Strategy guides

Fully loaded cost to win one new paying customer or account.

Formula

(Sales + marketing + onboarding) ÷ new customers in period

Typical benchmark

SaaS: payback ≤12–18 mo often cited; varies by ACV and motion.

Gross profit expected from a customer over the relationship.

Formula

ARPA × gross margin % × avg customer lifetime (months)

Typical benchmark

LTV:CAC ≥3:1 is a common SaaS sanity check (segment-specific).

How much value you earn per dollar spent acquiring a customer.

Formula

LTV ÷ CAC

Typical benchmark

≥3:1 healthy for many SaaS; <1:1 unsustainable at scale.

Months until gross profit from a customer recovers CAC.

Formula

CAC ÷ (monthly gross profit per customer)

Typical benchmark

Enterprise often 18–24 mo; SMB/PLG often target ≤12 mo.

Revenue minus direct cost of delivery, as a percentage of revenue.

Formula

(Revenue − COGS) ÷ Revenue × 100

Typical benchmark

Software 70–85%+; services 40–60% depending on labour mix.

Normalised yearly value of recurring subscription contracts.

Formula

MRR × 12 (with consistent recognition rules)

Typical benchmark

Boards track ARR growth rate and net retention together.

Revenue kept from a cohort including expansion, minus churn and downgrades.

Formula

(Start ARR + expansion − churn − downgrade) ÷ Start ARR

Typical benchmark

Best-in-class B2B SaaS often >110–120% NRR.

Revenue retained before expansion — isolates churn/downgrade only.

Formula

(Start ARR − churn − downgrade) ÷ Start ARR

Typical benchmark

Enterprise SaaS often targets GRR ≥90%.

Share of customers who cancel in a period.

Formula

Churned logos ÷ logos at period start

Typical benchmark

Annual logo churn <5–10% for SMB; lower for enterprise.

Growth rate plus profit margin — efficiency of scaled SaaS.

Formula

YoY revenue growth % + EBITDA or FCF margin %

Typical benchmark

≥40 combined is a common public-SaaS benchmark.

Net burn required to generate each dollar of net new ARR.

Formula

Net burn ÷ net new ARR

Typical benchmark

≤1.5× often cited as efficient; >2× raises efficiency questions.

Share of new users who reach a defined “aha” or value action.

Formula

Users completing activation event ÷ new signups

Typical benchmark

Define activation per product; 25–40%+ is strong for PLG trials.

Median time from signup to first meaningful outcome.

Formula

Median hours/days to activation event

Typical benchmark

Shorter TTV correlates with higher retention in most B2B SaaS.

Share of a signup cohort still active after N days or weeks.

Formula

Active users in cohort at week N ÷ cohort size

Typical benchmark

Look for flattening curve; compare W4/W8/W12 by segment.

Daily active users divided by monthly active users — stickiness.

Formula

DAU ÷ MAU

Typical benchmark

Consumer 20%+ strong; B2B workflow tools vary widely by role.

Share of active users using features that predict retention.

Formula

Users of predictive feature ÷ WAU or MAU

Typical benchmark

Identify 2–3 “retention features” from cohort analysis.

Share of active users who would be “very disappointed” without the product.

Formula

Very disappointed responses ÷ total survey responses

Typical benchmark

≥40% in target segment suggests PMF (Ellis heuristic).

Whether cohort retention flattens above zero over time.

Formula

Visual: cohort % active over time

Typical benchmark

Flat tail >20–30% (varies) beats continuous decay to zero.

Inbound, word-of-mouth, or referral share of new users or pipeline.

Formula

Organic new customers ÷ total new customers

Typical benchmark

Rising organic share often accompanies PMF in early SaaS.

How intensely loyal users engage vs casual signups.

Formula

Power-user actions/week vs median user

Typical benchmark

Clear power-user cluster with 5–10× engagement vs median.

Share of available consultant hours billed to clients.

Formula

Billable hours ÷ available hours

Typical benchmark

Professional services often target 75–85% utilization.

Revenue minus direct delivery cost for a project or engagement type.

Formula

(Project revenue − direct labour & expenses) ÷ revenue

Typical benchmark

Consulting 50–65%+; agency 40–55% depending on model.

Revenue from existing clients vs total revenue.

Formula

Repeat client revenue ÷ total revenue

Typical benchmark

Growing repeat % reduces CAC dependence for services firms.

Weighted pipeline relative to next period quota.

Formula

Qualified pipeline value ÷ quota target

Typical benchmark

2–3× next-quarter coverage is a common services sales rule.

Share of qualified proposals that close won.

Formula

Won deals ÷ qualified proposals

Typical benchmark

Track by segment; 30–40% strong for qualified consulting pipeline.

Annual billings or revenue per delivery FTE.

Formula

Total revenue ÷ billable FTE count

Typical benchmark

Benchmark against firm size and rate card; watch utilisation interaction.

How users or customers discover and arrive at your product.

Formula

New visitors/signups/MQLs from channel (pick one primary)

Typical benchmark

One primary acquisition metric per channel or motion.

First experience of core value — user “gets it”.

Formula

% reaching defined activation event

Typical benchmark

Must match your NSM input, not generic signup.

Users or customers return and continue receiving value.

Formula

Cohort retention at D7/D30 or logo renewal rate

Typical benchmark

Leading indicator for NRR and LTV in subscription businesses.

Monetisation — conversion to paid, expansion, or transaction value.

Formula

Conversion rate, ARPA, or expansion ARR

Typical benchmark

Tie to pricing model (seat, usage, project).

Existing users bring new users or amplify growth.

Formula

Referral signups ÷ total signups or k-factor

Typical benchmark

Viral coefficient k>1 rare in B2B; track referral % trend.