Platform

AI

AI Agents
Sense, decide, and act faster than ever before
AI Visibility
See how your brand shows up in AI search
AI Feedback
Distill what your customers say they want
Amplitude MCP
Insights from the comfort of your favorite AI tool

Insights

Product Analytics
Understand the full user journey
Marketing Analytics
Get the metrics you need with one line of code
Session Replay
Visualize sessions based on events in your product
Heatmaps
Visualize clicks, scrolls, and engagement

Action

Guides and Surveys
Guide your users and collect feedback
Feature Experimentation
Innovate with personalized product experiences
Web Experimentation
Drive conversion with A/B testing powered by data
Feature Management
Build fast, target easily, and learn as you ship
Activation
Unite data across teams

Data

Warehouse-native Amplitude
Unlock insights from your data warehouse
Data Governance
Complete data you can trust
Security & Privacy
Keep your data secure and compliant
Integrations
Connect Amplitude to hundreds of partners
Solutions
Solutions that drive business results
Deliver customer value and drive business outcomes
Amplitude Solutions →

Industry

Financial Services
Personalize the banking experience
B2B
Maximize product adoption
Media
Identify impactful content
Healthcare
Simplify the digital healthcare experience
Ecommerce
Optimize for transactions

Use Case

Acquisition
Get users hooked from day one
Retention
Understand your customers like no one else
Monetization
Turn behavior into business

Team

Product
Fuel faster growth
Data
Make trusted data accessible
Engineering
Ship faster, learn more
Marketing
Build customers for life
Executive
Power decisions, shape the future

Size

Startups
Free analytics tools for startups
Enterprise
Advanced analytics for scaling businesses
Resources

Learn

Blog
Thought leadership from industry experts
Resource Library
Expertise to guide your growth
Compare
See how we stack up against the competition
Glossary
Learn about analytics, product, and technical terms
Explore Hub
Detailed guides on product and web analytics

Connect

Community
Connect with peers in product analytics
Events
Register for live or virtual events
Customers
Discover why customers love Amplitude
Partners
Accelerate business value through our ecosystem

Support & Services

Customer Help Center
All support resources in one place: policies, customer portal, and request forms
Developer Hub
Integrate and instrument Amplitude
Academy & Training
Become an Amplitude pro
Professional Services
Drive business success with expert guidance and support
Product Updates
See what's new from Amplitude

Tools

Benchmarks
Understand how your product compares
Templates
Kickstart your analysis with custom dashboard templates
Tracking Guides
Learn how to track events and metrics with Amplitude
Maturity Model
Learn more about our digital experience maturity model
Pricing
LoginContact salesGet started

AI

AI AgentsAI VisibilityAI FeedbackAmplitude MCP

Insights

Product AnalyticsMarketing AnalyticsSession ReplayHeatmaps

Action

Guides and SurveysFeature ExperimentationWeb ExperimentationFeature ManagementActivation

Data

Warehouse-native AmplitudeData GovernanceSecurity & PrivacyIntegrations
Amplitude Solutions →

Industry

Financial ServicesB2BMediaHealthcareEcommerce

Use Case

AcquisitionRetentionMonetization

Team

ProductDataEngineeringMarketingExecutive

Size

StartupsEnterprise

Learn

BlogResource LibraryCompareGlossaryExplore Hub

Connect

CommunityEventsCustomersPartners

Support & Services

Customer Help CenterDeveloper HubAcademy & TrainingProfessional ServicesProduct Updates

Tools

BenchmarksTemplatesTracking GuidesMaturity Model
LoginSign Up

Good Product Team/Bad Product Team

Good product teams are customer obsessed, understand the value of focus, and know that the product is always evolving.
Insights

Jan 23, 2018

8 min read

Justin Bauer

Justin Bauer

Former Chief Product Officer, Amplitude

Good Product Team/Bad Product Team

As VP of Product at Amplitude, I get the opportunity to work with hundreds of different products teams every year — ranging from startups with only a handful of engineers to large enterprises with thousands of PMs. Each of them works with Amplitude because they believe we will help them build a better product.

But this naturally raises a simple question: why do companies need help building better products?

There are many reasons for this, but at its core it comes down to the fact that building product is hard, and most companies are not great at it. And the traditional ways of building and delivering product just don’t cut it in today’s product-led era.

So in the mode of Ben Horowitz’s classic essay Good PM/Bad PM, I’ve captured my thoughts on what I believe makes a good product team vs a bad product team.

On solving customer’s problems…

Good product teams are customer obsessed. They interact with their customers directly to get first hand feedback. They bring the voice of the user right into the heart of decision-making at every stage of the process. They ensure that everyone in product development — PM, Design and Engineering — are experts on the customer.

