Top 3 Customer Health Tools for Product Teams
Compare NPS, PMF, and A/B Test tools. Measure loyalty, validate product-market fit, and run statistically sound experiments.
Revenue is a lagging indicator. By the time revenue declines, the customer health problems that caused it are months old. These three tools measure leading indicators: Net Promoter Score for loyalty, the Sean Ellis test for product-market fit, and A/B test planning for experiment rigor. Together they tell you whether your product is trending toward growth or toward churn.
NPS Calculator
QuickNet Promoter Score is the gold standard for measuring customer loyalty and predicting growth. This calculator takes your survey responses, computes your NPS, and benchmarks it against SaaS industry averages by company stage and segment. Product leaders use NPS to track satisfaction trends, set customer health OKRs, and build the case for retention investments.
IC PM, Senior PM, Head of Product, VP Product, CPO
Number of promoters (9-10), passives (7-8), and detractors (0-6)
NPS score (-100 to 100), benchmark comparison, health assessment
PMF Calculator
QuickThe Sean Ellis test asks users how they would feel if they could no longer use your product. If 40% or more say "very disappointed," you have product-market fit. Product leaders use this metric to determine whether to double down on growth or pivot back to discovery. This calculator gives you the PMF percentage plus actionable guidance based on where you fall on the spectrum.
IC PM, Senior PM, Head of Product, VP Product, CPO
Survey response counts: very disappointed, somewhat disappointed, not disappointed
PMF percentage, pass/fail assessment, stage-specific recommendations
A/B Test Calculator
StandardRunning experiments without statistical rigor wastes engineering resources and leads to false conclusions. This calculator handles both pre-test sample size planning and post-test significance analysis. Product leaders use it to ensure experiments have adequate power before launch and to make confident ship/kill decisions when results come in, reducing the risk of shipping features that don not actually move metrics.
IC PM, Senior PM, Head of Product
Baseline conversion rate, minimum detectable effect, significance level, traffic volume
Required sample size, test duration estimate, statistical significance result
Summary Comparison
| # | Tool | Complexity | Best For | Use Case | |
|---|---|---|---|---|---|
| 1 | 📊NPS Calculator | Quick | IC PM, Senior PM, Head of Product +2 | Benchmark customer loyalty against industry standards and track trends over time. | Try it → |
| 2 | 🎯PMF Calculator | Quick | IC PM, Senior PM, Head of Product +2 | Determine if you should invest in growth or return to discovery. | Try it → |
| 3 | 🔬A/B Test Calculator | Standard | IC PM, Senior PM, Head of Product | Ensure experiments are statistically valid before making ship/kill decisions. | Try it → |
Best Tool by Role
Verdict
Track NPS quarterly for loyalty trends. Run the PMF test before major growth investments. Use the A/B Test Calculator to ensure every experiment has adequate statistical power.
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