metrics-dashboard

Name: metrics-dashboard
Author: phuryn

1.9kinstalls2.5kforks

How to install metrics-dashboard?

phuryn/pm-skills/metrics-dashboard

$npx -y skills add phuryn/pm-skills --skill metrics-dashboard

Installs into the current project.

Summary

Define and design a product metrics dashboard with key metrics, data sources, visualization types, and alert thresholds. Use when creating a metrics dashboard, defining KPIs, setting up product analytics, or building a data monitoring plan.

Files · 1

View on GitHub

SKILL.md

1	## Product Metrics Dashboard
2
3	Design a comprehensive product metrics dashboard with the right metrics, visualizations, and alert thresholds.
4
5	### Context
6
7	You are designing a metrics dashboard for $ARGUMENTS.
8
9	If the user provides files (existing dashboards, analytics data, OKRs, or strategy docs), read them first.
10
11	### Domain Context
12
13	Metrics vs KPIs vs NSM: Metrics = all measurable things. KPIs = a few key quantitative metrics tracked over a longer period. North Star Metric = a single customer-centric KPI that is a leading indicator of business success.
14
15	4 criteria for a good metric (Ben Yoskovitz, Lean Analytics): (1) Understandable — creates a common language. (2) Comparative — over time, not a snapshot. (3) Ratio or Rate — more revealing than whole numbers. (4) Behavior-changing — the Golden Rule: "If a metric won't change how you behave, it's a bad metric."
16
17	8 metric types: Vanity vs Actionable (only actionable metrics change behavior), Qualitative vs Quantitative (WHAT vs WHY — you need both; never stop talking to customers), Exploratory vs Reporting (explore data to uncover unexpected insights), Lagging vs Leading (leading indicators enable faster learning cycles, e.g. customer complaints predict churn).
18
19	5 action steps: (1) Audit metrics against the 4 good-metric criteria. (2) Update dashboards — ensure all key metrics are good ones. (3) Identify vanity metrics — be careful how you use them. (4) Classify leading vs lagging indicators. (5) Pick one problem and dig deep into the data.
20
21	For case studies and more detail: [Are You Tracking the Right Metrics?](https://www.productcompass.pm/p/are-you-tracking-the-right-metrics) by Ben Yoskovitz
22
23	### Instructions
24
25	1. Identify the metrics framework — organize metrics into layers:
26
27	North Star Metric: The single metric that best captures core value delivery
28
29	Input Metrics (3-5): The levers that drive the North Star
30
31	Health Metrics: Guardrails that ensure overall product health
32
33	Business Metrics: Revenue, cost, and unit economics
34
35	2. For each metric, define:
36
37	\| Metric \| Definition \| Data Source \| Visualization \| Target \| Alert Threshold \|
38	\|---\|---\|---\|---\|---\|---\|
39	\| [Name] \| [Exact calculation: numerator/denominator, time window] \| [Where the data comes from] \| [Line chart / Bar / Number / Funnel] \| [Goal value] \| [When to trigger an alert] \|
40
41	3. Design the dashboard layout:
42
43	```
44	┌─────────────────────────────────────────────┐
45	│ NORTH STAR: [Metric] — [Current Value] │
46	│ Trend: [↑/↓ X% vs last period] │
47	├──────────────────┬──────────────────────────┤
48	│ Input Metric 1 │ Input Metric 2 │
49	│ [Sparkline] │ [Sparkline] │
50	├──────────────────┼──────────────────────────┤
51	│ Input Metric 3 │ Input Metric 4 │
52	│ [Sparkline] │ [Sparkline] │
53	├──────────────────┴──────────────────────────┤
54	│ HEALTH: [Latency] [Error Rate] [NPS] │
55	├─────────────────────────────────────────────┤
56	│ BUSINESS: [MRR] [CAC] [LTV] [Churn] │
57	└─────────────────────────────────────────────┘
58	```
59
60	4. Set review cadence:
61	- Daily: Operational health (errors, latency, critical flows)
62	- Weekly: Input metrics and engagement trends
63	- Monthly: North Star, business metrics, OKR progress
64	- Quarterly: Strategic review and metric recalibration
65
66	5. Define alerts:
67	- What thresholds trigger investigation?
68	- Who gets alerted and through what channel?
69	- What's the expected response time?
70
71	6. Recommend tools based on the user's context:
72	- Amplitude, Mixpanel, PostHog for product analytics
73	- Looker, Metabase, Mode for SQL-based dashboards
74	- Datadog, Grafana for operational health
75
76	Think step by step. Save the dashboard specification as a markdown document.
77
78	---
79
80	### Further Reading
81
82	- [The Ultimate List of Product Metrics](https://www.productcompass.pm/p/the-ultimate-list-of-product-metrics)
83	- [The North Star Framework 101](https://www.productcompass.pm/p/the-north-star-framework-101)
84	- [The Product Analytics Playbook: AARRR, HEART, Cohorts & Funnels for PMs](https://www.productcompass.pm/p/the-product-analytics-playbook-aarrr)
85	- [AARRR (Pirate) Metrics: The 5-Stage Framework for Growth](https://www.productcompass.pm/p/aarrr-pirate-metrics)
86	- [The Google HEART Framework: Your Guide to Measuring User-Centric Success](https://www.productcompass.pm/p/the-google-heart-framework)
87	- [Funnel Analysis 101: How to Track and Optimize Your User Journey](https://www.productcompass.pm/p/funnel-analysis)
88	- [Are You Tracking the Right Metrics?](https://www.productcompass.pm/p/are-you-track