Bad product teams outsource customer understanding. They rely on second-hand feedback and see “The Business” as a proxy for customers, gathering requirements through antiquated methods like MRDs. They rely upon analysts to answer every question regarding user behavior, which delays decisions by days or even weeks of time. PMs will then ask for more dashboards, but whenever they need to explain why a metric changed they say they’ll “get back to that next meeting” (and they never do).

Good product teams have a clear intention behind the customer problems they are solving

Good product teams learn how to fish vs having analysts fish for them. Bad product teams make decisions based on a best guess from recent and anecdotal evidence, reserving analytics resources only for ‘mission critical’ questions. They rely on the noisiest qualitative sources, like sales, customer support or app reviews, and can’t see the forest from the trees.

Good product teams don’t build for their customer today, they build for who their customer will become. They use data to inform product decisions, not validate decisions they’ve already made. They use product analytics to know how users are actually using their product, not just rely on their best guess assumptions. They go beyond vanity metrics and have product analytics solutions that allow them to dive deep into their data to understand their customer’s journey.


On testing and refining…

Bad product teams lack a product strategy, or if they have one that strategy is not clearly delivered throughout their organization. They have a culture of being very reactive to the whims of upper management, which destroys entrepreneurial spirit and drive. They require 6 levels of reviews on every decision before they move forward because of dependencies and ‘turf wars’.

Good product teams understand the value of focus. They understand that having a product strategy means saying no many more times than saying yes. They have intention in their actions based on their core understanding of the problems they need to solve for. They set an aggressive 10x vision, but give the teams closest to the customer autonomy to figure out how to achieve that vision.

Bad product teams use agile as an excuse to not have a vision.

Good product teams iterate obsessively to test and refine their vision

Good product teams execute against their vision in 10% increments. They know that while you cannot substitute vision with data, you can better understand customer needs and test hypotheses about what customers want by utilizing data. They identify the riskiest assumptions and create experiments to test those assumptions. They build minimal valuable products that are narrative-complete, not feature complete. They constantly ask themselves if what they are focused on will have the biggest impact for their business.

Bad product teams claim because they’re agile they move quickly, but still take 3 months to release a feature. They work in sprints, but nothing reaches the customer at the end of the sprint. They say they are lean, but instead of building a skateboard, they build a car without a steering wheel.

Good product teams are optimized for learning: they understand that the first attempt is always wrong, and can iterate quickly because they have access to product analytics data to discover what is and isn’t working for the customer. They recognize that to innovate means taking on the risk of breaking what you have today. Bad product teams live in fear of losing what they have today.

Bad product teams make excuses to not ship quickly, and try to get it right on the first try. They say they celebrate failure, but don’t give people the room to explore. Good product teams experiment patiently, accept failures and double down when they see customer delight.


On measuring success and failure…

Good product teams measure themselves by outcomes; engagement, stickiness and retention, and can ultimately tie those to revenue generation. Bad product teams measure themselves by outputs; story point velocity, lines of code shipped or features delivered. Cost, schedule and scope rule the day.

Bad product teams follow a strict release schedule, and are always behind. Their PMs see impact as having a thoroughly documented user story. When they finally complete their project, they move onto the next thing and never look back because “they’re done”.

Good product teams measure success and failure based on customer outcomes

Good product teams know that product is always evolving — learning is never done and they put processes in place to make sure they come back to what’s important, even if that means deprecating a feature or product. Bad product teams instead operate in feature factories, constantly chasing the next shiny object in hopes of finding a silver bullet to save their product.

Good product teams understand that products are built with lead bullets — that you can’t 80/20 your way to everything and that there are certain things that you have to be better at than everyone else.

Bad product teams are organized in functional silos and point fingers at each other when “behind.” They lack clarity around role definition — PMs and Designers believe they need to “keep engineers busy.” Good product teams are organized around a shared view of the customer and common definitions of success. They clearly define who is accountable for what between PMs, Design and Engineering.

Good product teams articulate their goals ahead of time and share the impact that their work has against those goals (good and bad) to the entire company. Bad product teams celebrate shipping only, but don’t take the time to articulate impact. They believe that looking at product analytics is the responsibility of the PM team only, not the broader team.

Good product teams take the time to define a core set of critical metrics that matter for their customer. Everyone understands how their work impacts the broader goal for the company and what is most important to achieve. Bad product teams define every product metric as a KPI, effectively making nothing important.

Do you have examples from product teams you’ve been a part of? I’d love to hear them. Please share in the comments below.

Learn more about how to get into product management and product management best practices.


