PM Dispatch: Free Product Management Tools for Product Managers

PM Dispatch is a free, browser-based toolkit built by a Chief Product Officer with 10+ years in mobile gaming. No account or login required.

RICE Prioritization Calculator

Score and rank your product backlog using the RICE framework: Reach, Impact, Confidence, and Effort. The free RICE calculator helps product managers make data-driven prioritization decisions.

A/B Test Sample Size Calculator

Calculate the minimum sample size needed to detect a statistically significant lift in your A/B test. Supports conversion rate, retention, and ARPU experiments with adjustable MDE and power settings.

Stats Lab: A/B Test Significance Calculator

Frequentist and Bayesian A/B test analysis for product managers. Test conversion rate significance, retention lift, and ARPU differences with p-value and confidence interval outputs.

Growth Tools: ROAS, LTV & Cohort Analysis

Free growth modeling tools: ROAS calculator, customer lifetime value (LTV) modeler, ad revenue projector, and cohort retention analysis. Designed for mobile game and app product managers.

PM Playbook: Product Management Guides

Step-by-step product management guides on sprint planning, writing a PRD, setting OKRs, conducting user research, and building a product roadmap. Written by an experienced CPO.

Daily PM Insight

One product management insight per day: frameworks, mental models, and tactical tips from experienced product leaders. Rotating library updated regularly.

Mobile Gaming News for Product Managers

Curated mobile gaming industry news relevant to product managers, including monetization trends, game launches, and market analysis.

PM Dispatch Newsletter

Free weekly newsletter on mobile game monetization, live ops strategy, and growth tactics for games PMs. Subscribe at pmdispatch.com.

Built by a CPO · Always free

The toolkit
for games PMs.

Free tools for A/B tests, ROAS, retention, and live ops. Built from 10 years running mobile games at scale.

20+

Tools

Frameworks

Free

Always

📮 Weekly newsletter on PM, growth, and mobile monetization

20+

Tools

Prioritization

Stats Lab

Growth Tools

A/B Sample Size

PM Playbook

Leaderboard

Daily Insight

About

RICE Scorer

Reach × Impact × Confidence ÷ Effort

Feature / Initiative	Reach %	Impact	Confidence	Effort	T-Shirt	RICE Score

Priority Ranking

ICE Scorer

Impact × Confidence × Ease: faster, lighter than RICE

Feature	Impact (1–10)	Confidence (1–10)	Ease (1–10)	ICE Score

ICE Ranking

Define Criteria & Weights

Weights must sum to 100. Customize criteria for your team.

Weight Distribution

Weighted Feature Scoring

Must Have

Critical

Could Have

Nice-to-have

Should Have

Important

Won't Have

Deferred

Kano Feature Classifier

Rate each feature on Functional (present) and Dysfunctional (absent) satisfaction.

Kano Quadrant

HIGH FUNCTIONAL

LOW FUNCTIONAL

DISSATISFIED

SATISFIED

DELIGHTERS

INDIFFERENT

PERFORMANCE

MUST-BE

Two-Proportion Z-Test

Control vs Treatment

Control Users

Control Conversions

Treatment Users

Treatment Conversions

Significance Level (α)

Test Type

Result

Bayesian A/B: Conversion

Beta-Binomial model

Prior: Beta(1,1), uninformative. Updates on observed data.

Control Users

Control Conversions

Treatment Users

Treatment Conversions

Minimum Detectable Effect (%)

Simulation samples

Posterior Distribution

Bayesian A/B: Retention

D1 / D7 / D30 retention test

Retention Day

Control Cohort Size

Control Retained

Treatment Cohort Size

Treatment Retained

Prior strength

Retention Posterior

Interpretation

ARPU Comparison

Mann-Whitney U + Bootstrap CI

Control ARPU ($)

Control Std Dev ($)

Control Users

Treatment ARPU ($)

Treatment Std Dev ($)

Treatment Users

Analysis Period (days)

ARPU Distribution Estimate

Revenue Impact

ROAS Curve Projection

Model cumulative ROAS over time across spend scenarios

CPI ($)

D0 ARPU ($)

LTV Multiplier (30d→180d)

Monthly Ad Budget ($)

D7 ARPU ($)

D30 ARPU ($)

D60 ARPU ($)

D180 ARPU ($)

Upload Cohort Data

CSV or XLSX · Each row = one acquisition date cohort

📂

Drop file here or click to browse

.csv · .tsv · .xlsx · .xls

Or paste CSV data

Configuration

Column detection is automatic; override if needed

Expected format:
Columns: Day · CPI · Installs · Spend · Revenue Day 0 · Revenue Day 1 … Revenue Day N · D0 ROAS · D1 ROAS …
Each row is one acquisition date cohort. Revenue columns are per-install or total (configure below).

Revenue columns are

Curve fit method

Projection horizon (days)

Breakeven target (%)

Budget scenarios, comma-separated ($)

📉 Retention adjustment (optional, refines curve)

D1 Retention (%)

D7 Retention (%)

D30 Retention (%)

Retention model

When enabled, the projected ROAS curve is multiplied by a retention survival curve fitted to your D1/D7/D30 inputs. Projections beyond your observed data window decay realistically instead of extrapolating linearly.

