Customer HealthTop List3 tools

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.

1
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NPS Calculator

Quick

Net 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.

Best for

IC PM, Senior PM, Head of Product, VP Product, CPO

You enter

Number of promoters (9-10), passives (7-8), and detractors (0-6)

You get

NPS score (-100 to 100), benchmark comparison, health assessment

Try NPS Calculator →
2
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PMF Calculator

Quick

The 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.

Best for

IC PM, Senior PM, Head of Product, VP Product, CPO

You enter

Survey response counts: very disappointed, somewhat disappointed, not disappointed

You get

PMF percentage, pass/fail assessment, stage-specific recommendations

Try PMF Calculator →
3
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A/B Test Calculator

Standard

Running 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.

Best for

IC PM, Senior PM, Head of Product

You enter

Baseline conversion rate, minimum detectable effect, significance level, traffic volume

You get

Required sample size, test duration estimate, statistical significance result

Try A/B Test Calculator →

Best Tool by Role

IC PM
Senior PM
Head of Product
VP Product
CPO

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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