Comments

Sharon Sciammas: Thanks for sharing your experience I could not agree more. The question is how to you tranform bad behavior to a good one? most ppl what to their best. bad team do know that they are bad. How do you take a bad team and help them grow (especially when they are not aware of being bad)

Shane Williamson: Nailed it 🙂

About the author
Justin Bauer

Justin Bauer

Former Chief Product Officer, Amplitude

More from Justin

Justin Bauer is a former Chief Product Officer at Amplitude, where he strove to make it easy for companies to make better decisions from their data. He’s a 2x entrepreneur as well as an alumnus of McKinsey, Stanford GSB and Carleton College.

More from Justin
Topics
Platform
  • Product Analytics
  • Feature Experimentation
  • Feature Management
  • Web Analytics
  • Web Experimentation
  • Session Replay
  • Activation
  • Guides and Surveys
  • AI Agents
  • AI Visibility
  • AI Feedback
  • Amplitude MCP
Compare us
  • Adobe
  • Google Analytics
  • Mixpanel
  • Heap
  • Optimizely
  • Fullstory
  • Pendo
Resources
  • Resource Library
  • Blog
  • Product Updates
  • Amp Champs
  • Amplitude Academy
  • Events
  • Glossary
Partners & Support
  • Contact Us
  • Customer Help Center
  • Community
  • Developer Docs
  • Find a Partner
  • Become an affiliate
Company
  • About Us
  • Careers
  • Press & News
  • Investor Relations
  • Diversity, Equity & Inclusion
Terms of ServicePrivacy NoticeAcceptable Use PolicyLegal
EnglishJapanese (日本語)Korean (한국어)Español (Spain)Português (Brasil)Português (Portugal)FrançaisDeutsch
© 2025 Amplitude, Inc. All rights reserved. Amplitude is a registered trademark of Amplitude, Inc.

Recommended Reading

article card image
Read 
Customers
The Future is Data-Driven: Introducing the Winners of the Ampy Awards 2025

Dec 2, 2025

6 min read

article card image
Read 
Insights
Marketing Analytics in 2026: Predictions from the People Who Measure Everything

Nov 25, 2025

9 min read

article card image
Read 
Customers
Amplitude Pathfinder: How Dan Grainger Bet on Amplitude & Won

Nov 25, 2025

16 min read

article card image
Read 
Product
Getting Started: Driving Product Engagement by Obsessing Over Activation

Nov 24, 2025

4 min read

Explore Related Content

Integration
Using Behavioral Analytics for Growth with the Amplitude App on HubSpot

Jun 17, 2024

10 min read

Personalization
Identity Resolution: The Secret to a 360-Degree Customer View

Feb 16, 2024

10 min read

Product
Inside Warehouse-native Amplitude: A Technical Deep Dive

Jun 27, 2023

15 min read

Guide
5 Proven Strategies to Boost Customer Engagement

Jul 12, 2023

Video
Designing High-Impact Experiments

May 13, 2024

Startup
9 Direct-to-consumer Marketing Tactics to Accelerate Ecommerce Growth

Feb 20, 2024

10 min read

Growth
Leveraging Analytics to Achieve Product-Market Fit

Jul 20, 2023

10 min read

Product
iFood Serves Up 54% More Checkouts with Error Message Makeover

Oct 7, 2024

9 min read

Blog
InsightsProductCompanyCustomers
Topics

101

AI

APJ

Acquisition

Adobe Analytics

Amplify

Amplitude Academy

Amplitude Activation

Amplitude Analytics

Amplitude Audiences

Amplitude Community

Amplitude Feature Experimentation

Amplitude Guides and Surveys

Amplitude Heatmaps

Amplitude Made Easy

Amplitude Session Replay

Amplitude Web Experimentation

Amplitude on Amplitude

Analytics

B2B SaaS

Behavioral Analytics

Benchmarks

Churn Analysis

Cohort Analysis

Collaboration

Consolidation

Conversion

Customer Experience

Customer Lifetime Value

DEI

Data

Data Governance

Data Management

Data Tables

Digital Experience Maturity

Digital Native

Digital Transformer

EMEA

Ecommerce

Employee Resource Group

Engagement

Event Tracking

Experimentation

Feature Adoption

Financial Services

Funnel Analysis

Getting Started

Google Analytics

Growth

Healthcare

How I Amplitude

Implementation

Integration

LATAM

Life at Amplitude

MCP

Machine Learning

Marketing Analytics

Media and Entertainment

Metrics

Modern Data Series

Monetization

Next Gen Builders

North Star Metric

Partnerships

Personalization

Pioneer Awards

Privacy

Product 50

Product Analytics

Product Design

Product Management

Product Releases

Product Strategy

Product-Led Growth

Recap

Retention

Startup

Tech Stack

The Ampys

Warehouse-native Amplitude