Customer Satisfaction Score
CSAT measures how satisfied customers are with a specific interaction, feature, or experience. Fast to collect, easy to act on.
CSAT
Formula
CSAT = (Satisfied responses ÷ Total responses) × 100Satisfied = scores of 4 or 5 on a 1–5 scale
Calculator
Benchmarks
0%50%100%
Below 60% — Poor60–79% — Fair80%+ — Strong
Industry average: 75–85% across SaaS. Aim for 80%+ as a baseline. Below 60% signals product or service issues that need urgent attention.
When to use it
CSAT is best after a specific interaction — a support ticket, onboarding session, or feature release. It’s transactional by nature. Don’t use it as your only satisfaction measure — pair it with NPS for strategic direction and CES for friction detection. Run it consistently so you can spot trends, not just snapshots.
Net Promoter Score
NPS measures loyalty and likelihood to recommend. It segments customers into Promoters, Passives, and Detractors to reveal your growth potential.
NPS
Formula
NPS = % Promoters (9–10) − % Detractors (0–6)Passives (7–8) are excluded. Score ranges from −100 to +100.
Calculator — enter respondent counts per score
0 — Not at all likely10 — Extremely likely
0
Detractors (0–6)
0
Passives (7–8)
0
Promoters (9–10)
Benchmarks
Below 0 — Danger zone0–29 — Room to grow30–69 — Healthy70+ — World class
SaaS average: ~31. Compare against your own trend first, then industry benchmarks.
What to do with your score
Detractors — Close the loop fast. Survey them. Fix root causes.
Passives — Convert them. Find the one thing holding them back.
Promoters — Activate them. Referrals, case studies, community.
Passives — Convert them. Find the one thing holding them back.
Promoters — Activate them. Referrals, case studies, community.
Customer Effort Score
CES measures how easy it is for customers to accomplish a task. Low effort = high loyalty. The single strongest predictor of churn.
CES
Formula
CES = Sum of all effort scores ÷ Total responsesTypically on a 1–7 scale. Higher = more effort (worse).
Calculator
Benchmarks (1–7 scale)
1–3 — Low effort (great)3–5 — Moderate effort5–7 — High effort (fix this)
Key insight: 96% of high-effort customers become disloyal. CES predicts churn better than CSAT. Ask it right after key product moments — onboarding, support, checkout.
Churn Rate
The percentage of customers or revenue lost in a period. The single most important metric for subscription products. Every point of churn compounds.
Churn
Customer churn
Churn Rate = (Customers lost ÷ Customers at start) × 100MRR churn
MRR Churn = (MRR lost ÷ MRR at start) × 100Customer churn calculator
MRR churn calculator
Benchmarks
Under 2% monthly — Excellent2–5% monthly — Acceptable early-stage5%+ monthly — Critical
The compounding reality: 5% monthly churn = ~46% annual churn. At that rate you replace half your customer base every year just to stand still. Even reducing churn from 3% to 2% monthly can double your long-term revenue.
Retention Rate
The percentage of customers who stay over a given period. The inverse of churn — and the truest signal of product-market fit.
Retention
Formula
Retention Rate = ((Customers at end − New customers) ÷ Customers at start) × 100Calculator
Benchmarks
Below 85% annual — Concern85–93% annual — Average93%+ annual — Strong
PMF signal: Retention is the most honest measure of product-market fit. If your retention curve flattens (even at 30%), you have a core audience. If it keeps declining to zero, you have a retention problem — not a growth problem.
DAU / MAU Ratio
The stickiness ratio. Shows what proportion of monthly active users engage daily. High DAU/MAU = habitual product.
Stickiness
Formula
Stickiness = (Daily Active Users ÷ Monthly Active Users) × 100A ratio of 20%+ is generally considered good. WhatsApp / Slack approach 50%+.
Calculator
Benchmarks
Under 10% — Low engagement10–20% — Moderate20%+ — Strong habit formation
Context is everything: A project management tool used weekly may have a 14% ratio and be healthy. A social app at 14% has a problem. Set your benchmark based on expected usage frequency.
Time to Value
How long it takes a new user to reach their first meaningful outcome. The shorter TTV, the more likely they are to activate, retain, and expand.
TTV
Formula
Average TTV = Sum of (Value moment − Sign-up timestamp) ÷ Total usersDefine your “value moment” first — first export, first invite sent, first result achieved.
Calculator (in hours)
What good looks like
Under 1 hour — Excellent1–24 hours — Acceptable24+ hours — Activation risk
The aha moment: Define your value moment precisely before measuring. The best product teams work backwards — they identify what makes users stick, then optimise everything to get new users there faster.
How to reduce TTV
1. Define the value moment clearly — not “signed up” but “completed first X”.
2. Remove steps — every click before value is a risk of drop-off.
3. Pre-fill, pre-configure, pre-populate — reduce the work users have to do.
4. Use progressive onboarding — show value first, collect details later.
5. Measure cohort by cohort — TTV should trend down over time as you improve.
2. Remove steps — every click before value is a risk of drop-off.
3. Pre-fill, pre-configure, pre-populate — reduce the work users have to do.
4. Use progressive onboarding — show value first, collect details later.
5. Measure cohort by cohort — TTV should trend down over time as you improve.