Cohorts

—

Total Installs

—

Avg CPI

—

Avg D0 ROAS

—

Avg D7 ROAS

—

Proj. Breakeven

—

ROAS Curve by Day (Avg across cohorts)

Actual observed + power-law projection

Revenue per Cohort by Day

Each line = one acquisition cohort

Budget Scenario Comparison

Projected total revenue at each monthly spend level

Projected ROAS Milestones

Fitted curve extrapolated from observed data

Day	Proj. ARPU/Install ($)	ROAS %	Status
Load data to see projections

Cohort Summary Table

One row per acquisition cohort: revenue by day, ROAS, CPI

No data loaded

Analysis & Recommendations

Load cohort data to see automated analysis.

LTV Calculator

Multiple models

Model

ARPU (per period)

Retention Rate (%)

Gross Margin (%)

Discount Rate (%)

Periods (months)

LTV Curve

Ad Revenue Estimator

DAU × Sessions × eCPM model

Daily Active Users (DAU)

Ad Sessions per DAU per day

Fill Rate (%)

Rewarded Video eCPM ($)

Interstitial eCPM ($)

Banner eCPM ($)

RV : Interstitial : Banner split

Revenue Breakdown

Cohort Revenue Model

Monthly install cohorts + retention curve

Monthly new installs

Month 1 conversion rate (%)

Avg first purchase ($)

Monthly repeat purchase rate (%)

Avg repeat purchase ($)

Monthly retention (%)

Months to project

Monthly Cumulative Revenue

Conversion Rate Test

Two-proportion Z-test power analysis

Baseline conversion rate (%)

Minimum Detectable Effect, relative (%)

Statistical power (%)

Significance level (α)

Test type

Daily traffic to experiment (%)

Total daily users (all variants)

Number of variants (incl. control)

Power Curve

Sample size vs detectable effect

Test Duration Scenarios

Retention Rate Test

D1 / D7 / D30 cohort sizing

Baseline retention rate (%)

Minimum Detectable Effect, absolute (pp)

Retention day

Power (%)

Alpha

Daily new installs (experiment)

Cohort Size vs Detectable Effect

Timeline

ARPU / Revenue Test

T-test for continuous revenue metric

Baseline ARPU ($)

ARPU std deviation ($) (typically 3–5× ARPU for games)

Minimum detectable ARPU lift ($)

Power

Alpha

Daily users in experiment

Revenue observation window (days)

Standard Deviation Impact

How SD affects required sample size

Revenue Guardrails

Multi-Variant Test Planner

Bonferroni-corrected sample sizes

Baseline metric value (%)

MDE relative (%)

Number of variants (excl. control)

Family-wise error rate (α)

Power

Daily users

Variant Comparison Table

⚠️ Multi-Variant Warnings

North Star Definition

North Star Metric name

Target value

Current value

Time period

Import Data

Paste CSV: period, metric1, metric2, … (header row required)

Leading Indicators

Define the metrics that predict your North Star. Weights must sum to 100.

North Star Score

—

Composite score

0Target

North Star Trend

Leading Indicators Over Time

Portfolio Insight

Arturo Ruiz Valdés

CPO

Chief Product Officer · PerBlue · Vancouver, WA

I've spent the last 10 years building products and systems in the games industry, designing features and digging into data to ship titles like Summoners War: Sky Arena, Disney Heroes: Battle Mode, and Legendary: Game of Heroes. Today I lead product strategy at PerBlue, working across our full portfolio, from early prototypes through live ops and monetization in scaled titles.

PM Dispatch came out of a simple frustration: every new role meant rebuilding the same spreadsheets and stat calculators from scratch. So I built the tool I wish had existed when I was starting out, all the prioritization frameworks, significance tests, and growth models a PM actually needs, in one place, free.

Years in Games

10+

Games Launched

Major Franchises

20+

Toolkit Tools

Mobile Gaming Monetization Live Ops Systems Design Prototyping Gacha Design Bayesian A/B Product Strategy P&L Game Design

Arturo Ruiz Valdés

Chief Product Officer · Game Industry

Building products that reach millions. PM Dispatch is the free toolkit I wish I had when I started.

Notable Franchises

Summoners War

Sky Arena

Disney Heroes

Battle Mode

Legendary

Game of Heroes

Connect

Got feedback?

Bug, idea, feature request, or just a thought. I read every message. PM Dispatch is built in public and your input shapes what gets built next.

The PM Dispatch Newsletter

A newsletter about live ops, mobile game monetization, and growth. Frameworks and case studies from a CPO who has shipped them in production.

No spam. Unsubscribe any time. Written by an actual PM, not AI.

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PM Dispatch: Free Product Management Tools for Product Managers

RICE Prioritization Calculator

A/B Test Sample Size Calculator

Stats Lab: A/B Test Significance Calculator

Growth Tools: ROAS, LTV & Cohort Analysis

PM Playbook: Product Management Guides

Daily PM Insight

Mobile Gaming News for Product Managers

PM Dispatch Newsletter

The toolkit
for games PMs.

Arturo Ruiz Valdés

Arturo Ruiz Valdés

The PM Dispatch Newsletter

Today's PM Challenge

Challenge complete!

The toolkitfor games PMs.

Arturo Ruiz Valdés

Arturo Ruiz Valdés

The PM Dispatch Newsletter

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Today's PM Challenge

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The toolkit
for games PMs.