Solutions · B2B · SaaS

SaaS growth
that compounds.

Acquisition, activation, retention and expansion in SaaS are one connected P&L — not separate charts. We treat them that way.

Commercial model

ARR compounds. Sign-ups don't.

A SaaS business isn't a lead machine — it's a customer machine. Trial-to-paid activation, first-30-day usage, expansion and retention decide whether acquisition spend earns back at all. Marketing that ignores the second half is just an expensive sign-up funnel.

Why this hits EBITDA and risk

Payback is the number that decides burn.

  • CAC payback determines how much acquisition growth the business can safely absorb
  • NRR expansion above 100% is worth more than any acquisition efficiency lift
  • PLG signal fed into a sales-led motion without qualification burns AE capacity fast
  • Churn attributed back to source stops the business from re-acquiring the same wrong customer
Audience & operating model

Who this is built for.

B2B SaaS from Series A through late-stage — PLG, sales-led, or hybrid — where trial-to-paid, activation and expansion are the levers that decide unit economics. Typical stack is HubSpot or Salesforce, a product analytics tool (Amplitude, Mixpanel, PostHog), Google Ads, LinkedIn, and a growing content and SEO programme.

The SaaS cohort loop

Sign-ups are the start of the P&L, not the end.

  1. Cohort economics
    Paid ARR & NRR
  2. 01
    Acquisition cohort
    By channel, plan and use case
  3. 02
    Activation · first value
    PLG event or sales-led kick-off
  4. 03
    Trial → paid conversion
    The first place economics get real
  5. 04
    Expansion
    Seats, plan tier, cross-product
  6. 05
    Renewal · churn risk
    Predicted from usage and CS signal
  7. 06
    Reactivation · win-back
    Cancelled and downgraded cohorts
Illustrative loop. PLG lives or dies on activation and trial-to-paid; sales-led lives or dies on qualification and expansion. Attributed treats both honestly rather than pretending they are the same motion.
Payback economics

CAC payback decides how fast you can grow.

Cumulative contribution vs CAC
— Payback threshold
— Baseline cohort— After Attributed
Illustrative

Illustrative. Attributed models cumulative contribution per cohort against CAC — so growth commitments are made against a defensible payback curve, not against last-quarter's blended CAC.

Typical growth leaks

Where SaaS growth actually leaks.

  • Paid optimising to free sign-ups that never activate or convert
  • PLG onboarding designed for the demo, not the first successful use case
  • Sales-led motion firing on unqualified PLG signal — burning AE capacity
  • Expansion treated as a CS problem, not a marketing one
  • Churn measured monthly but never attributed back to acquisition source
  • Pricing-page experiments that ignore trial-to-paid impact
Connected system

What Attributed builds.

Acquisition + Activation
  • Paid and SEO measured to trial-to-paid and paid ARR, not sign-ups
  • PLG onboarding rebuilt around activation events that predict retention
  • Product-qualified lead scoring for sales handover
  • Sales enablement, pricing pages and demo flow tuned to actual objections
Retention + Intelligence
  • Cohort ARR curves by acquisition source, plan and use case
  • Expansion, cross-sell and price plan movement tracked as revenue events
  • Churn attribution back to source and onboarding pattern
  • Board-ready weekly view of paid ARR, expansion and NRR
Senior operators own it

Who does the work.

A senior SaaS strategist owns the paid, PLG and sales-led motions as one plan. A senior lifecycle operator owns activation and onboarding events. A senior RevOps voice owns CRM reconciliation, PQL scoring and cohort ARR reporting with your finance team.

Findings, Recommendations & Alerts

What Intelligence surfaces for SaaS.

  • Findings — cohorts where activation is collapsing; channels whose trials never reach paid
  • Recommendations — onboarding, PQL scoring and expansion changes tied to paid ARR impact
  • Alerts — activation regressions in a live cohort, expansion drop, cancel-reason clusters
  • Implementation Packs — activation event instrumentation, PQL scoring rebuild, expansion motion design
Implementation priorities

Where we go first.

  1. 1
    Define the activation event

    The specific in-product moment that predicts trial-to-paid and second-cycle retention.

  2. 2
    Rebuild onboarding around it

    Trim onboarding to what drives activation; everything after checkout is a retention programme.

  3. 3
    Rebuild PQL scoring and handover

    So AE capacity lands on the accounts most likely to convert, not the most recent sign-ups.

  4. 4
    Reprice paid targets against paid ARR

    Feed trial-to-paid and payback signals back to the ad platforms — bidding follows ARR, not sign-ups.

  5. 5
    Publish cohort ARR and NRR weekly

    Board-ready view with senior operator sign-off; churn attributed back to acquisition source.

QA & validation

How we know it moved.

  • Every activation and onboarding change ships with a holdout cohort so uplift is measurable
  • Cohort ARR views are reconciled with finance monthly, not implied from CRM only
  • PQL scoring rebuilds are reviewed with sales leadership before rollout
  • Every Implementation Pack has a success metric tied to paid ARR, activation rate or NRR
Success metrics

What we report against.

Primary
Paid ARR added per channel
Compounding
Net revenue retention by cohort
Efficiency
CAC payback in months
Activation
Trial-to-paid and activation rate by cohort
Connected system

Acquisition, activation, expansion — one P&L.

Acquisition

Paid and SEO priced against paid ARR by cohort, not free sign-ups.

Activation

Onboarding and PLG rebuilt around events that actually predict retention.

Retention

Expansion and churn programmes attributed back to acquisition source and plan choice.

Intelligence

Cohort ARR curves reconciled with CRM, product and finance — one weekly view.

Book a Growth Review.

Bring your PLG or sales-led SaaS metrics. We'll walk through the cohort economics your dashboard doesn't surface.