkout | 95 | 25% of pricing viewers |
| Self-serve paid | 34 | 36% of checkout starts |
Sales-led conversion (same month):
| Stage | Volume | Rate |
|---|---|---|
| MQL (demo + ABM) | 85 | — |
| SQL (discovery held) | 28 | 33% accept |
| Opportunity | 19 | 68% of SQL |
| Closed-won | 6 | 32% win rate |
Handoff issue found: 22 MQLs sat >48h without disposition — accept rate artificially low. RevOps added SLA dashboard; following week accept rate moved from 28% to 35% with same lead quality.
Pricing funnel issue: Mobile pricing views (18% of total) converted at 4% vs desktop 11%. Responsive checkout fix queued before any paid acquisition scale.
Consumer fitness app (B2C) — trial conversion
Section titled “Consumer fitness app (B2C) — trial conversion”Context: 14-day trial, no sales team except corporate wellness. Activation = 1 workout completed in first 72 hours.
Signup → paid micro-funnel:
| Stage | Volume | Rate |
|---|---|---|
| Installs → accounts | 28,000 → 22,400 | 80% |
| Activated (1 workout in 72h) | 11,200 | 50% of accounts |
| Opened paywall (trial day 7+) | 4,480 | 40% of activated |
| Started subscription flow | 2,240 | 50% |
| Paid before trial end | 1,680 | 75% of started |
Diagnosis: Install→account at 80% is acceptable; 50% activation is the lever — users who skip first workout rarely pay. Lifecycle push on day 1 (“8-minute starter”) tested; activation rises to 56% in two weeks, trial→paid follows +4 points.
Pricing note: Annual plan toggle on pricing screen raised payment succeeded by 9% among users who reached checkout — measured as pricing funnel experiment, not brand change.
Corporate wellness (sales-led slice): 12 MQLs / quarter from HR downloads; 4 SQL after discovery; 1 closed-won — tracked on same conversion dashboard but excluded from PLG signup→paid targets to avoid blending motions.
Common pitfalls
Section titled “Common pitfalls”- Activation = “signed in.” Login is not value; it correlates weakly with retention.
- MQL inflation. Lowering the score to hit volume targets destroys Sales trust and accept rate.
- No reject reason codes. Marketing can’t fix sources without structured feedback.
- Pricing page as PDF. Uninstrumented pricing on sales calls only — you lose self-serve conversion data.
- Blending PLG and SLG conversion rates. One headline “conversion rate” hides that enterprise deals convert on different timelines.
- Optimizing checkout before activation. Fix Place: Logistics first; checkout tests on unactivated users waste cycles.
Tools / further reading
Section titled “Tools / further reading”- Product analytics: Amplitude, Mixpanel, PostHog — funnel steps, activation cohorts, holdout-friendly event export.
- CRM: HubSpot, Salesforce — MQL/SQL stages, SLA reports, reject reason dashboards.
- Session replay: FullStory, Hotjar, LogRocket — pricing and onboarding drop-off diagnosis (sample responsibly for privacy).
- Billing: Stripe, Chargebee, RevenueCat — payment succeeded vs checkout started reconciliation.
- Sales engagement: Outreach, Salesloft — time-to-first-touch on MQLs.
- Canonical read: Hooked ( Nir Eyal ) — habit formation tied to activation design; The SaaS Sales Method ( Jacco van der Kooij ) — SQL and discovery discipline for B2B handoffs.
Cross-links
Section titled “Cross-links”- Funnel: Overview — A→C→R map and decision tree.
- Funnel: Acquisition — channel quality feeding conversion.
- Funnel: Retention — what happens after paid.
- Place: Logistics — delivery, onboarding, time-to-first-value.
- Price — pricing model and packaging strategy.
- PLG vs Sales-Led Measurement — motion-specific definitions.
- Sales Analytics & Forecasting — pipeline after SQL.
- Experimentation (A/B) — testing conversion changes safely.