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Type

metrics-dashboard

1.9kinstalls2.5kforks

View on GitHub

How to install metrics-dashboard?

phuryn/pm-skills/metrics-dashboard

$npx -y skills add phuryn/pm-skills --skill metrics-dashboard

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	## Product Metrics Dashboard
2
3	Design a comprehensive product metrics dashboard with the right metrics, visualizations, and alert thresholds.
4
5	### Context
6
7	You are designing a metrics dashboard for $ARGUMENTS.
8
9	If the user provides files (existing dashboards, analytics data, OKRs, or strategy docs), read them first.
10
11	### Domain Context
12
13	Metrics vs KPIs vs NSM: Metrics = all measurable things. KPIs = a few key quantitative metrics tracked over a longer period. North Star Metric = a single customer-centric KPI that is a leading indicator of business success.
14
15	4 criteria for a good metric (Ben Yoskovitz, Lean Analytics): (1) Understandable — creates a common language. (2) Comparative — over time, not a snapshot. (3) Ratio or Rate — more revealing than whole numbers. (4) Behavior-changing — the Golden Rule: "If a metric won't change how you behave, it's a bad metric."
16
17	8 metric types: Vanity vs Actionable (only actionable metrics change behavior), Qualitative vs Quantitative (WHAT vs WHY — you need both; never stop talking to customers), Exploratory vs Reporting (explore data to uncover unexpected insights), Lagging vs Leading (leading indicators enable faster learning cycles, e.g. customer complaints predict churn).
18
19	5 action steps: (1) Audit metrics against the 4 good-metric criteria. (2) Update dashboards — ensure all key metrics are good ones. (3) Identify vanity metrics — be careful how you use them. (4) Classify leading vs lagging indicators. (5) Pick one problem and dig deep into the data.
20
21	For case studies and more detail: [Are You Tracking the Right Metrics?](https://www.productcompass.pm/p/are-you-tracking-the-right-metrics) by Ben Yoskovitz
22
23	### Instructions
24
25	1. Identify the metrics framework — organize metrics into layers:
26
27	North Star Metric: The single metric that best captures core value delivery
28
29	Input Metrics (3-5): The levers that drive the North Star
30
31	Health Metrics: Guardrails that ensure overall product health
32
33	Business Metrics: Revenue, cost, and unit economics
34
35	2. For each metric, define:
36
37	\| Metric \| Definition \| Data Source \| Visualization \| Target \| Alert Threshold \|
38	\|---\|---\|---\|---\|---\|---\|
39	\| [Name] \| [Exact calculation: numerator/denominator, time window] \| [Where the data comes from] \| [Line chart / Bar / Number / Funnel] \| [Goal value] \| [When to trigger an alert] \|
40
41	3. Design the dashboard layout:
42
43	```
44	┌─────────────────────────────────────────────┐
45	│ NORTH STAR: [Metric] — [Current Value] │
46	│ Trend: [↑/↓ X% vs last period] │
47	├──────────────────┬──────────────────────────┤
48	│ Input Metric 1 │ Input Metric 2 │
49	│ [Sparkline] │ [Sparkline] │
50	├──────────────────┼──────────────────────────┤
51	│ Input Metric 3 │ Input Metric 4 │
52	│ [Sparkline] │ [Sparkline] │
53	├──────────────────┴──────────────────────────┤
54	│ HEALTH: [Latency] [Error Rate] [NPS] │
55	├─────────────────────────────────────────────┤
56	│ BUSINESS: [MRR] [CAC] [LTV] [Churn] │
57	└─────────────────────────────────────────────┘
58	```
59
60	4. Set review cadence:
61	- Daily: Operational health (errors, latency, critical flows)
62	- Weekly: Input metrics and engagement trends
63	- Monthly: North Star, business metrics, OKR progress
64	- Quarterly: Strategic review and metric recalibration
65
66	5. Define alerts:
67	- What thresholds trigger investigation?
68	- Who gets alerted and through what channel?
69	- What's the expected response time?
70
71	6. Recommend tools based on the user's context:
72	- Amplitude, Mixpanel, PostHog for product analytics
73	- Looker, Metabase, Mode for SQL-based dashboards
74	- Datadog, Grafana for operational health
75
76	Think step by step. Save the dashboard specification as a markdown document.
77
78	---
79
80	### Further Reading
81
82	- [The Ultimate List of Product Metrics](https://www.productcompass.pm/p/the-ultimate-list-of-product-metrics)
83	- [The North Star Framework 101](https://www.productcompass.pm/p/the-north-star-framework-101)
84	- [The Product Analytics Playbook: AARRR, HEART, Cohorts & Funnels for PMs](https://www.productcompass.pm/p/the-product-analytics-playbook-aarrr)
85	- [AARRR (Pirate) Metrics: The 5-Stage Framework for Growth](https://www.productcompass.pm/p/aarrr-pirate-metrics)
86	- [The Google HEART Framework: Your Guide to Measuring User-Centric Success](https://www.productcompass.pm/p/the-google-heart-framework)
87	- [Funnel Analysis 101: How to Track and Optimize Your User Journey](https://www.productcompass.pm/p/funnel-analysis)
88	- [Are You Tracking the Right Metrics?](https://www.productcompass.pm/p/are-you-track

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